Science Cultures in a Diverse World: Knowing, Sharing, Caring 981165378X, 9789811653780

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Bernard Schiele Xuan Liu Martin W. Bauer   Editors

Science Cultures in a Diverse World: Knowing, Sharing, Caring

Science Cultures in a Diverse World: Knowing, Sharing, Caring

Bernard Schiele · Xuan Liu · Martin W. Bauer Editors

Science Cultures in a Diverse World: Knowing, Sharing, Caring

Editors Bernard Schiele University of Quebec at Montreal Montreal, QC, Canada

Xuan Liu National Academy of Innovation Strategy Beijing, China

Martin W. Bauer London School of Economics and Political Science London, UK

ISBN 978-981-16-5378-0 ISBN 978-981-16-5379-7 (eBook) https://doi.org/10.1007/978-981-16-5379-7 Jointly published with China Science and Technology Press The print edition is not for sale in China (Mainland). Customers from China (Mainland) please order the print book from: China Science and Technology Press. © China Science and Technology Press 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publishers, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publishers nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publishers remain neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Foreword by Pierre Mutzenhardt

The aspiration behind the founding of Science&You was to bring together researchers and practitioners of scientific events engaging with the public on key issues shaping science and society today. Ever since it was first held back in 2005, the event has become a calendar highlight in the international landscape of scientific and technical culture. It is altogether unique in seeking to connect a wide range of stakeholders for the purposes of joint discussions and experience-sharing on the subjects of scientific outreach, activities engaging with the public and communication. The swift developments in science and technology and constant changes in the world around us are raising questions and concerns among citizens—requiring a multidisciplinary scientific approach. One of the main responsibilities researchers have is to answer those questions. To that end, their answers need to be communicated and shared with society more effectively. Science communication is instrumental in safeguarding social cohesion. The crises we are experiencing (from ecological, economic and health points of view) and our current fast-changing, information-driven society further accentuate the need for a close link between science and citizens, which more than ever calls for a pooling of discussions and practices where events that help make science accessible to the mainstream are concerned. Innovating by promoting dialogue between the knowledge fields: this is Université de Lorraine’s motto, and Science&You upholds that message. Over the years this event has been held, we have had the opportunity of seeing the international community getting to grips with these questions and taking part in this common project: to compare experiences, perspectives and cultures. The 2018 Science&You, which Université de Lorraine was delighted to organize jointly with the National Academy of Innovation Strategy, was attended by a host of international experts in scientific communication. On the agenda were such topical issues relating to the subject as scientific communication in the internet age, community science and responsible innovation and research … and this publication presents the most striking strands of thought to emerge from those debates.

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Foreword by Pierre Mutzenhardt

To end, I should like to extend my warmest thanks to our Chinese partners. I very much hope you will enjoy reading this. Nancy, Metz, France

Pierre Mutzenhardt President of Université de Lorraine

Foreword by Han Qide

From its inception in Europe, modern science has evolved from a means to foster enlightenment into a means to master nature. And the cultural context that drives its evolution has become an object of study, from the traditions that inform ‘small’ science to the atmosphere that nurtures ‘big’ science. Modern history witnesses the extraordinary journey of the Chinese intellectuals. It includes a natural view of the unity of humanity and nature, the development of rigorous methods of exegesis and textual analysis, and the commitment to truth and facts of modern science. Quite consciously at the very beginning, they saw in modern science the means to ‘save the country’ and ‘serve the people’. However, as it took hold and developed in China, interest in the cultural context that accompanied its development grew. Open, broad-minded and committed to humanity, China has fostered an inclusive culture bridging past and present, the East and the West. With its cultural distinctiveness, relevance and diversity, China’s culture of science is a major addition to the world. In the fall of 2018, an iteration of the Science&You Conference was held in China in a partnership between the University of Lorraine and the National Academy of Innovation Strategy, China Association for Science and Technology, bringing top scholars from around the world. With ‘Knowing, sharing, caring: New insights for a diverse world’ as its theme, attesting to the pluralistic and diverse character of the culture of science, it set the stage for an exciting exchange of rich and stimulating ideas. Following a rigorous peer-review process, the most significant contributions have been collected in the present book: Science Cultures in a Diverse World. We hope that it will help to further academic research and mutual understanding. Science&You is a major international conference, and we look forward to future collaborations with

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Foreword by Han Qide

the University of Lorraine as China continues to establish itself as a major platform for international exchanges and as a contributor to the culture of science worldwide. Beijing, China

Han Qide Academician of the Chinese Academy of Sciences; President of the Western Returned Scholars Association; Honorary President of the China Association for Science and Technology; Past Chairman of the Jiu San Society; Past Vice Chairman of the 12th CPPCC National Committee

Introduction: New Questions, New Objects, New Approaches

This book includes an opening keynote address and 17 contributions from 33 authors from 16 different countries. With the exception of the opening address, these contributions were selected from among a hundred talks given in the 20 panels of the 2018 Science&You conference, which was jointly organized by the Chinese National Academy of Innovation Strategy (NAIS, Beijing) and the University of Lorraine (France), in Beijing, China, from 15 to 17 September; the event attracted more than 400 delegates.1 Science&You promotes and valorizes science cultures. As such, it is the offshoot and development of the ‘Hubert Curien Days’ (Journées Hubert Curien) on science culture, named after the French physicist and minister of research and technology who founded the event with the ambition of creating an unmissable international forum for science culture researchers and professionals.2 Following openings made by NAIS after the 2015 Science&You conference, held in Nancy (France), a collaboration was brokered with the University of Lorraine with a view to organizing the conference in China in September 2018. This will to develop science culture coincided with that of the China Association for Science and Technology (CAST), which was celebrating its 60th birthday in 2018.

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Each talk was selected after a double-blind peer-review process. The selection of the 17 chapters of the book likewise involved a double-blind peer-review process: immediately following the conference, the most significant talks were selected after a first round of selection by the co-editors, before being subsequently reviewed by the prospective authors themselves following the second peer review. 2 Hubert Curien (1924–2005), a Lorraine native and career physicist and professor, successively held the posts of General Director of the French National Centre for Scientific Research, President of the French National Centre for Space Studies, President of the European Space Agency and Minister for Research. Over his whole life, he promoted and valorized science culture. The Journées Hubert Curien were founded in 2005 in his memory and to carry on his legacy. In 2012, following their fourth iteration, they became Science &You. ix

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On History With a risk of oversimplifying things, we can say that China manifested its commitment to widening science culture as early as 1949, the very year of the founding of the People’s Republic, and that commitment has been constantly reaffirmed (Yin and Li 2020). In China, as in Western nations, a movement for the popularization of scientific thought manifested itself early in the 19th century, well before the state took up the mantle (Schiele 1994; Gascoigne et al. 2020). However, it was not until the 1980s that Western governments became aware of the necessity of a science culture, adopting proactive policies and allocating greater funding. In this regard, we stress, on the one hand, the role of the United Nations Educational, Scientific and Cultural Organization, beginning in the 1960s, in promoting a humanist vision of the appropriation of scientific culture in an approach focusing on personal and collective growth, and, on the other hand, the impact of reports produced by the Organisation for Economic Co-operation and Development, also beginning in the 1960s, which shed light not only on the growing political, economic and social role played by sciences and technologies in contemporary societies but also on the growing importance of the diffusion, access to and the sharing of science culture for their continuous scientific and economic development. Thus, maintaining the growth necessary to satisfy the expectations of the population rested not only upon scientific and technological development but also on the collective ability to contribute to it and to adapt to the changes it provokes: economic, cultural, social and technoscientific development were inextricably linked (Godin 2005). Thus, from the 1980s onwards, science culture, under the heading of ‘science literacy’, beyond its role in personal growth, had become a prerequisite for economic development and the general evolution of societies, since it gave individuals a greater understanding of and a greater say in the issues raised by technoscientific advances.

On Research This newfound valorization of science culture also stimulated the first wave of research on the public diffusion of science. If we omit precursors, such a Charles Percy Snow’s highly influential 1959 The two cultures—which not only contrasted scientific and literary cultures but judged the latter to be out of phase with the contemporary world—Hillier Kriegenbaum’s 1967 survey of media coverage of science and Philippe Roqueplo’s 1974 analysis of the media portrayal of science, the science communication research field truly began with the creation of ministries of science and technology and the adoption of proactive policies for the publicization of science. Needless to say, the ‘two cultures’ thesis keeps quiet about its very precondition (i.e. the perspective from a third culture, that of anthropology and the social sciences), from which the struggle between the protagonists of the ‘two cultures’ is analysed.

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From that third perspective, the issue also becomes undeniably one of plurals: we are dealing with science cultures. The 1982 Colloque national sur la science et la technologie (National Conference on Science and Technology), inaugurated by then Research and Technology Minister Jean-Pierre Chevènement, crystallized and catalysed in France this dual movement of the valorization and diffusion of sciences, leading to the creation of the first French cultural centres of science, technology and industry. The Royal Society working group led by Sir Walter Fred Bodmer in 1985 would play the same role for the UK, since it would lead to the creation of the Committee for the Public Understanding of Science, which was tasked with implementing its recommendations. In China, a new impulse was given by Deng Xiaoping at the March 1978 National Conference, which led directly to the opening of the country’s first science and technology centres as part of a multipurpose network of facilities providing a wide range of activities, from exhibitions to training programmes (Yin and Li 2020). More recently, on the initiative of Xi Jinping, China’s National Action Plan for Scientific Literacy 2016– 2020 was adopted (Zhihao 2018). Thus, for 70 years in China and for 40 or so in the West, the promotion and valorization of science culture, as well as the development of tools to measure its effects, have been high priorities for a majority of nation-states and therefore an object of research and public debate. Science and technology culture are now more than ever at the very heart of the social project, and all countries, to varying degrees, participate in it. Raising scientific literacy, improving the image of the sciences, involving the public in debates and encouraging the young to pursue careers in the sciences: those are the aims underlying every new policy and every new measure adopted. Let us add that the twofold purpose of communicating science and evaluating its effects upon populations is regularly reaffirmed, bringing back science—and, today, technology—to the forefront every time new and life-changing advances come over the horizon. Thus, the very destiny of any society is now entwined with its ability to develop a genuine science and technology culture, accessible for participation not only to the few who, by virtue of their training or trade, work in the science and technology fields, but to all, thereby creating occasions for society to debate and to foster a positive dialogue about the directions of change and future choices. When organizing and attending a conference at which researchers from different places of the world gather, we inevitably find that things work differently in different contexts. It is therefore useful to distinguish between ‘scientific culture’ and ‘science culture’. The former term puts the focus on the ethos and practice of science labs and research establishments and how they are resourced, while the latter term focuses more outside the lab to trace the presence of ‘science’ as a reference in public attention and interests, in mass media discourse and in public attitudes of trust, support and reservation (Bauer 2015; Bauer et al. 2012; Bauer et al. 2019). If we focus on the latter, we inevitably start talking about ‘science cultures’ in the plural, not least to accommodate the rising tide of empirical evidence to which this book makes a contribution.

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From Conference to Book This is why this conference was organized on the theme of Knowing, sharing, caring: new insights for a diverse world, which was derived from the observation that globalization rests upon diversity: diversity of science communication strategies and practices; diversity of contexts in which communication actions take place; diversity of publics at which science communication is aimed; diversity of reception; diversity of understanding; diversity of questions, issues and the responsibilities of science communicators as well as scientists; diversity of research in the science of science communication, models, approaches, applications and impacts. This book, like the conference, acknowledges that diversity of contexts, publics, research, strategies and new innovating practices because the conference aimed to stimulate exchanges, discussions and debates, to initiate a reflection conducive to decentring and to be an opportunity for enrichment by providing the reader with means to achieve the potentialities of that diversity through a comparison of the visions that underpin the attitudes of social actors, the challenges they perceive and the potential solutions they consider. Thus, the book aims first and foremost to raise questions in such a manner that readers so stimulated will feel compelled to contribute and will do so. In this spirit, however significant, the results presented and shared are less important than the very questions they seek to answer: How are we to rethink the diffusion, the propagation and the sharing of scientific thought and knowledge in an ever more complex and diverse world? What to know? What to share? How do we do it when science is broken down across the whole spectrum of the world’s diversity? By compiling the conference talks judged the most significant, this book aims to build upon the fact that, although science is truly at the heart of our contemporaneity, it is lived through a multiplicity of forms and ways of being, none of which is able to claim sole legitimacy. What, then, are the emerging practices of scientific communication? Which ones simultaneously innovate and promote critical thought in the specific contexts in which they are put into practice? What lessons can be learned? How can those practices be adapted from one context to another? To what extent do they engage the responsibility of the actors involved? Those are the challenges science communication and science communicators are facing today in order to ensure the development of science cultures.

Opening The opening speech given by Massimiano Bucchi (Italy) set the tone of the conference by pointing out the challenges faced by science communication in this age of digital media: an age of proliferation of the forms of diffusion, of the accelerated entry of information into circulation and of ‘real time’ in which traditional safeguards work only sporadically, as scientists themselves are sometimes carried away. This is the

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context, he said, that compels a critical reappraisal of the accepted understanding of the science–society relationship. That is the aim of this book: to decentre oneself from traditional approaches and explore new paths with, ultimately, the aim of rethinking the science–society relationship. Thus, the various chapters address issues rarely raised in science communication and adopt perspectives that are likewise rarely mobilized, for the aim is to account for the diversity of reasonings and favour new approaches in order to enrich the spectrum of research in science communication. In other words, to rethink science communication, and therefore science cultures, ‘outside the envelope’.

Cross-Cutting Themes At the risk of oversimplifying, we can pinpoint a number of cross-cutting themes revolving around the central, though far from only, the theme of the conference and the book. Theoretical Concerns The majority of our authors have in common the will to renew reflection by addressing less familiar issues, by thinking outside the box, so to speak, and by exploring new theoretical and methodological approaches. This will to develop explicit, coherent and often transdisciplinary theoretical frameworks breaks radically with the great number of one-off empirical studies that clutter the field. From an epistemological perspective, Chap. 1 questions the disciplinary status of ‘science communication’ claimed by many authors, arguing instead that most research is in fact ‘object oriented’. Thus, the authors of Chap. 4 argue that the study of science festivals mobilizes three research fields: science communication, museology and education. In the same vein, Chap. 8 proposes a theoretical model of the translation of the science subculture for other groupings of subcultures. From another standpoint, Chap. 9 argues for the international coordination of research on the assessment of science culture as the necessary condition for a solid scientific basis. Chapter 13, departing from technical considerations, widens the definition of ‘science culture’ by developing a theoretical approach resting upon the perception of the road as ‘social space’ to assess the public’s attitudes towards new types of vehicles. Social Dynamics Another trend expressed in nearly all chapters is the inclusion of ‘social dynamics’— in the broad sense—as a specific parameter, whether through the mobilization of established theoretical frameworks derived from other disciplines or through the development of new ones. Thus, Chap. 2 insists upon the interactional dynamic inherent in any participatory approach. In the same spirit, Chap. 6 addresses the science–society relationship by examining the role played by researchers in their relations with citizens. Chapter 7 discusses, with a strong theoretical grounding, the effect of religious beliefs upon the attitudes of social groups towards science.

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Mass Mediation In addition to the opening speech stressing the structuring effect of digital media in the contemporary world, Chap. 5 takes note of the transformation of science publicization practices as a result of the explosion of social media, while Chap. 10 examines the impact of stories spread by the media, and especially their impact on the acceptance of high-tech artefacts, such as artificial intelligence. Chapter 15, by comparison, examines the impact of the digitalization of society upon science culture industries. The Role of the State Four chapters address the key role of the state. In the wake of the promulgation of an innovation policy in China, Chap. 12 analyses the risks inherent in any policy for science and technology innovation. From the standpoint of science culture, Chap. 14 examines the scope of the French policy for the valorization of science culture, which tasks researchers with contributing to the publicization of the sciences. In the same vein, Chap. 16 analyses the expected reconversion of the discourse of Chinese science museums towards the promotion of innovation. Chapter 17 shows that the drying up of Brazilian state funding for the publicization of the sciences has led to a reduction in activities and audiences. The Role of Institutions Little attention has been paid to the role of institutions in the publicization of the sciences, even though they are increasingly involved. For instance, the 2012 Science&You conference focused on the contribution of university researchers to the public diffusion of the sciences. From a comparative standpoint, Chap. 3 discusses the diffusion practices of researchers from institutions from eight countries. Technology The shaping of technological change, the challenges it offers and the debates about its directions are integral to a reflection on science culture and, in that spirit, Chap. 11 examines the attitude of scientists from various fields towards a new technology (genetic modification).

Overview The book is divided into four parts, covering six axes of reflection (Table 1).

Part I Science Communication at the Crossroad Chapter 1, written by Bernard Schiele (Canada), Toss Gascoigne (Australia) and Alexandre Schiele (Israel), examines the plural and polysemic nature of the terms used by researchers in science culture and by science mediators. Those terms express

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Table 1 Distribution of focus points in chapters (dark grey: main focus; light grey: secondary focus) Chapter

Theoretical

Social

X

X

State

Media

Technology

Institution

Part 1 1 2

X

3 4

X X

X

5

X

Part 2 6

X

7

X

X

8

X

X

9

X

Part 3 10

X

X

11

X

12 13

X

X X

X

X

Part 4 14

X

15

X

16

X

17

X

X X

both ensembles of significant and varied practices disseminated and circulating in the social space and the representations accompanying them. According to the authors, that vagueness, made manifest by the substitutability of terms, is one of the specificities of a field, the historical, social, cultural and economic overdeterminations of which often supersede every other preoccupation by providing a preformed interpretative framework when the need to characterize and describe public science diffusion practices arises. The heterogeneity of the field demonstrates that the various lines of research that are today united under the term ‘science communication’, or any other umbrella term that spontaneously imposes itself as self-evident to researchers, have not succeeded in erasing the context, which is reified in their research objects and discourses.

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Per Hetland (Norway), in Chap. 2, discusses the ongoing trend termed ‘participatory science communication’, which is part of a wider movement called ‘Science 2.0’. The movement aims to actively engage citizens in order to achieve concrete objectives, such as environmental protection. This standpoint clearly breaks with the deficit and conceptual models, since citizen engagement, here necessary to achieve specific targets, is also a necessary condition for the acquisition of the knowledge necessary to achieve them. Such a dynamic is only possible on three conditions: ‘access, interaction and participation’. In other words, this perspective departs from the traditional individual-centred approach in favour of a collective interactional dynamic in which experts and laypeople mingle and exchange to harmonize their abilities in order to better coordinate their common action to reach a specific goal. In Chap. 3, Marta Entradas (Portugal) examines the public communication function of a number of major research institutions in eight countries. She questions the specific role played by the ‘meso-level’ of the organization (i.e. where research is taking place), which she contends remains largely unknown. From a comparative standpoint, she seeks to understand how the science communication function manifests itself at this organizational level in various countries by studying the real practices of each institution. This research especially takes into account the growing role of institutions, and specifically research structures, in the public communication of science. According to her, those actions geared for the public are in response to clear demands for greater engagement and transparency on the part of researchers and institutions and contribute to a decentralizing trend in public science communication activities within institutions in all the countries studied. Nevertheless, she warns of the risk of ‘communication becoming a marketing tool detached from the original aims of public engagement’. Elpiniki Pappa (Greece) and Dimitrios Koliopoulos (Greece), in Chap. 4, show that, notwithstanding their long history, science festivals underwent a renewal 40 or so years ago and have become a global phenomenon. And, although their importance has often been stressed, they have rarely been objects of research—a situation that the authors seek to remedy. From a study of Greek science festivals, they endeavour to describe and categorize the festivals’ general characteristics, and especially to assess them. However, here again, little research has been conducted, and most studies have relied on closed-question questionnaires and self-reporting. Thus, the ‘lack of a solid theoretical framework for the evaluation of science festivals’ is not only blatant but considerably limits the ability of researchers to assess the ‘potential cognitive impact on visitors, and particularly on school students’ of science festivals. And not only is the lack of such a framework an obstacle to any systematic assessment; they argue that a framework could be developed only by drawing upon research fields that address the diffusion of scientific knowledge from distinct standpoints: science communication, science museology and science education. In Chap. 5, Michelle Riedlinger (Australia), Alexandre Schiele (Israel) and Germana Barata (Brazil) discuss the impact, in the Canadian context, of the arrival of new communication technologies and the subsequent embrace of social media upon science communication practices, forcing science communicators to adapt themselves, especially as new voices were being heard, new values were being expressed

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and new modes of interactions, such as ‘informal community networks’, overtook traditional institutional forms. The authors endeavoured to map emerging practices online in order to ‘gain a better understanding of the emerging activities of online science communicators and what they value’. However, according to them, this reconversion was spurred not only by the new technologies, but also by the disengagement of federal and provincial governments from science culture programmes, the weakening of traditional media now directly competing with emerging modes of communication, and the increasingly limited role of journalists as gatekeepers, all of which trends are accelerating adaptation to and integration into the new mediascape. Thus, in this fluid mediascape, the authors see as significant both attempt to establish ‘good’ online science communication practices and the associations of science communicators promoting them. Finally, even if the role played by traditional media continues to distinguish Quebec from the other Canadian provinces, the new preoccupation with greater inclusiveness and equity is just as strong in Quebec as elsewhere in Canada.

Part II Science–Society Dynamics In Chap. 6, Anne M. Dijkstra (Netherlands) examines the responsible research and innovation movement and shows that it goes well beyond engagement and individual participation because, by arguing for a science that is responsible to society, it directly questions how researchers see their own role and their relations with citizens. This movement, according to her, is one of the signs of a transformation of the science–society relationship. From this standpoint, social responsibility takes precedence: the aim is to produce knowledge that meet specific needs in specific contexts and for specific populations, and that implies the development of new practices. To explore ‘what the practices mean for the communication process and the role of the researchers and citizens involved’, the author compares various projects in three countries. That comparison leads her to conclude that ‘researchers in different situations are becoming more aware of their role as researchers towards society. They engage with society, are involved in science education and communication, and reflect on ethical conduct at the beginning of projects or during the research process’. In that respect, this chapter cuts across the themes discussed in Chap. 3. In Chap. 7, Bankole Adebayo Falade (South Africa) and Refilwe Mary-Jane Ramohlale (South Africa) address science communication from another standpoint— that of social groups—and specifically the prior effect of the religious beliefs of various (genuine or symbolic) African social groups on the acceptance or rejection of the ‘unfamiliar’ revealed by science. Thus, among the limits to the diffusion of science in Africa, they stress the continent’s linguistic diversity (1000-plus mother tongues), its diversity of religious beliefs and its social inequalities, all of which restrict access to scientific information: ‘these multi-faith, polyethnic and relatively poor publics create the diverse contexts for science communication in Africa, manifesting in a variety of impacts as social groups appropriate science differently.’ The

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authors’ comparative approach, drawing in part upon the works of Pierre Bourdieu and Serge Moscovici, leads them to differentiate and characterize the attitudes of various groups towards science (associated with progress) in terms of the ‘space of science’ in order to stress the symbolic dimension as well as the positioning of social groups against each other. They conclude, on the one hand, that the association of science with progress varies among groups because that relationship is constantly modulated by the interplay of various factors (gender, age, religion, income and so on). On the other hand, they show that science and belief coexist within the same groups and that, although religious belief does not entail an anti-science attitude, the level of acceptance of science as an expression of progress varies among religions. Gauhar Raza (India) and Surjit Singh (India), in Chap. 8, focus on the same question, this time in India, but raise the theoretical issue of cultural distance. Their contribution recalls the main conceptual moments of the development of the communication model. According to them, the works of Claude Shannon and Warren Weaver were a turning point because they asserted that ‘the fundamental problem of communication is that of reproducing at one point either exactly or approximately a message selected at another point’, which soon inspired social scientists to apply that model to social transmission processes. We can see that the idea of ‘distance’, although not explicitly articulated, was nonetheless latent. Raza and Singh add another element: culture, which they see as a key factor in the propagation of science, since science is a ‘social activity’, and scientists not only ‘have a distinct culture’ but are ‘agents of knowledge’. Without suggesting a definition of science culture—an impossible task, according to them—they assert that each new idea emerges from a subculture and that time is needed for its wide dissemination (we could add, those new ideas become fruitful only through that process). This is why they define ‘cultural distance … as the distance that a world view, attitude, perception or idea, generated within one cultural context, travels on a timescale before it is democratized within the thought structures of other cultural groups’. From a survey they conducted, they identified four factors, intrinsic to the nature of scientific knowledge, that are at the heart of cultural distance and must be considered when actions involving cultural groups, whose distance to reference knowledge has been measured, are envisaged. In Chap. 9, Michel Claessens (Belgium), who also agrees that a consensual definition of culture remains out of reach, wonders whether what is called ‘science culture’ can, in fact, be measured. Opting for an operational approach, and following Martin W. Bauer and Ahmet Suerdem, he distinguishes ‘scientific culture’ from ‘science culture’, defining the latter as ‘the general environment (society) in which science and technology development while being supported and considered as social values’, thus making his own the conclusions of works correlating ‘people’s knowledge of science’ and ‘economic development’. And this is one of the reasons why, he says, a number of countries survey the level of science culture of their populations, although the notion remains ambiguous. As an example, he describes the long tradition of promotion and valorization of science culture in France and shows that a wide range of initiatives and activities continue to enrich and thus perpetuate the spirit and values associated with science and technology. However, he laments that the European Union ended its programmes supporting initiatives across Europe, including a European Science

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Week, leaving to individual countries the burden of organizing such an event in the absence of overall coordination. Nevertheless, Eurobarometers, conducted regularly since 1974, continue to provide significant information on the gradual elevation of the level of science culture in the countries surveyed, and thus remain the best argument in favour of coordinating global and comparative surveys of science culture. Claessens also makes the case for an alliance called World Investigation of Science Culture (WISE) to define, measure, promote, support and connect science culture globally. He maintains that only an initiative such as WISE would provide ‘robust scientific grounds for science culture and sharing data and good practices’.

Part III Public Attitudes In Chap. 10, Ahmet Suerdem (Turkey) and Sherat Akkilic (Turkey) discuss how the media depict high-tech artefacts, such as artificial intelligence (AI), and how to ‘help the audience to relate their everyday knowledge and experiences to the potential impacts of a given technology’. They say that the study of media stories—‘media framing’—is fundamental because the media play a part in the formation of those representations, and therefore in people’s assessments of the potential risks or benefits of new technology. However, the difficulty in analysing ‘frames’ arises because frames simultaneously incorporate cognitive and cultural elements, rendering semiotic or content analysis methods inoperative. Instead, the authors opt for a conceptual mapping derived from discourse analysis and drawing upon computational linguistics, which proves particularly useful for comparative approaches, such as the present study of the ‘media framing’ of AI by various newspapers in different countries. The results show that the ‘media in different countries represent AI in ways that reflect the cultural, societal and political context in which they are embedded’. Since the structuring effect of the context is already well known, the true benefit of this method lies in its ability to process a great quantity of textual material, which is especially useful when science journalists must cover complex situations, allowing them to ‘focus more on deeper analyses of specific issues’. In Chap. 11, in the same vein, Jianbin Jin (China), Xiaoxiao Cheng (China) and Zhaohui Li (China) discuss the attitudes of scientists towards new technologies and the products of those technologies, in this case genetically modified organisms (GMOs). Whereas past surveys have sought to identify the relationship between a population’s knowledge about new technologies and its attitudes to the risks posed by those technologies to determine whether the former affects the latter and, if so, whether the effect is positive or negative, they instead surveyed 12,000 Chinese experts because experts ‘usually play crucial roles in policymaking in contemporary governance’ and influence the media coverage and the public perception of emerging technologies. They are key opinion leaders, and yet, in contrast to other opinion leaders, their scientific training functions as a lens through which they cognitively approach the issue and they ‘therefore base their attitudes to GMOs on a cognitive foundation’. However, other factors weigh in the formation of attitudes, such as a

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person’s domain of expertise or institutional affiliation. All in all, the authors conclude that experts generally tend to view GMOs positively, although their attitudes are far from uniform. In Chap. 12, Yandong Zhao (China) and Miao Liao (China) similarly raise the question of novelty and innovation, but this time from the perspective of the risk associated with innovation in a context in which the Chinese Government has set innovation as a national goal in the pursuit of economic development. They argue for responsible research and innovation (RRI) using consultation and dialogue between stakeholders—the government, the scientific community, the public and industry—to ensure that efficiency and responsibility are evenly balanced. However, they lament the fact that ‘communication and interaction among various actors in China is still weak, and are not tightness enough, and it is difficult to form a “synergy” in RRI practice’, especially when the political, economic, social and ethical risk inherent in any innovation drive calls for such mechanisms. Thus, innovation cannot sustain itself without some tolerance for failure. The authors conclude that ‘innovation is sustainable only when it is recognized by society, accepted by the public and serves people’s well-being. This is the only way to avoid and mitigate innovation risks and achieve sustainable economic and social development. To achieve that goal, scientific communication is needed to create a better national environment for supporting innovation in various sectors.’ In Chap. 13, Chris Tennant (UK) examines attitudes to AI and its use in the future deployment of autonomous vehicles in a social space until now reserved for human drivers but that will soon have to be shared. He emphasizes, as have other researchers before him, that the still uncertain public mood will be a decisive factor in the acceptance of this rising technology and questions why research has until now focused mainly on the technical aspects rather than on the considerations of the public. As in all other chapters in Part III, the issue is the public’s reaction to new technology and to repeated exhortations to accept it as inevitable. Similar to Suerdem and Akkilic, Tennant treats the representations held by the public—in this case its conception of mobility in the social space—as a filter conditioning the reception and assimilation of information on new technology. This is why he opted for a perspective that sees the ‘road’ itself as a complex system in which multiple dynamics are in constant interaction, with the aim of identifying how representations of the road as a social space dictate drivers’ interactions with other drivers—their ‘driving sociability’. Tennant reminds us that any knowledge is social and therefore entails behaviours, beliefs, opinions and judgements, and that any attempt to apprehend the diffusion or appropriation of knowledge without factoring in its social nature is both simplistic and partial.

Part IV Professions and Institutions In Chap. 14, Samuel Cordier (France) asserts that, although the state now plays a key role in the promotion and valorization of scientific, technological and industrial culture, involved actors are constantly innovating to reach new publics. In France,

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as in many countries, actors ranging from universities to research institutions have been at the forefront of initiatives such as the ‘science shops’ found in many regions, often acting in advance of state initiatives. According to Cordier, the ‘creation of places dedicated to scientific culture in the regions is closely linked to the entry of science into cultural spaces and the emergence of cultural centres’; that is, science culture is now part of social discourse. This movement picked up speed with the growing involvement of the state, since the ‘spreading of humanist culture, notably through the development of the humanities and social sciences, and scientific, technical and industrial culture … is now part of the mission of higher education, which must promote the interaction between science and society’. In other words, science culture is not only now an essential part of the social space, but its place in that space is ensured by the state-mandated mobilization and obligation of researchers to contribute to it, leading to a great diversity of practice. However, the paradox is that our era is characterized by the proliferation of disinformation, fake news and pseudoscience, and that is why ‘it is more necessary than ever to develop critical thinking. By sharing the scientific approach, citizens can be empowered to develop and reinforce their curiosity, open-mindedness and critical thinking.’ Fujun Ren (China), Xuan Liu (China) and Jianquan Ma (China) prefer to speak of the ‘science popularization’ (SP) industry rather than ‘science culture’. In Chap. 15, their focus is on all SP activities, whether non-profit or for-profit, and all the steps from production to consumption. They emphasize that the state promotes and facilitates the development of business-oriented popular science activities within the wider development of cultural industries; that is, two sectors coexist under the coordination of the state. However, the authors emphasize the digital turn: ‘science communication has entered a new era using highly integrated digitalization in society and the economy, so the SP industry in China is gradually changing’. They say that one of the factors that account for this push is the inherent interactivity of new media— ‘SMS, WeChat, online forums, instant communication and other channels’. And this factor explains why the Internet has become the main source for science and technology information, although television remains important. CAST took advantage of this new context to launch China Science Communication, a national platform, and GuoKe, with ‘Science and technology is interesting’ as its motto. In Chap. 16, Xiang Li (China), Xuan Liu (China) and Peng Ren (China) discuss the rapid development of China’s network of science and technology museums over the past three decades and the recent government-mandated obligation to raise the people’s level of scientific literacy in order to innovate and transform China into a powerful country of science and technology. According to the authors, this is a logical development of the mission of Chinese science and technology museums, since the museums have always stressed the practical value of science, making them natural auxiliaries of the education system. Their eminently didactic mission is ‘the dissemination of knowledge … All their other functions (the promotion of culture, experience of science and participation in science) are developed on that basis.’ This is why, the authors argue, the museums must now adapt and ‘think about their contribution to innovation’ in order to ‘fit into the country’s overall innovation culture’. Furthermore, that adaptation meets a need for deeper change in society: ‘it is worth

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noting that innovation-oriented knowledge and skills are becoming an increasingly common public demand and are the future direction for the expansion of science literacy.’ In Chap. 17, Luisa Massarani (Brazil) and Jessica Norberto Rocha (Brazil) similarly address the question of science museums in their own country. As is the case for China, they stress that the past three decades have been characterized by the rapid development of the museum sector, including the founding of a hundred or so new museums and the adoption of policies to try to ‘extend their reach to more diverse audiences and to forge relations with publics who have not traditionally been frequent visitors.’ However, while the 2000s saw a great flurry of science culture policies, since the mid-2010s resources have dried up and political priorities have shifted: the Department of Science, Technology and Social Inclusion and its Office for the Popularization and Dissemination of Science and Technology have closed, the ministry in charge has now merged with another, and funding was completely withdrawn in 2019. The authors draw our attention to the fact that museum attendance peaked in 2015 before falling sharply, which they see as proof of the efficiency of the 2000s policies. This new context leads them to rethink how to meet the needs of those who do not visit science museums, whether they have no physical access or are not in the habit of visiting science museums, stressing the many and novel science communication strategies devised by mediators to reach them.

Acknowledgements This introduction would be incomplete without acknowledging all those who made possible the conference and, therefore, this book. We thank the presenters and the members of the scientific committee who made the conference the success it was, and the authors who agreed to develop their contributions after the second round of peer reviews. Without them, this book would never have seen the light of day. We also extend our thanks to all the individuals and organizations that supported the conference: Hui Luo of CAST, who at the time was the director of NAIS; Fujun Ren, her successor at NAIS; and Pierre Mutzenhardt, President of the University of Lorraine. We also extend our thanks to Julie Adam and Nicolas Beck of the University of Lorraine and Ji Zao, Hailing Xu and Yanling Xu from NAIS, who coordinated the organization of the conference. We extend our final thanks to Fujun Ren for supporting the idea of a publication and to James Dixon for copyediting the text. Bernard Schiele University of Quebec at Montreal, Montreal, QC, Canada [email protected]

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Xuan Liu Research Associate, Deputy Director of the Institute of Innovation Environment, National Academy of Innovation Strategy, Beijing, China [email protected] Martin W. Bauer London School of Economics and Political Science, London, UK [email protected]

References Bauer MW (2015) Making science is global, science culture remains local. J Sci Temper 3(1/2):44– 55 Bauer MW, Shukla R, Allum N (eds) (2012) The culture of science—how the public relates to science across the globe. In: Routledge studies of science, technology & society, vol. 15. Routledge, New York Bauer MW, Pansegrau P, Shukla R (eds) (2019) The cultural authority of science—comparing across Europe, Asia, Africa and the Americas. In: Routledge studies of science, technology & society, vol. 40. Routledge, London Bodmer WF (1985) The public understanding of science. The Royal Society, London Gascoigne T, Schiele B, Leach J, Riedlinger M, with Lewenstein B, Massarani L, Broks P (2020) Communicating science: a global perspective. Australian National University Press, Acton Godin B (2005) Measurement and statistics on science and technology—1920 to the present. In: Routledge studies in the history of science, technology and medicine, vol. 22. Routledge, New York Krieghbaum H (1967) Science and the mass media. New York University Press, New York Ministère de la recherche et de la technologie (1982), Recherche et Technologie, Actes du Colloque national, 13–16 January. La Documentation française, Paris Roqueplo P (1974) Le partage du savoir. Éditions du Seuil, Paris Schiele B (1994) When science becomes culture. University of Ottawa Press, Québec Snow CP (1959) The two cultures, the Rede lecture. Cambridge University Press, London Yin L, Li H (2020), China: science popularization on the road forever. In: Gascoigne T, Schiele B, Leach J, Riedlinger M, Lewenstein B, Massarani L, Broks P (eds) Communicating science: a global perspective. Australian National University Press, Acton, 205–226 Zhihao Z (2018) Xi urges enhancing scientific literacy. China Daily, 18 September, http://www.chi nadaily.com.cn/a/201809/18/WS5ba040b7a31033b4f4656900_1.html

Opening Address

The Challenges of Science Communication 2.0: Quality, Credibility and Expertise Abstract What are the key challenges for science communication in the age of digital media? Are they entirely new or, rather, occurring in a different communicative context of long-standing issues pertaining to the credibility and reliability of information and the role of experts? Mystification for propaganda, also involving scientific content and scientists themselves, has certainly not been introduced with the Internet. In the context of a ‘crisis of mediators’, the quality of public communication of science is—even more than in the past—highly dependent on the quality of research produced and published in specialized contexts. New research is increasingly pushed in real time into the public domain without being ‘filtered’, as was the case in past decades, by professional mediators and popularizers. This inevitably connects science communication at large with trends causing major concerns in the world of research policy and academic publishing: for example, a significant rise in retractions, the emergence of ‘predatory journals’ and lack of and failure in replicating studies. The contemporary communicative landscape clearly places new and greater responsibility on researchers and their institutions, who are increasingly active in communication to the ‘end user’ and not always prepared to deal with the dynamics and potential risks of such engagement. More generally, we could see in this landscape relevant challenges for science in social research and opportunities to rethink some of the key concepts in this area. Keywords Science · Science communication · Science in society · Trust in science · Democracy

Challenges in Science Communication Recently, wide-ranging discussions about so-called “post-truth” have significantly involved science-related issues and science communication. xxv

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The theme of credibility and reliability of information is obviously central for science communication and public understanding of science. However, some themes deserve more attention in this context. We live in a communication environment that is radically different from the past, nevertheless, we paradoxically continue to invoke traditional forms of certifying the trustworthiness of information. In the age of ‘science communication 1.0’, if we wish to call it that, the reputation of the source or journal brand was enough to reassure us (for good or for ill) of the credibility of content. ‘I read it in the newspaper’ and ‘It was on the TV news’ were expressions often used to close a discussion. Nowadays, such guarantees seem no longer viable. The Internet hosts a deluge of citations dubiously attributed to famous thinkers and scientists in an attempt to cling to their authority and prestige. Some time ago, the magazine New Scientist collected a long series of quotes attributed to Einstein (including one widely spread on the disappearance of bees) but never actually said or written by the famous physicist.3 ‘A scientist said it’ is increasingly and confusingly used as a synonym for ‘scientific’. The quality of information has a cost—in science communication as in other domains—and we cannot expect such quality from social media networks whose core business is not about informing or publishing and, furthermore, when people are not willing to spend a few euros or dollars to read a newspaper or magazine. To make an analogy with gastronomy, it is as if, when accustomed to stuffing ourselves at a cheap, all-inclusive buffet, we would suddenly expect to find haute cuisine delicacies there. Even if such delicacies were there, it is doubtful that we would be able to distinguish them from the rest. Mystification for propaganda, also involving well-established scientists, is certainly not a novelty introduced by the Internet. In 1914, some of the greatest German scientists of the time, including seven Nobel laureates, signed and disseminated the so-called manifesto of 93. The manifesto denied a series of facts (including the invasion of neutral Belgium by Germany) for the sole purpose of supporting the scientists’ own nation’s stance.4 The quality of public communication of science is—even more than in the past— highly dependent on the quality of research produced and published in specialized contexts. In the context that I have described elsewhere as a ‘crisis of mediators’, new research is increasingly pushed in real time into the public domain without being ‘filtered’, as was the case in past decades, by professional mediators and popularizers. This inevitably connects science communication at large with trends causing major concerns in the world of research policy and academic publishing: a significant rise in the number of retracted papers (an estimated 1000% in the past 10 years, rising from 30 cases in 2002 to more than 600 only in Medline, 2016); the emergence of ‘predatory journals’ available to publish any content regardless of its quality; and lack of and failure in replicating studies and experiments.5 The now fully discredited 3

‘Einstein said: I didn’t say that’, New Scientist, 8 October 2014, www.newscientist.com. An English translation of the manifesto can be read at https://wwi.lib.byu.edu/index.php/Manife sto_of_the_Ninety-Three_German_Intellectuals. 5 Data from Retractionwatch.com. See also Steen et al. (2013), Ioannidis (2005). A list of predatory journals is available at https://beallslist.weebly.com/. 4

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study on the link between vaccines and autism was at the time published by the prestigious medical journal The Lancet; and the same holds for other studies later proven to be false (or even fraudulent) after their appearance in significant journals. Some cases bear particular interest in the field of science communication. In 2016, the journal Science published a paper by scientists from the University of Uppsala, Sweden, according to which exposure to high concentrations of polystyrene would lead to some fish larvae ‘preferring to eat plastic rather than their natural prey’. The paper’s conclusions obviously appealed to multiple media frames, and they suddenly made headlines globally. ‘Fish eat plastic like teens eat fast food, researchers say,’ summarized BBC News. The paper was retracted by the journal in May 2017 following accusations of data fabrication. However, further reports revealed that the journal had earlier dismissed strong criticism on the paper and its empirical basis submitted by a non-academic, amateur scientist member of the American Association for the Advancement of Science. This led a science journalist to raise the questions: ‘Does citizen science count for nothing in academia? Are amateur scientists expected only to unquestioningly applaud and assist their academic role models, while keeping their scientific criticisms to themselves?’ (Schneider 2017). Rather than joining complaints and despair for an alleged decay of the quality of science communication, we could see in this landscape relevant challenges and opportunities for our research and discussions. Some points for discussion and further research follow.

Quality and Responsibility At least since the early 1990s, we have begun to recognize the fluidity and continuous nature of science communication rather than its segregated, compartmental division between specialist and popular domains. Today, with scientists publicly debating in real time through their Twitter accounts or blogs and users being able to access new research in real time, science communication (as well as the distinction between experts and non-experts) has never been so fluid and porous. This opens new opportunities for scientists’ visibility, as well as risks of pushing rushed conclusions and even fraudulent content into the public discussion. But it also paves the way for a new circularity, opening the scientific debate to the input and scrutiny of quasi-experts, amateurs and citizen scientists and eventually foreshadowing new roles for former mediators, such as investigative science journalism. Historically, discussion on science communication largely started in the post-war decades as the scrutiny of the quality of science journalism and popularization; one could provocatively ask whether contemporary discussion on science communication could foster a ‘scrutiny of the quality of science communication at large’, including that produced by the specialists. For scholars in our field, this also implies rethinking the very meaning of key terms such as ‘quality’ and ‘accuracy’. Accuracy of science communication was traditionally defined as adherence to the specialist message, but

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is that still the case? Was the BBC headline ‘accurately’ reporting on the fish-eating plastic study published by Science? We probably need a new notion of accuracy; we certainly need a broader notion of quality, encompassing not only accuracy but openness to scrutiny and dialogue, independence and fairness. The contemporary communication landscape clearly places new and greater responsibility on researchers and their institutions, who are increasingly active in communication to the ‘end user’ and not always prepared to deal with the dynamics and potential risks of such engagement. During the heated debate about vaccination that ensued in Italy in 2016, an immunologist who had heavily and generously committed to engage in discussion through his own Facebook page eventually decided to abruptly cancel all comments by claiming ‘Here only those who have studied can comment, not the common citizen. Science is not democratic’. Such communicative landscape also places much greater responsibility on the users of information and their selection and evaluation of content and its reliability. This poses an obvious question of competence. It also demands greater attention, by science communication studies, not only to the production of and access to content, but also to the diversity in its use. The circulation of information in social media, for example, serves a variety of ‘uses and gratifications’—to recall a classic concept in media theory6 —that range from information to entertainment, to the digital surrogate of bar chat. Much has been discussed how to limit the circulation of (even censoring) certain content. Very little discussion has been about how social media content is selected and evaluated on the basis of context and individual needs (such as ‘I want to relax for a few minutes or indulge in loose chat/gossip; I read and comment without much thought’, which is totally different from ‘I have to vaccinate my child, so I’ll ask my doctor for accurate information.’). Discussions of post-truth and the quality of science communication are often, more or less explicitly, coupled with speculations about substantially declining trust in science per se, mistrust in scientists and their expertise, and even anti-science attitudes. From empirical research, and with possible regional variations, that seems generally not the case.7

Science’s Cultural Authority: Trends and Changes Beyond speculations about an alleged generalized decline of trust in science, there is indeed an open—and largely neglected—question for our field. That is, to put it inevitably in general and sketchy terms, the theme of changes in science’s cultural authority and more broadly in the social status of science. By science’s cultural authority, I refer to the process that had already in 1906 attracted the attention of 6

See Katz et al. (1973). For Europe, see, for instance, Special Eurobarometer 401 on responsible research and innovation, science and technology, coordinated by the European Commission, https://ec.europa.eu/commfront office/publicopinion/archives/ebs/ebs_401_en.pdf.

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economist and sociologist Thorstein Veblen, leading him to notice that ‘On any large question which is to be disposed of for good and all the final appeal is by common consent taken to the scientist’; to define science’s role as ‘Quasi lignum vitae in Paradiso Dei, et quasi lucerna fulgoris in domo Domini’, like the tree of life in God’s paradise, and like a lamp of splendour in the house of the Lord; and eventually to ask: ‘How has this cult of science arisen?’ (Veblen 1906). We know from several historical, social and public perception studies that much has been changing in science, in society and at the intersection of the two.8 It is increasingly important for research on science in society to analyse which communicative processes may have contributed to changes in the cultural and social status of science. For instance, what is the impact of the long-standing and persisting emphasis on science as a producer of technology and welfare, as a toolbox whose input is investments and output is the solution of practical problems. This notion has dominated, during the past decades, the rhetoric of research policy and innovation in Europe (also by subsuming most of social and political discussion under the handy, policy-friendly label of ‘responsible research and innovation’). Could this have played a role in public and culturally defining science as a practical toolbox (or even as a supermarket!)— something that can then be challenged or even discarded when its answers/solutions do not match the needs, expectations and purposes (or even tastes) of relevant participants (Bucchi 2009; Bucchi and Trench 2014, 2016)? To a certain extent, this, rather than a plain anti-science frame, could help us interpret contemporary public debates like those on vaccination. And what is the long-term impact of the fashionable wave of pop formats for presenting science to the public: competitions among young scientists, Famelab, three-minute pitches and so on? Could this have contributed to shaping an image of science as ‘easy’ and quick to make as well as to understand that undermines all the uncertainty, the patience and hard labour and therefore encourages superficial, horizontal criticism by users, just like in travel or food users’ reviews (see, e.g., Scharrer et al. 2016)?

Democracy and the Discussion About Science in Society Finally, democracy is often implied in discussions about the quality of communication and public debate. Should anybody, regardless of their preparation, have a say on science communication? Or, as the Italian immunologist put it, only those who have studied can comment, because ‘science is not democratic’? This is probably a theme for political discussion at least as much as a theme for scholarly reflection. On the one hand, it would be easy to agree that science is not democratic. It would be silly to vote by majority on the validity of the laws of gravitation. Furthermore, we have clear historical evidence that the quality of 8

For an overview of these transformations, see Bucchi and Trench (2014).

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research performance is not necessarily linked to democratic regimes: classic examples include medical research in Nazi Germany and space research in the Soviet Union. In democratic societies, however, the discussion about science in society should certainly be democratic. As we know from a large body of literature in our field, that includes not only discussion of the potential implications of research applications, but also open and engaging discussion of the priorities of research funding and of the very aims and research agenda.9 It is quite an ambitious task, and one that largely remains unfulfilled in most societies and research policy contexts. But, again, it is an opportunity for research on science in society to display its relevance and contribute to an informed and democratic discussion. Massimiano Bucchi Università di Trento Trento, Italy [email protected]

Acknowledgments I am grateful to Susan Howard, Brian Trench and an anonymous reviewer for their helpful comments and suggestions. A different version of this chapter has been published as an editorial in Public Understanding of Science, 2017, 26(8):890–893, https://doi.org/10.1177/0963662517733368.

References Bauer M, Allum N and Miller S (2007) What can we learn from 25 years of PUS survey research? Liberating and expanding the agenda. Public Understand Sci 16:79–98. https://doi.org/10. 1177%2F0963662506071287 Bucchi M (2009) Beyond technocracy: citizens, politics, technoscience. Springer, New York Bucchi M, Neresini F (2002) Biotech remains unloved by the more informed. Nature 416:261. https://doi.org/10.1038/416261a Bucchi M, Neresini F (2004) Why are people hostile to biotechnologies? Science 304:1749. https:// doi.org/10.1126/science.1095861 Bucchi M, Trench B (eds) (2014) Handbook of public communication of science and technology, new edition. Routledge, London, New York Bucchi M, Trench B (2016) Science communication and science in society: a conceptual review in ten keywords. Tecnoscienza 7:151–168 Ioannidis PA (2005) Why most research findings are false. PLoS Med 2:e124. https://doi.org/10. 1371/journal.pmed.0020124

9

See examples: Wynne (1995); Bucchi and Neresini (2002, 2004); Bauer et al. (2007).

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Katz E, Blumler JG, Gurevitch M (1973) Uses and gratifications research. Public Opini Q 37:509– 523. https://doi.org/10.1086/268109 Scharrer L, Rupieper Y, Stadtler M (2016) When science becomes too easy: science popularization inclines laypeople to underrate their dependence on experts. Public Understand Sci 26:1003– 1018. https://doi.org/10.1177/0963662516680311 Schneider L (2017) Fishy peer review at Science by citizen scientist Ted Held. For better science. http://www.forbetterscience.com Steen RG, Casadevall A, Fang F (2013) Why has the number of scientific retractions increased? PLoS One 8:e68397. https://doi.org/10.1371/journal.pone.0068397 Veblen T (1906) The place of science in modern civilization. American J Soc 11:585–609 Wynne B (1995) Public understanding of science. In: Jasanoff S, Markle GE, Petersen JE, Pinch T. STS handbook. Sage Knowledge. https://doi.org/10.4135/9781412990127.n17

Contents

Part I 1

Science Communication at the Crossroad

Communicating Science: Heterogeneous, Multiform and Polysemic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bernard Schiele, Toss Gascoigne, and Alexandre Schiele

2

Citizen Science as Participatory Science Communication . . . . . . . . . Per Hetland

3

Science Communication on Offer by Research Institutes in Eight Countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Marta Entradas

4

5

Attempts to Categorize and Evaluate Science Festivals, a 30-Year-Old Science Communication Event: The Case of Greece . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Elpiniki Pappa and Dimitrios Koliopoulos Emerging Practices in Science Communication in Canada . . . . . . . . Michelle Riedlinger, Alexandre Schiele, and Germana Barata

Part II

3 47

63

77 91

Science–Society Dynamics

6

Meeting the Needs of Society: Experiences from Practices at the Science–Society Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 Anne M. Dijkstra

7

Science Communication in Nigeria and South Africa: Beliefs, Social Groups and the Social Space of Science . . . . . . . . . . . . . . . . . . . 125 Bankole Adebayo Falade and Refilwe Mary-Jane Ramohlale

8

The Cultural Distance Model: Empirical Evidence from India . . . . . 151 Gauhar Raza and Surjit Singh

9

Science Culture: A Critical and International Outlook . . . . . . . . . . . . 165 Michel Claessens xxxiii

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Contents

Part III Public Attitudes 10 Cultural Differences in Media Framing of AI . . . . . . . . . . . . . . . . . . . . 185 Ahmet Suerdem and Serhat Akkilic 11 Segmentation Disparities in Scientific Experts’ Knowledge of and Attitudes Towards GMOs in China . . . . . . . . . . . . . . . . . . . . . . . 209 Jianbin Jin, Xiaoxiao Cheng, and Zhaohui Li 12 Responsible Research and Innovation in China and the Risks in Innovation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 Yandong Zhao and Miao Liao 13 Exploring Emerging Public Attitudes Towards Autonomous Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253 Chris Tennant Part IV Professions and Institutions 14 The Evolution of Scientific, Technical and Industrial Culture in France . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269 Samuel Cordier 15 Emerging Practices Based on New Media in the Chinese Science Popularization Industry: Transformation in the New Era of Science Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 277 Fujun Ren, Xuan Liu, and Jianquan Ma 16 Science Communication in the New Era: Skills Education at Science and Technology Museums . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299 Xiang Li, Xuan Liu, and Peng Ren 17 Science Museums: The Brazilian Case . . . . . . . . . . . . . . . . . . . . . . . . . . 311 Luisa Massarani and Jessica Norberto Rocha Science Cultures in a Diverse World Knowing, Sharing, Caring . . . . . . . . 325

Editors and Contributors

About the Editors Bernard Schiele is a Professor of Communications in the Faculty of Communication at the University of Quebec at Montreal (Canada). At present, he is the co-editorin-chief, with Ren Fujun (NAIS), of the new journal Cultures of Science. He is also a founding and current member of the Scientific Committee of the PCST network. He chaired the International Scientific Advisory Committee for the New China Science and Technology Museum (2006–2009). He was a member of the Expert Panel on the State of Canada’s Science Culture (2013–2014), which published Science culture: where Canada stands (Council of Canadian Academies, 2014). Among other books, he has recently published as a co-editor are Musées, Mutations [Museums, Mutations] (OCIM, 2019) and, with Toss Gascoigne and other scholars, Communicating science: a global perspective (ANU Press, 2020). He is the recipient of the ICOM– Canada International Achievement Award (2012). Xuan Liu is an Associate Research Fellow of the National Academy of Innovation Strategy, China Association for Science and Technology (CAST). She has received a Ph.D. degree from the University of Science and Technology of China. During her Ph.D. study, she was also a visiting Ph.D. student in the London School of Economics and Political Science (LSE). She has presided as project head or participated in more than 30 international cooperation projects, national research projects and ministeriallevel and provincial work. She has published more than 40 journal papers, conference papers and research reports in both English and Chinese as the first or corresponding author. From 2014 to 2018, she served as a member of the Scientific Committee of Public Communication of Science and Technology (PCST) and been invited to be keynote speaker at important international academic conferences. Her main research interests are the culture of science, public engagement with science, the innovation environment and ecology. Martin W. Bauer read Psychology and Economic History (Bern, Zurich, London) and is Professor of Social Psychology and Research Methodology, London School of xxxv

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Editors and Contributors

Economics and Political Science (LSE). A former editor-in-chief of Public Understanding of Science(2009–2016), he investigates ‘common sense’ in a comparative perspective and particularly in relation to science and emerging technologies. His international project-network, MACAS, mapping the cultural authority of science, conducts and analyses attitude surveys, mass media mappings and qualitative enquiries on controversial technosciences. His recent book publications include The Psychology of social influence: modes and modalities of shifting common sense, Cambridge University Press, 2021; The cultural authority of science: comparing across Europe, Asia, Africa and the Americas, London, Routledge Studies of Science, Technology and Society, London, 2019; Atoms, bytes and genes: public resistance and technoscientific responses, Routledge, New York, 2015.

Contributors Serhat Akkilic Istanbul Bilgi University, Istanbul, Turkey Germana Barata Schol-CommLab At Simon Fraser University, Vancouver, Canada; Laboratory of Advanced Studies in Journalism (Labjor), State University of Campinas, São Paulo, Brazil Xiaoxiao Cheng School of Journalism and Communication, Tsinghua University, Beijing, China Michel Claessens European Commission and Free University of Brussels, Brussels, Belgium Samuel Cordier Heritage curator, Director of the zoological museum of Strasbourg, Strasbourg, France Anne M. Dijkstra Science Communication, University of Twente, Enschede, The Netherlands Marta Entradas ISCTE-IUL, Instituto Universitário de Lisboa, Lisbon, Portugal Bankole Adebayo Falade Centre for Research On Evaluation, Science and Technology (CREST), Stellenbosch University, Stellenbosch, South Africa; Department of Psychological and Behavioural Sciences, London School of Economics and Political Science, London, UK Toss Gascoigne Centre for Public Awareness of Science, Australian National University, Canberra, Australia Per Hetland Department of Education, University of Oslo, Oslo, Norway Jianbin Jin School of Journalism and Communication, Tsinghua University, Beijing, China

Editors and Contributors

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Dimitrios Koliopoulos Department of Educational Sciences and Early Childhood Education, University of Patras, Patras, Greece Miao Liao Changsha University of Science and Technology, Changsha, China Xiang Li National Academy of Innovation Strategy, Beijing, China Zhaohui Li National Communication Center for Science and Technology, China Association for Science and Technology, Beijing, China Xuan Liu National Academy of Innovation Strategy, Beijing, China Jianquan Ma National Academy of Innovation Strategy, Beijing, China Luisa Massarani National Brazilian Institute of Public Communication of Science and Technology and Master of Communication of Science, Technology and Health, Casa de Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil Elpiniki Pappa Department of Educational Sciences and Early Childhood Education, University of Patras, Patras, Greece Refilwe Mary-Jane Ramohlale Science Education Centre, School of Physical and Mineral Sciences, Faculty of Science and Agriculture, University of Limpopo, Limpopo, South Africa Gauhar Raza Council of Scientific and Industrial Research (CSIR), New Delhi, India Fujun Ren National Academy of Innovation Strategy, Beijing, China Peng Ren Beijing Yimu Animation Technology Co, Beijing, China Michelle Riedlinger School of Communication and the Digital Media Research Centre, Queensland University of Technology, Brisbane, QLD, Australia; Schol-CommLab At Simon Fraser University, Vancouver, Canada Jessica Norberto Rocha Cecierj Foundation, Rio de Janeiro, Brazil Alexandre Schiele Hebrew University of Jerusalem, Jerusalem, Israel Bernard Schiele University of Québec At Montréal, Montreal, QC, Canada Surjit Singh Department of Zoology, Indira Gandhi University, New Delhi, India Ahmet Suerdem Istanbul Bilgi University, Istanbul, Turkey Chris Tennant Department of Psychological and Behavioural Science, London School of Economics and Political Science, London, UK Yandong Zhao Department of Sociology, Renmin University of China, Beijing, China

Acronyms and Abbreviations

AAAS ACS AI ASF AV CAST CNKI CNNIC CNS COPUS CPC CS CSR CV DST EU GBIF GM GMO IoT MDS MIT NAIS NBIC NGO NHRF NIMBY OECD PAS PE PSC PUS

American Association for the Advancement of Science Association des Comunicateurs Scientifiques du Québec Artificial intelligence Athens Science Festival Autonomous vehicle China Association for Science and Technology China National Knowledge Infrastructure China Internet Network Information Center Cell, Nature and Science Committee for the Public Understanding of Science (UK) Communist Party of China Citizen Science Corporate social responsibility Coherence value Department of Science and Technology (South Africa) European Union Global Biodiversity Information Facility Genetically modified, genetic modification Genetically modified organism Internet of Things Multidimensional scaling Massachusetts Institute of Technology National Academy of Innovation Strategy (China) Norwegian Biodiversity Information Centre Non-government organization National Hellenic Research Foundation Not In My Back Yard Organisation for Economic Co-operation and Development Public Awareness of Science Public engagement Participatory Science Communication Public Understanding of Science xxxix

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R&D RRI S&T SAIAB SC SciCo S-H-A SL SO system SP STEM SWCC UK UN UNESCO US WCI

Acronyms and Abbreviations

Research and Development Responsible Research and Innovation Science and technology, scientific and technological South African Institute for Aquatic Biology Science culture Science communication Social science, humanities and arts Scientific literacy Species Observation system Science popularization Science, technology, engineering, mathematics Science Writers and Communicators of Canada United Kingdom United Nations United Nations Educational, Scientific and Cultural Organization United States WeChat Communication Index

List of Figures

Fig. 3.1 Fig. 3.2 Fig. 3.3 Fig. 3.4 Fig. 4.1

Fig. 5.1 Fig. 7.1 Fig. 7.2 Fig. 9.1 Fig. 9.2

Fig. 10.1 Fig. 10.2 Fig. 10.3 Fig. 10.4 Fig. 11.1 Fig. 11.2 Fig. 11.3 Fig. 12.1

Institutional public events, by country . . . . . . . . . . . . . . . . . . . . . . Traditional media channels, by country . . . . . . . . . . . . . . . . . . . . . Frequency of social media channel use, by country . . . . . . . . . . . Public events and traditional media use, by country (n = 2030) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Overview of science festival activities related to their degree of formality (x-axis) and their target audiences (y-axis) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A demographic comparison of social media communicators of science and other science communicators in Quebec . . . . . . . . Bi-plot of concatenated table for Nigeria . . . . . . . . . . . . . . . . . . . Bi-plot of concatenated table for South Africa . . . . . . . . . . . . . . . Actions aiming to promote science culture cover a large variety of target publics, methods and objectives . . . . . . . . . . . . . Improvement in the percentage of correct answers to the Eurobarometer scientific quiz in 12 European countries, 1992–2005 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Number of news items, according to topic dominance . . . . . . . . . Document clusters, by topics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Topics, by country . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . a INDSCAL mapping of the topic space. b INDSCAL mapping of the country space . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Estimated marginal means of factual knowledge about GMOs among expert segments . . . . . . . . . . . . . . . . . . . . . . Estimated marginal means of subjective knowledge about GMOs among expert segments . . . . . . . . . . . . . . . . . . . . . . Estimated marginal means of attitudes towards GMOs among expert segments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Changing public attitudes towards the idea that ‘scientists shall be responsible for the bad things committed by other people with their inventions’ Source STPISTW (2009, 2011) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

68 68 68 70

85 101 139 140 169

176 199 199 200 202 221 222 222

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Fig. 13.1 Fig. 15.1

Fig. 15.2

Fig. 17.1

List of Figures

A scenario used in our survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . Main channels for the Chinese people to access scientific and technological information. Source China citizens’ scientific literacy report IV, China Science and Technology Press, 2018 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Channels used by the Chinese people to access scientific and technological information from the internet and level of trust in the scientific and technological information communicated through online channels. Source China citizens’ scientific literacy report IV, China Science and Technology Press, 2018 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Percentages of interviewees who reported visiting a science or cultural communication space or participating at an S&T event in 2006, 2010, 2015 and 2019. Source CGEE (2019:15) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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List of Tables

Table 1.1 Table 1.2 Table 1.3 Table 1.4 Table 1.5 Table 1.6 Table 1.7 Table 1.8 Table 2.1 Table 3.1 Table 3.2 Table 3.3 Table 4.1 Table 5.1

Table 7.1 Table 7.2 Table 7.3 Table 7.4 Table 7.5 Table 7.6 Table 7.7

List of studied countries and regions . . . . . . . . . . . . . . . . . . . . . List of categories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Occurrences, by categories and countries, in descending order . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Least mentioned, moderately mentioned and most mentioned denominations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Order of categories, by occurrence of the terms or lack thereof . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Maximum number of occurrences for a given country, in decreasing order . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Occurrences, by countries in alphabetical order, and categories, in descending order . . . . . . . . . . . . . . . . . . . . . . Order of categories, by occurrence of terms, by countries . . . . Participatory science communication: access, interaction, and participation . . . . . . . . . . . . . . . . . . . . . . . . . . . Analysis of variance, by country . . . . . . . . . . . . . . . . . . . . . . . . Audiences addressed by research institutes, by country . . . . . . Rationales for communicating with the public, by country . . . Categorization of examples of Greek science festivals . . . . . . . A comparison for values derived from a thematic analysis of the question, ‘What makes good science writing and/or science communication?’ . . . . . . . . . . . . . . . . . . Population indices for Nigeria and South Africa . . . . . . . . . . . . Manifest variables used in the analysis . . . . . . . . . . . . . . . . . . . Three-factor solutions for the aggregation of attitude variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Correlations between variables for South Africa . . . . . . . . . . . . Correlations between variables for Nigeria . . . . . . . . . . . . . . . . Abbreviations used in the analysis . . . . . . . . . . . . . . . . . . . . . . . Nigeria concatenated table and correspondence analysis output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

10 11 12 17 18 22 35 38 52 70 71 72 81

105 128 135 137 138 139 143 144 xliii

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Table 7.8 Table 9.1 Table 9.2 Table 9.3 Table 10.1 Table 10.2 Table 11.1 Table 11.2

Table 11.3 Table 11.4 Table 13.1 Table 13.2 Table 13.3 Table 13.4 Table 15.1 Table 15.2 Table 15.3 Table 15.4 Table 15.5 Table 15.6 Table 15.7 Table 15.8

List of Tables

South Africa concatenated table and correspondence analysis output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A brief history of activities aimed at developing science culture in Europe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Questions on science and technology included in Eurobarometer no. 224 (2005) . . . . . . . . . . . . . . . . . . . . . . . . National and international surveys of public knowledge of science . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Source counts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Topics, keywords and excerpts . . . . . . . . . . . . . . . . . . . . . . . . . . GMO knowledge of segments defined by disciplinary field, education level, and occupation . . . . . . . . . . . . . . . . . . . . Between-subjects effects of disciplinary field, education level and occupation on the knowledge–attitude relationship . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Correlations between knowledge of and attitude towards GMOs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The impact of GMO knowledge on attitude towards GMO mediated by perceived benefit and perceived risk . . . . . . . . . . . Comfort with the prospect of autonomous vehicles, 13 European countries, 2015 (n = 9,012) . . . . . . . . . . . . . . . . . . . . Comfort with the prospect of autonomous vehicles, series of surveys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Reasons for comfort with the prospect of autonomous vehicles, US survey, 2017 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Technological optimism scale questions, US survey 2017 . . . . Changes in the number of Chinese internet users and the internet penetration rate in recent years . . . . . . . . . . . . The number of SP websites built with government funding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . SP website ranking of China Science Communication and GuoKe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . SP weibo information for China Science Communication and GuoKe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . SP weibos posted by China Science Communication and GuoKe, 1–7 December 2020 . . . . . . . . . . . . . . . . . . . . . . . . SP weibo effect of China Science Communication and GuoKe, 1 to 7 December 2020 . . . . . . . . . . . . . . . . . . . . . . SP WeChat effect of China Science Communication and GuoKe, 13–19 February 2021 . . . . . . . . . . . . . . . . . . . . . . . Weibo account information with different labels . . . . . . . . . . . .

146 170 175 178 193 195 219

224 225 226 256 257 258 260 283 285 288 290 291 292 293 294

Part I

Science Communication at the Crossroad

Chapter 1

Communicating Science: Heterogeneous, Multiform and Polysemic Bernard Schiele, Toss Gascoigne, and Alexandre Schiele

Abstract That science communication applies to both a field of practices and a field of research on those practices seems obvious enough. The very title of the 2020 book, Communicating science. A global perspective—part of an attempt to provide an overview of the way modern science communication has developed over the past 40 or so years, in 39 different countries or regions, reinforced by instructions to the prospective authors—framed the project around ‘science communication’, naturalizing it, encouraging its homogenization and reinforcing it through the peer-review and editing processes (It is worth noting that such a survey was conducted and published on the occasion of the 1994 PCST Conference in Montreal. See Schiele (When science becomes culture, University of Ottawa Press, Ottawa, 1994). But the draft chapters showed that ‘science communication’ is not a universal term. It has many definitions, and from the second half of the twentieth century researchers and practitioners have described it variously as an objective, a goal, a process, a result and an outcome. In this chapter, we have sought to list every term used by the authors and evaluate their degree of penetration of the field, understood as the frequency of their occurrence and as the number of authors using them. Close examination showed that 16 different words or phrases were used in the book for what we called ‘science communication’. Some were confined to a single country, others were applied across a number of countries. Only five authors defined the terms they used, but most did not, probably considering that their meaning was self-evident. This chapter lists and categorizes those terms, grouping them into three categories : ➀ most mentioned,

B. Schiele (B) University of Québec At Montréal, Montreal, QC, Canada e-mail: [email protected] T. Gascoigne Centre for Public Awareness of Science, Australian National University, Canberra, Australia e-mail: [email protected] A. Schiele Hebrew University of Jerusalem, Jerusalem, Israel e-mail: [email protected] © China Science and Technology Press 2021 B. Schiele et al. (eds.), Science Cultures in a Diverse World: Knowing, Sharing, Caring, https://doi.org/10.1007/978-981-16-5379-7_1

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➁ moderately mentioned and ➂ least mentioned. Authors tended to use the terminology interchangeably, even though most terms are context specific and tributary to national political, social and cultural trends. Keywords Science communication · Public communication of science and technology · Public engagement · Participation · Public understanding of science · Science literacy · Scientific culture · Scientific temper · Vulgarization · Democratization

1.1 Foreword The importance of a science culture1 accessible to and shared by all, in a world now shaped by technoscience, has long been self-evident. However, numerous actors regularly stress its necessity and call for the improvement of the general level of competency. As early as 1934, John Dewey observed that the reach of science (the word ‘technoscience’ did not yet exist) extended beyond material culture, and held that the acquisition of scientific attitudes was the aim of any training—education’s ‘supreme intellectual obligation’.2 Since the end of World War II, actions in many countries by people such as Warren Weaver in 1951 in the United States, François Le Lionnais in 1958 in France and Charles Percy Snow in 1959 in England clearly aimed to raise awareness. Researchers, teachers, volunteers and associations have propagated the scientific ethos and shared their passion with the public; and the media (newspapers, radio and television) closely followed suit by including science in their programming.3 Coinciding with this push, other researchers at the turn of the 1960s turned their attention to the processes and effects of the diffusion, propagation and penetration of science within society, making it their object of research and contributing to the 1

Following Plato, science culture can be defined as an opinion justified by reason and its confrontation with reality. In a debate, arguments supported by proofs are advanced, and the demonstration of the proofs is the mark of the scientific spirit. Science culture is, on the one hand, a substrate of basic notions and, on the other, hypothetico-deductive reasoning; that is, we are able to use schemes in a reasoning process that aims to identify the causal explanations of various phenomena. A scheme, according to Piaget, describes what in an action is transposable, generalizable or differentiable from situation to situation (that is, what is common in the various repetitions of the same action), and hypothetico-deductive reasoning is the capacity to deduce conclusions from pure hypotheses or observations. 2 Although the atomic bombings in 1945 were a turning point, the uses of chemistry and physics during World War I had similar effects. John Dewey also referred to those effects when he wrote: ‘It has become a common place to refer to consequences of chemistry in its application to warfare. High explosives, with their allies of steel and airplane derived from physics, are capable of destroying every city on the face of earth, and we are even threatened with bacterial warfare’ (Dewey 1934: 2). 3 We will limit ourselves to pointing out the new wave of public diffusion of science in the wake of World War II, without forgetting the very significant ‘vulgarization’ or ‘popularization’ movement of the 19th and early twentieth century, which some have called a ‘Golden Age’ (see Raichvarg and Jacques 1991).

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emergence of a new research field. For the past 30 years, researchers have questioned the status of their field, hereafter referred to as ‘science communication’ (SciCom). A related question is: should we consider SciCom as a field, or has it become a discipline in its own right?

1.2 The Structure of the Field 1.2.1 Yesterday: A Heterogeneous and Multiform Research Field Thirty years ago, Jacobi and Schiele (1990) proposed an assessment of scientific vulgarization (the expression ‘SciCom’ was not in use then) in which they concluded that ‘various practices of diffusion’ of science and technical culture were differently termed by researchers and practitioners. Examples of varying terminologies include ‘public science communication’ (Pierre Fayard 1988); ‘parallel school’ (Rovan 1973; Girard 1979; Schaeffer 1986); ‘science sociodiffusion’, ‘science divulgation’ (Guédon 1980, 1981); and ‘science popularization’ (Jacobi 1983). Today, those terms are rarely used, except for ‘public science communication’, which provides the PCST Network with its title. The network was founded in 1989, and its biennial conferences bring together researchers and practitioners in the field, which today is referred to as science communication.4 Jacobi and Schiele (1990) opted to use the term ‘scientific vulgarization’ because in French it set the diffusion of science as applying only outside of the scientific community and outside formal education. That definition respected the two conditions laid down by François Le Lionnais in 1958: an ‘explanatory and diffusion activity’ taking place ‘outside of official and other similar formal schoolings’ and which aimed neither ‘to train nor provide advanced training for specialists’ (Le Lionnais 1959: 7). It is useful to add that this vision endured over the years, regardless of its many reformulations. We can therefore consider it the ur-definition of what would come to be known as the ‘deficit model’ (Schiele 2008). The deficit model

4

The first conference was organized in 1989 by Pierre Fayard and took place at the Futuroscope in Poitiers, France. The Futuroscope, conceptualized in 1983 by Roger Monory, president of the Vienne Department in France, and opened in 1987, originally aimed to be an observatory of the future (it has since then become a science and futurology theme park). For Pierre Fayard, then professor at the University of Poitiers, the Futuroscope, with its window on the potential of information and communication technologies, was the place to hold this first conference on ‘public science communication’. The Poitiers conference was followed by conferences in Madrid (1991, also organized by Pierre Fayard) and in Montreal (1994, by Bernard Schiele). From Melbourne (1996, by Toss Gascoigne and Jenni Metcalfe) on, the informal PCST network became increasingly institutionalized and has become a full-blown international organization that organizes a conference every two years.

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has today been recast as ‘transmission activity’, in which the object is to communicate information to the public.5 This is why, according to Jacobi and Schiele, ‘this qualification of vulgarization for a wide range of practices is not simplistic since it acknowledges a diversity of practices which, in any regard, resists simplification of any sort’ (Jacobi and Schiele 1990: 81, passim). The theoretical construction of the object—scientific vulgarization—was, according to Jacobi and Schiele, just as complex, because the issues and models used were closely interconnected. And, for that reason, ‘the researcher who takes this activity as a research object cannot gloss over these perspectives nor over their structuring effect upon his own approach.’ In other words, ‘the theoretical construction of the research object is therefore dependent upon its conditions of production, with the study of scientific vulgarization committing as much the researcher as the social actor’ (Jacobi and Schiele 1990: 81, passim). From their assessment conducted in the late 1980s, Jacobi and Schiele drew two major conclusions: first, that scientific vulgarization ‘met a social demand that was not only widespread but emanated from distinct institutional loci’; and second, that the research on scientific vulgarization did not take place in a ‘homogenous framework’; that is, ‘there was no theory of vulgarization per se’ (Jacobi and Schiele 1990: 82, passim).

1.2.2 Today: Still a Heterogeneous and Multiform Research Field Both the area of practices and the field of research remain heterogeneous, and that conclusion has been confirmed repeatedly over the past 30 years. In their 2008 survey, Mulder et al. concluded that four great domains—‘four pillars of science communication’ (2008: 280)—exercise a decisive influence upon research and training programmes: ‘natural sciences, educational studies, social studies of science and communication studies’ (2008: 280, passim). They stress that each pillar is ‘mostly interdisciplinary and built on even older disciplines’ (2008: 280). Bell (2010) reached the same conclusion: ‘all I can do is reiterate my general point. Science communication is less a community of researchers, but more space where communities coexist and the work of a science communication worker (be they academic, practitioner or

5

The definition was proposed by François Le Lionnais at the meeting debate of the Association des écrivains scientifiques de France (Science Writers Association of France) held at the Palais de la Découverte in Paris on 26 February 1958: ‘any explanatory or diffusion activity of scientific and technical knowledge, culture and thought, but under two conditions, two limitations. The first, that these explanations and diffusion of scientific and technical thought must take place outside [formal] education … Second condition, that these extracurricular explanations be not aimed at the training or advanced training of specialists in their own field, because we aim to complete the culture of specialists outside of their field’ (Le Lionnais 1959: 7).

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bit of both) is one of constant negotiation’, adding, ‘That is problematic, but unavoidable.’ More recently, Dijkstra et al. (2020), talking of potential science communication actors, concluded that: ‘A great diversity of participants may be involved in the process of science communication including scientists, policy-makers, activists, ordinary citizens, and other groups. The science communication process is dynamic, constantly changing, and driven by a variety of interpretations, views of science, and communication goals.’ Just as Jacobi and Schiele had opted for a generic definition of ‘vulgarization’, Dijkstra et al., after acknowledging that the expression ‘science communication’ is ‘widely used and interpreted in various ways’, opted for a ‘working definition’.6 Their definitions conform to their respective zeitgeists: whereas the latter stress public engagement, the former stress the public diffusion and circulation of scientific information. To extend the list of all those who observed that the field, at the levels of both practices and research, was structurally heterogeneous would only prove redundant. We can therefore assert that ‘science communication’ as a research field exists at the point of intersection and interaction of actors, discourses and practices, and this is the fundamental structure of the SciCom research field: heterogeneous, and characterized by a diversity of hybrid and multiform research activities. As Guenther and Joubert (2017: 1) put it: ‘science communication is a dynamic, interdisciplinary field of research that draws from a wide range of disciplines and encompasses a wide spectrum of scientific approaches.’

1.3 The Different Terms for ‘Science Communication’ and Their Meanings What is the situation today? ‘Vulgarization’ has fallen into disuse, being successively supplanted by ‘scientific literacy’ (SL) ‘public awareness of science’ (PAS) ‘public understanding of science’ (PUS) ‘science culture’ (SC) and, more recently, by ‘public engagement’ (PE) (see Stilgoe et al. 2014) and ‘citizen science’ (CS) (see Delfanti 2010;7 Lewenstein 2016; Hecker et al. 2018). While the expression ‘science communication’ (SciCom) now seems to dominate the literature, it nonetheless coexists with those other terms. 6

The working definition proposed by Dijkstra et al. echoes the one proposed by the UK National Coordinating Centre for Public Engagement (2019: 3): ‘Science communication describes the many ways in which the process, outcomes, and implications of the sciences—broadly defined—can be shared or discussed with audiences. Science communication involves interactions, with goals of interpreting scientific or technical developments or discussing issues with a scientific or technical dimension.’ To truly illustrate the fleeting and ephemeral nature of definitions in this area, that definition disappeared from the UK National Coordinating Centre for Public Engagement website in 2020. 7 Lewenstein (2016) compiled a number of variants to illustrate the scope of the practice: ‘“peer to peer” science, participatory science, community science, community-based research, public participation in research, crowdsourced science, and so on.’

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1.3.1 A Tangle of Terms The making of the book Communicating science. A global perspective8 on the initiative of Toss Gascoigne was an opportunity to conduct a content analysis of the terms used in 39 countries to designate and qualify both the practices themselves and the theoretical objects constructed to make sense of them.9 The book aims to provide an overall view of the state of SciCom and of its main development stages, actors, institutional forms and so on in each country. The call for contributions specified the aim of the project and the information to provide in each chapter to allow comparisons between countries (see Schiele and Gascoigne 2020). For example, authors were expected to discuss the media coverage of science, the associations and organizations dedicated to the promotion and diffusion of science, the main government initiatives, the role of universities, public attitudes and so on. More specifically, they were asked to nominate the terms used to refer to ‘science communication’ in their country (see Box 1.1). Box 1.1 Extracts from the call for contributions We want a book chapter of 5000–7000 words documenting the emergence of modern science communication in your country. It will record major events, debates, activities and people in science communication over about the last 60 years. … A summary of where your country stood at the beginning of the emergence of modern science communication. This will be somewhere between 1945 and 1970, and the aim is to set the context. … focus on the ‘firsts’ and subsequent developments … What terminology was used for ‘science communication’, and did it change over the years? Science, technology and society Public understanding of science Scientific temper Social appropriation of S&T Dissemination of science Vulgarization Popularization of science …

8

The book can be found at https://press.anu.edu.au/publications/communicating-science. The book contains 40 chapters. Two are introductory chapters, and one focuses not on a country but a topic: health communication in a number of African countries. Those three chapters are not included in the current analysis. The remaining 37 chapters deal with single countries, except for the Scandinavian chapter, which deals with three countries. This analysis therefore covers 39 separate countries.

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9

The chapters went through an iterative process of editing, but the material used for this analysis (the ‘corpus’) consists of the first version submitted by the 37 groups of authors. The analysis therefore focuses on the original versions, before evaluation, peer review and copyediting. We opted for the original version before any suggestion for redrafting by reviewers and copyeditors, since they may have significantly affected the published version—a process akin to a ‘conversion’ for Knorr-Cetina (1981: 152). There will therefore be differences between the corpus and the published chapters, but this is intentional. In our view, the original contributions were the most accurate representation of the lexicon of each author. As an aside: ‘contribution’ and ‘text’ are used interchangeably to refer to the content of the corpus, while ‘chapter’ refers to the published version. In the same spirit, we use ‘author’ in the singular, regardless of the number of authors of each contribution, because what we are interested in is auctorialité—the author as function and not as a historically situated person.10 Furthermore, we occasionally use the word ‘country’ or even directly name the country in question as shorthand for ‘the author of the contribution on this particular country’. Finally, when we quote directly from contributions, we refer to the published version. The analysis covered all 39 countries or regions and accomplished a systematic survey of every occurrence of each term used by the authors for what we broadly term ‘science communication’ (see Table 1.1). Each country region was separately coded, with the exception of the Nordic countries—Denmark, Norway and Sweden—which were covered in a single contribution on account of their similarities. This is why the corpus comprises 39 countries or regions but only 37 contributions. The coding units are the occurrences and variations of terms; similar terms were grouped together but distinct variations were given their own distinct categories. Thus, ‘science literacy’ and ‘scientific literacy’ are a minor variation of the same term and were both recorded in the category ‘science literacy’ (SL). A total of 16 categories were identified. Table 1.2 lists the categories. It must be stressed that the categories were not fixed before the analysis, but rather derived by aggregation; that is, the analysis of the first text made it possible to identify a first list of terms; the analysis of the second added new terms, leading to the re-analysis of the first text. This iterative procedure was followed for every text of the corpus, which made it possible to identify every term and every formulation of those terms. This methodology might take longer, but it is systematic and exhaustive. And, to ensure reliability, the texts were coded twice. It goes without saying that this analysis was limited by each author’s viewpoint, interpretation of instructions, national specificities and writing style. Nevertheless, those differences do not significantly affect the data, since the only categories are the occurrences of terms. Furthermore, this approach is first and foremost exploratory, and we welcome any critique, commentary or suggestions. Table 1.3 presents the data. There is one row for each country, from 1 to 37, from CN (China) to JM (Jamaica; see Table 1.1 for a list of country abbreviations). Countries are listed in descending order, ranked by the number of times they used

10

See Foucault (1994: 789–821).

10

B. Schiele et al.

Table 1.1 List of studied countries and regions Country or region

Code

Country or region

Codea

Aotearoa New Zealand

NZ

Malaysia

MY

Argentina

AR

Mexico

MX

Australia

AU

Netherlands

NL

Brazil

BR

Nigeria

NG

Canada

CA

Pakistan

PK

China

CN

Philippines

PH

Colombia

CO

Portugal

PT

Estonia

EE

Russia

RU

France

FR

Scandinavia

SC

Germany

DE

Singapore

SG

Ghana

GH

South Africa

ZA

India

IN

Spain

ES

Iran

IR

Taiwan, China

TW

Ireland

IE

Thailand

TH

Israel

IL

Turkey

TR

Italy

IT

Uganda

UG

Jamaica

JM

United Kingdom

GB

Japan

JP

United States

US

Korea

KR

Note The list includes only 37 countries or regions, since the contribution on Scandinavia (SC) covers Denmark, Norway and Sweden a Code: Country and region

any term for ‘science communication’. China topped the list with 177, and Jamaica was lowest with 25. Those numbers are listed in the second last column. We identified 16 categories of terms for ‘science communication’ (see Table 1.2), and they are listed along the top of the table. The categories are listed from the most frequently used term (‘SciC’, science communication, 1,685 mentions) to the least frequently used (‘SM’, science mediation, 7 mentions). The total from each category is in row 38 (see Table 1.3). Some numbers are highlighted in grey, showing the maximum number of occurrences in each category. For example, China (CN) makes the greatest use of both ‘SP’ (science popularization, 123 occurrences) and ‘SL’ (science literacy, 13 occurrences). (Another version of Table 1.7, with the countries listed alphabetically, is in the appendix; see Table 1.6). The content analysis identified 3,076 occurrences. ‘Science communication’ (SciC) occurred 1,685 times, or 54.8% of the total, and that term was present in all contributions. However, the authors did not all afford the term the same weight (median value: 47). We stress that the instructions to the authors had imposed ‘science

1 Communicating Science: Heterogeneous, Multiform and Polysemic

11

Table 1.2 List of categories Code

Category

DS

Democratization of science, social appropriation

EM

Empowerment

PA

Awareness, public awareness (of the importance of S&T), raising awareness

PC

Public communication of science

PCST

Public communication of science and technology

PE

Public engagement (PE), public engagement in science and technology (PEST), inclusivity, citizen engagement, engagement with science, critical engagement with science, involvement, engagement model, engagement-oriented approach, engagement-oriented programme, science engagement, mode of engagement, citizen science

PT

Participation, public participation, community participation, participation in science, participatory activities, participative, citizen participation

PUS

Public understanding of science (PUS), public understanding of science and technology (PUST)

SC

Scientific culture, scientific and technological culture, culture of science

SciC

Science communication

SI

Science information, scientific information, level of information, health or medical information

SL

Science literacy, scientific literacy

SM

Mediation, scientific mediation

SP

Science popularization

ST

Scientific temper

VS

Vulgarization

communication’ as the default term of the contribution to be submitted (see Box 1.2): of the 827 words in the instructions, 49 were ‘science’ while the compounds ‘science communication’ / ‘communicator(s) / ‘journalist(s)’ appeared 19 times. It can therefore be argued that ‘science communication’ became the term by default when the authors discussed practice or theory without referring to a specific situation or theoretical standpoint. Bergeron, who used the term 21 times in the contribution on France, confirms it when she writes: ‘for a matter of homogeneity, I strove to use the expression ‘science communication’ as a generic name for our topic’ (Bergeron 2020: 309). In short, it appeared that the term ‘SciC’ acted as hypernym in the discourses of the authors.

74

55

ZA

US

8

9

10 IL

52

76

55

21

39

36

17 IR

18 AR

19 IT

20 KR

45

14 NZ

16 EE

42

13 IE

15 RU

63

49

11 NL

12 PT

22

34

68

TH

IN

76

6

JP

5

59

78

62

24

SciC

7

DE

CA

MX

2

4

CN

1

3

Code

R

21

5

30

6

0

14

0

0

0

0

3

0

0

10

10

0

1

2

7

5

1

2

3

10

29

23

1

4

13

0

4

2

1

1

5

1

1

2

1

1

0

3

60

3

0

0

1

0

0

1

1

4

1

1

3

5

1

0

0

0

5

9

15

3

1

1

0

23

1

0

PA

77

PC

5

9

11

1

5

1

5

123

8

PE

SP

0

13

12

2

0

0

1

3

19

0

6

0

2

3

1

0

2

2

3

2

0

2

3

7

3

0

1

3

0

1

1

1

5

0

4

11 2

3

0

7

1

17

3

5

0

1

PUS

1

2

2

1

0

1

0

10

1

2

6

PT

20

11

0

SC

4

2

5

4

0

1

0

4

4

0

1

1

1

4

2

1

8

0

1

13

6

3

0

1

0

0

2

2

0

2

0

0

0

1

0

0

0

1

0

0

0

0

3

1

6

0

5

0

0

0

0

2

1

4

3

1

1

DS

27

0

0

SL PCST

Denomination

Table 1.3 Occurrences, by categories and countries, in descending order

0

0

3

1

1

0

0

0

1

0

0

0

0

0

0

0

0

0

15 1

0

0

0

0

0

0

0

0

1

0

0

0

0

10

1

1

0

2

0

0

0

0

1

0

EM

26

0

0

0

0

0

ST

2

0

2

3

0

0

0

0

0

3

SI

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

6

0

0

0

VS

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

2

0

0

SM

(continued)

77 46.8%

77 50.6%

77 27.3%

82 67.1%

83 91.6%

84 61.9%

85 52.9%

88 47.7%

90 54.4%

93 67.7%

96 57.3%

97 76.3%

98 22.4%

105 32.4%

109 62.4%

110 69.1%

129 45.7%

134 58.2%

164 37.8%

177 13.6%

P %/SciC

12 B. Schiele et al.

38

37

21

28

31 NG

32 CO

33 FR

34 TW

49

28 ES

60

32

27 GB

42

59

26 BR

29 GH

56

30 UG

0

47

24 TR

25 AU

5

8

3

4

0

0

0

0

0

0

0

0

50

53

22 MY

1

SP

23 SG

SciC

44

Code

21 SC

R

Table 1.3 (continued)

0

0

0

8

5

0

3

0

5

1

7

13

5

1

PE

1

0

3

1

0

0

2

0

3

3

0

2

0

13

PC

1

0

1

2

4

0

0

1

0

8

8

2

15

0

PA

4

10

0

0

3

0

5

0

0

0

3

0

0

0

SC

4

3

9

0

3

0

0

7

4

1

5

1

1

5

PT

0

0

0

0

0

1

4

0

0

2

0

1

0

0

22 0

0

0

1

5

2

0

0

1

0

1

0

0

2

0

0

0

1

0

0

2

SL PCST

0

0

0

0

2

0

PUS

Denomination

1

0

1

0

0

0

2

7

0

0

0

0

0

10

DS

0

4

0

1

0

0

0

0

0

2

3

0

1

0

SI

0

0

0

0

0

0

0

0

0

0

0

0

0

0

ST

0

1

0

0

0

0

0

0

0

0

0

0

0

1

EM

0

1

0

0

0

0

0

0

0

0

0

0

0

0

VS

P %/SciC

(continued)

48 58.3%

54 38.9% 0

54 68.5% 5

57 66.7%

58 72.4%

61 98.4%

63 77.8%

69 46.4%

71 83.1%

71 78.9%

75 62.7%

76 69.7%

76 65.8%

77 57.1%

0

0

0

0

0

0

0

0

0

0

0

0

SM

1 Communicating Science: Heterogeneous, Multiform and Polysemic 13

37 JM

38 n

1

8.4%

258

0

11

5.0%

153

0

0

2

4.2%

129

8

4

23

0

3.9%

121

0

2

0

3.4%

104

1

1

0

2.7%

83

0

2

0

2.3%

72

0

1

0

1.8%

55

0

0

0

1.5%

45

0

0

0

1.4%

44

0

1

0

0.8%

26

0

0

0

0.6%

18

0

0

0

0.2%

7

0

0

0

4.7%

25 48.0% 3076 54.8%

9.3%

SciC = science communication; SP = science popularization; PE = public engagement; PC = public communication; PA = public awareness; SC = scientific culture; PT = public participation; PUS = public understanding of science; SL = science literacy; PCST = public communication of science and technology; DS = democratization of science; SI = scientific information; ST = scientific temper; EM = empowerment; VS = vulgarization; SM = scientific mediation Notes Column 1: line numbering Column 2: international coding (see Box 1.2) Columns 3–18: ‘SciC’ to’SM’: distribution, by categories Column 19: P: total number of occurrences, by countries Column 20: %/SciC: percentage of occurrences of ‘SciC’, by countries Line 21: ‘SC’ (row 21) is an acronym created to refer to Scandinavia (Denmark, Norway and Sweden) Line 38: n: total of occurrences, by categories Line 39: %/n: percentage of one occurrence cross-countries; highlighted values show the maximum number of occurrences for any given category and country Line 40: %/Oc: percentage of the maximum number of occurrences (highlighted in grey) for a given category of the total number of occurrences Line 41: %/OcP: percentage of the maximum number of occurrences (highlighted in grey) for a given category of the total number of occurrences for a given country

7.3% 20.9% 13.0% 16.1% 24.8% 10.3%

46 21.7% 40 42.5%

0.2% 100.0%

7

0

0

4.6% 45.7% 23.3% 50.3% 17.8% 16.5% 10.6% 26.5% 18.1% 49.1% 22.2% 34.1% 100.0% 55.6% 85.7% 71.4%

8.7%

269

4

1

10

41 %/OcP 58.2% 69.5% 61.2% 47.0% 50.0% 15.5% 11.5% 31.9%

40 %/Oc

54.8%

12

1685

36 PH

39 %/n

10

17

35 PK

Table 1.3 (continued)

14 B. Schiele et al.

1 Communicating Science: Heterogeneous, Multiform and Polysemic

15

Box 1.2 ‘Science communication’ … ‘the emergence of modern science communication’ … ‘our book will document the emergence of modern science communication across the world’ … ‘will compare government programs in different countries to support science communication’ … ‘the growth of jobs in science communication’… ‘how and when did research in science communication begin?’ … ‘how did modern science communication begin in your country?’ … ‘did the government become interested in science and science communication?’ …. The other most mentioned terms were, in decreasing order, ‘popularization’ (SP) (269 occurrences, 8.7%), ‘public engagement’ (PE) (258 occurrences, 8.4%), ‘public communication’ (PC) (153 occurrences, 5.0%), ‘public awareness’ (PA) (121 occurrences, 3.9%) and ‘public participation’ (PT) (104 occurrences, 3.4%). Those six categories accounted for 36.6% of all occurrences, which is significant, but the most important factor is the number of occurrences for each term used by each country; for instance, Argentina (AR; Table 1.3, line 18): 30 ‘SP’, 21 ‘SciC’, 12 ‘SC, 5 ‘SL,’ 2. ‘PC’, 2 ‘PT’, 1 ‘PE’, 1 ‘PA’, 1 ‘PUS’, 1 ‘DS’ and 1 ‘SI’, for a total of 77 occurrences (a value corresponding to the median). ‘SP’ (39%) had more occurrences than ‘SciC’ (27.3%). If Germany (DE; line 3), to take another example, was the country with the most references to ‘SciC’ (78), it accounted for only 58.2% of the 134 occurrences of different terms used in the chapter, ahead of ‘PC’ (23, 17.2%) and ‘PT’ (10, 7.5%). As a last example, ‘SciC’ occurred 45 times (52.9%) out of a total of 85 in the contribution on Aotearoa New Zealand (NZ); it was followed by ‘PE’ (29, 34.1%). In short: no author committed to a single term. This diversity of terms needs to be investigated, especially as only five countries have proposed definitions for some of the terms they used: A

B

China: … ‘scientific literacy refers to the following abilities: (1) to possess scientific knowledge, method, thoughts and ethos; (2) to apply them to resolve practical problems and participate in public affairs concerning science and technology’ (Yin and Li 2020:220). Colombia: … ‘social appropriation of S&T … an intentional social process in which diverse actors in a reflexive manner articulate to exchange, combine, negotiate and dialogue knowledge, motivated and by their needs and interests to use, apply and enrich such knowledge in their contexts and concrete realities’ (Franco-Avellanda and Pérez-Bustos 2010, cited by Daza-Caicedo et al. 2020: 243) … ‘a process of understanding and intervention of the relationships between technoscience and society, built upon active participation of the various social groups that create knowledge’ (Colciencias 2010, cited by Daza-Caicedo et al. 2020: 243).

16

B. Schiele et al.

C

Scandinavia (Denmark): … ‘research communication … a way to provide citizens with enough knowledge and competencies to be able to enter into “a democratic dialogue about research, its results and processes, its benefits and opportunities, its consequences, dilemmas and risks”’ (Tænketanken for forståelse for forskning, 2004, cited by Hetland et al. 2020: 260). Uganda: … ‘adult literacy is used in reference to people who missed school or for people who want to acquire new knowledge and skills outside the formal education system’ (Lukanda 2020: 923). United States: … ‘we define science communication broadly as a diversity of activities, with a variety of purposes, that strengthen the connections between the scientific research enterprise (its history, processes, people, and products) and public audiences’ (Bevan et al. 2020: 962).

D

E

It thus truly seems as though the field, which we have called heterogeneous and multiform, is also characterized by the almost random use of a great variety of terms, which authors use to refer to the objects they encounter in their discourse. Thus, the field is heterogeneous and multiform, but also polysemic. Of course, the term ‘science communication’ (SciC), which accounted for 54.8% of occurrences, appears dominant. This is easily explained by the instructions to the authors (Box 1.1): it did not emerge from a consensus that came to dominate and rally all the actors in the field. These polysemic terms constantly overlap and are substitutable for one another; they are expressions of a global, indefinite and undifferentiated signified, thus betraying a conceptual vacuum. Although commendable, the attempt by Burns et al. (2003) to define a number of terms (PUS, SL, SC, SciC) has little echo in the literature; there is no reference to their classification in the corpus, and it now looks somewhat simplistic. The use of one or multiple terms in one or multiple texts, without even a minimal definition—only five authors having defined the terms—projects a false assurance of knowledge, since each term lays claim to a specific category of facts. However, facts do not stand on their own, but make sense only in an explicit theoretical framework: knowledge is only the expression of facts that make direct or indirect sense of it. In the corpus, the terms used are not conceptual tools necessary for a process of understanding; instead, they only simulate it (that is, they merely play a rhetorical role). They ape scientific legitimacy, alluding to legitimate forms of knowledge at a given time, without expressing something specific; that is, they connote without denoting, at times harking to a global pervasive signified. Yet, they never answer the underlying question: what is it? Ultimately, the authors used the terms almost interchangeably, without thinking about subtle variations in their meanings. Table 1.4 lists the 16 groups of terms, separated into the least mentioned, the moderately mentioned and the most mentioned.

1 Communicating Science: Heterogeneous, Multiform and Polysemic

17

Table 1.4 Least mentioned, moderately mentioned and most mentioned denominations Code

Denomination

Count Occ

Least mentioned ST

Scientific temper

1

26

SM

Mediation, scientific mediation

2

7

VS

Vulgarization

2

7

EM

Empowerment

8

18

DS

Democratization of science, social appropriation

14

45

PCST Public communication of science and technology

15

55 158

Moderately mentioned SI

Science information, scientific information, level of information, health 16 or medical information

44

SC

Scientific culture, scientific and technological culture, culture of science 19

121

PUS

Public understanding of science (PUS), public understanding of science 19 and technology

83 248

Most mentioned SP

Science popularization

20

269

SL

Science literacy, scientific literacy

23

72

PC

Public communication of science

23

153

PA

Awareness, public awareness (of the importance of S&T), raising awareness

27

129

PT

Participation, public participation, community participation, participation in science, participatory activities, participative, citizen participation

30

104

PE

Public engagement (PE), public engagement in science and technology 31 (PEST), inclusivity, citizen engagement, engagement with science, critical engagement with science, involvement, engagement model, engagement-oriented approach, engagement-oriented programme, science engagement, mode of engagement, citizen science

258

985 SciC

Science communication

37

1685

Denomination = term and variations of the term; Count = number of contributions that used the term or one of its variations; Occ = number of occurrences of the term

1.3.2 The Structuring Effect of the Context The fact that the authors used some terms more often than others is worth discussing. Table 1.5 presents the same data as Table 1.3 but distinguishes those who used a term at least once (white side of the table) from those who did not (grey side). Occurrences for each category are listed in descending order. Thus, row 1 presents the

AU

IR

IL

SG

RU

MY

ES

PT

11

12

13

14

15

16

17

18

SC

BR

10

21

5 ZA

47 UG

CA

9

TR

GH

8

NZ

MX

7

19

5 IN

49 MY

NL

44 EE

45 NL

49 BR

50 DE

52 IT

53 IN

55 CN

55 TR

56 KR

59 NG

59 TH

3 EE

4 NZ

5 MX

5 AR

5 IT

5 IR

5 UG

7 IE

7 FR

8 BR

9 TW

60 RU 10 SC

62 JP 11 TR

63 PH 11 CN

68 SG 13 GB

74 IL 13 PT

76 IE 23 CO

6

20

PA

PC

SL

2 IE

2 AR

2 CO

2 IT

2 RU

1 EE

1 NL

1 NG

1 JP

1 IL

2 NG

2 DE

2 NZ

3 PT

3 PK

4 AR

4 ES

4 SG

5 CO

5 AU

2 SG

3 JP

3 NZ

3 UG

3 PH

4 IR

4 IE

5 ZA

8 BR

5 JM

SP

PUS

SC

SI

5 RU 14 DE

1 MX

1 TR

1 RU

1 PH

1 US

1 IL

1 JP

IE

1 CO 0 TR

1 EE

1 RU

1 TH

2 NZ

3 AR

3 UG

4

4 CN

5 MY

5 PH

6 KR

8 US

8 CA

IR

IL

1 PH

1 SC

1 CA

1 DE

1 CO

1 IL

2 JM

2 NG

2 IT 2 NG

2 TW

2 IT

4 IR

4 FR

4 MX

4 PK 10

4 IN 10

4 TH 10 PT

3

0 MY

0 PK

1 DE

1 NZ

1 TH

1 PH

1 IR

1 ZA

1 UG

2 IE

2 TR

3 IN

3 TW

3 ES

3 IL

0 0

1 GB 1 US 0 CA

IR

IN

ES

NL

SC

NZ

IE

DE

IT

KR

EM

VS

SM

ST

PT

SG

0 MY

0 JP

0 NG

0 IR

0 IN

0 NZ

0 PH

0 MY

0 NG

0 IR

0 PT

0 AR

0 IT

CN AR

0 IE

1 KR FR

0 TR 0 IT 0 IR

1 IL

0 0

0

(continued)

0 MY 0 NG 0 CA

0 NG 0 IR 0 DE

0 IR 0 PT 0 US

0 0

0 PT 0 AR 0 GB

0

0

0

0

0 AR 0 IE 0 SC

0 IE 0 AU 0 PH

0 AU 0 IL 0 MY

0 IL 0 TR 0 NG

0 0 IT 0 CN 0 PT

1 TR

0

0 0 CN 0 NL 0 AR 1 IT

0 0

0 1 MX 0 SC 0 ZA 0 NL 0 NZ 0 IE

0

1 SC 0 ZA 0 IL

1 CN

0

1 ZA 0 IN 0 TR

0 NZ 0 MX 0 AU

0

1 TH 0 US 0 CN 1 IN 0 TH 0 IT

0 0

1 US 0 CA 0 FR

2 FR 1 DE 2 NL

1 NL

2 NZ

2 MX

3 SC

4 ZA

5 FR

6 IN

7 TH

1 AU

1 MX

1 TW

1 PT

1 AR

2 CN

2 ES

2 CA

2 IE

2 DE

3 US

3 NL

6 GB

1 CO

TR

JP

0 TW

0

0 DE

1

2 PH

1

1

1

DS

CA 27 SC 10 US 10 CA 6 FR 5 IN 26

PCST

1 NG

1

1

2

2

2

3

1 SC

2 MY

2 NG

3 IR

3 PT

3 AR

3 IE

4 AU

5 ZA

6 IL

4 FR 10 TR

3

5 AR 12 IT 5 MX 11 IN

3

4

7 IT 13 CN

JP 17 PT 19 FR

5 KR 21 IN

8 AR 30

2 TH

2 MY

2 TW

3 IE

3 KR

3 IR

3 PT

8 ZA

6 TR

5 SG 4 IN

9 RU 8 IT

7 AU

7 IN

9 MY 15 SC 13 AR

76 NZ 29 DE 10 TH 15 DE 23 CA

US

3

PT

TH

JP

2

PE

78 ZA 60 IL 11 PK 23 MX 77 CN 13 CN 123 GB 22 CA 20 NL 15

5

EE

1

4

SciC

DE

R

Denomination

Table 1.5 Order of categories, by occurrence of the terms or lack thereof

18 B. Schiele et al.

IE

UG

IT

NG

CO

KR

IN

GB

TW

CN

ZA

AR

FR

PH

JM

PK

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

PE

PT

SL

0 ES

1 ES

0 PK

0 JP

0 NG

0 RU

0 KR

0 GH

24 PT

22 FR

21 TW

21 JM

17 CO

12 GH

10 GB

104

129

0 GB 153

0 PK

0 ES

0 JM

72

0 ZA

0 GB

0 UG

0 IE

0 NZ

0 TR

0 PT

0 ES

0 MY

0 SG

269

0 GH

0 NG

0 PK

0 ES

0 SG

0 JM

0 AU

0 NL

0 EE

0 ZA

0 MX

83

0 GH

0 US

0 KR

0 NL

0 BR

0 SC

0 GB

0 CN

0 EE

0 CO

0 RU

0 NG

0 SG

IT

0 FR 0

0 JP

0 BR

SI

121

0 PK

0 JM

0 EE

0 BR

0 UG

0 GH

0 RU

0 TH

0 SG

0 JP

0 NZ

0 KR

0 CO

0 MX

0 TW

0 ES

RU

PH

US

IL

TH

ZA GB

EE

BR

CO

44

0

0

PK

JM

0 AU

0

0

0

0 UG

0

0 GH

0

DS

0 PK

0 JM

0 AU

0 EE

0 BR

0 UG

0 GH

0 ZA

0 RU

0 PH

0 IL

0 TH

0 MY

0 SG

0 FR

0 TR

55

PCST

0 MX

0

0

0

0

0

EM

45

0 PK

0 JM

0 EE

0 BR

0 UG

0 GH

0 RU

0 SG

0 JP

0 KR

0 CO

0 TW

0 ES

0 CA

0 DE

0 GB

VS

SM

ST

18

7

7

0 PK 0 PK 0 PK

0 JM 0 JM 0 JM

0 EE 0 EE 0 EE

0 BR 0 BR 0 BR

0 UG 0 UG 0 UG

0 GH 0 GH 0 GH

0 RU 0 RU 0 RU

0 SG 0 SG 0 TH

0 JP 0 JP 0 SG

0 KR 0 KR 0 JP

0 CO 0 CO 0 NZ

0 TW 0 TW 0 KR

0 ES 0 ES 0 CO

0 DE 0 GB 0 MX

0 GB 0 PH 0 TW

0 PH 0 MY 0 ES

26

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

SciC: science communication; PE: public engagement; PT: public participation; PA: public awareness; PC: public communication; SL: science literacy; SP: science popularization; PUS: public understanding of science; SC: scientific culture; SI: scientific information; PCST: public communication of science and technology; DS: democratization of science; EM: empowerment; VS: vulgarization; SM: scientific mediation; ST: scientific temper Note: Number above zero indicates at least one occurrence in a given category; grey indicates its absence

258

0 GH

0 JM 0 GH

0 AU

0 FR

0 US

0 NL

0 EE

0 US 0 CA

0 FR

0 UG

0 FR

0 KR

0 NL

0 IL

0 BR

0 MY

1 BR

0 CO

1 US

28 AU

1 SG

1 JM 0 SC

32 SC

34 CA 0 IN

0 NZ

1 SC

0 AU

0 UG

0 CN

0 BR

0 DE

1 TH 1 KR

0 GH

0 NL

0 GB

1 PH

0 JM

1 US

0 TW

SC 0 AU

PUS 0 SC

SP

Denomination JP

1 GH

1

1 TW

1 ZA

1 MX

1 CA

1 CN

1 TW

1 EE

PC 1 IR

1 TR

1 AU

36 MX

PA

2 PT

1 GB

1 MY

1 TH

2 PH

3 CA

3 NL

37 PK

38 AR

39 IR

42 ES

42 US

1685

SciC

R

Table 1.5 (continued)

1 Communicating Science: Heterogeneous, Multiform and Polysemic 19

20

B. Schiele et al.

greatest number of occurrences of a given expression for a given country, regardless of category. Taking ‘SciC’ as an example, the greatest number of occurrences is 78 (DE, row 1: Germany) and the lowest is 10 (PK, row 37: Pakistan) (see Table 1.5). We note that, once the data is reorganized in this way, the table is subdivided into two nearly equal parts, separated by a stepped line. By comparing the columns, we observe that a number of authors favour one term over another, independently from the fact that a number of terms are favoured over others by the authors taken collectively. For example, ‘SP’, the second category in terms of occurrences with a total of 269, is mentioned by the author of the contribution on China (CN) 123 times—the greatest among all countries in the corpus. This term is also present in 19 other contributions: Argentina (AR) 30 times, South Korea (KR) 21 times, Russia (RU) 14 times, and so on in descending order. As another example, ‘ST’ (scientific temper; last column on the right), is mentioned 26 times in the corpus, occupying the 13th rank after ‘SI’ (44 occurrences) but before ‘EM’ (18 occurrences) and ‘VS’ and ‘SM’ (7 occurrences each), and yet does not occur outside the contribution on India (IN). We address the specific cases of China and India below. More generally, Table 1.5 presents the terms that have currency in the field. Thus, ‘SciC’ is mentioned by all 37 authors, ‘PE’ by 31, ‘PT’ by 30 and so on. And, in so far as a given term appears in multiple discourses produced in the field, Table 1.5 shows—within the limits of the corpus—the rate of penetration of a term in the field and its use by the various authors. In this spirit, we observe that a first group of terms (‘ST’, ‘SM’, ‘VS, ‘EM’, ‘DS’, ‘PCST’) is little used (a total of 158 occurrences). However, it could be argued that ‘DS’, used by 14 authors, and ‘PCST’, used by 15, occupy a middle rank. However, only Scandinavia (SC) and Canada (CA) use them 10 or more times. A second (middle) group (‘SI’, ‘SC’, ‘PUS’), with 16 (‘SI’) to 19 (‘SC’, ‘PUS’) countries mentioning them, accounts for a total of 248 occurrences, and a third (major) group (‘SP’, ‘SL’ ‘PC’, ‘PA’, ‘PT’, ‘PE’) accounts for a total of 985 occurrences, if ‘SciC’ is excluded, or 2,670, if it is included. Of course, the pertinence of this repartition (‘little’, ‘moderate’ and ‘major’) can be questioned, but it illustrates the rate of penetration of a given term in the field (see Table 1.4). A number of categories demand a more in-depth discussion.

1.3.3 Science Communication (SciC) All the authors employed ‘SciC’ since, as we have suggested, the instructions to the authors proposed a generic term in order to standardize the terminology of all the contributions to the book on the theme expressed in its very title: Communicating science. A global perspective. Our view is that ‘SciC’ has largely gained currency in the discourses in and about the field—for the time being—because it is generic, encompassing other terms, some of which have played the same role in the past: ‘SL’ (Miller 1983; Durant 1994), ‘PUS’ (see ‘PUST’) (Durant et al. 1989), and more recently ‘PCST’ (Fayard 1987, 1988). Furthermore, relativizing its popularity, ‘SciC’ now has to contend with ‘PE’ (public engagement), ‘PT’ (public participation), ‘PA’

1 Communicating Science: Heterogeneous, Multiform and Polysemic

21

(public awareness), and, more recently, ‘citizen science’ (CT) (Lewenstein 2016; Hecker et al. 2018). Those later terms all stress the active role of the public. In this spirit, ‘SciC’ could be interpreted as situational: ‘SciC’, by virtue of its recentness, rings more modernly for a discourse that seeks to distance itself from the past. We can also question, on another level, whether the generic use of ‘SciC’ is not a bid for the autonomization of a heterogeneous field particularly exposed to political, social and cultural winds (see European Commission 2020). We can question whether the popularity of the term is not the sign of a renewed interest motivated by the necessity of an acculturation of the public. Bauer and Schiele have identified new cycles of interest and disinterest in science: an interest stirred by the arrival of new technologies (Bauer 2012, 2017), new economic imperatives (Schiele 2005), or both, followed by a latency period during which the adaptation of the public is not pressing anymore. Thus, the replacement of one term by another might be the sign of technoeconomic transformations necessitating a new social and cultural acculturation of the public. Perhaps it is in this spirit that the recent rise of the term ‘citizen science’, which is promoted by the European Commission (2020), should be interpreted. Note: Number above zero indicates at least one occurrence in a given category; grey indicates its absence. On this point, it must be said that ‘SciC’ coexists with ‘PE’ (public engagement), which was mentioned by 31 authors, ‘PT’ (public participation), mentioned by 30, and ‘PA’ (public awareness), mentioned by 27, for a total of 491 occurrences (or 15.9% of all occurrences), to which ‘EM’ (empowerment) should be added, although only eight authors made use of that term. It might be useful to stress that these expressions advocate, at least in principle, for a two-way communication between the public and specialists; that is, for a greater role for the public in decision-making on economic, environmental, health and risk issues that could potentially affect it (Schiele 2020; Bressers 2010). Furthermore, those terms, and the practices that they imply, presuppose an acknowledgement of the respective abilities and contributions of both the public and specialists, and not a deficit to overcome. In short, for a vision founded on the premise of a knowledge deficit needing to be overcome, is substituted a vision emphasizing a consultation processes (Bauer et al. 2007), if not participation, involving equal partners with varied expertise. Of course, it is not certain that all authors subscribe to that interpretation, since all these terms are interchangeable and without clear definitions. The other terms (‘SL’, ‘SP’ and so on), the use of which is on a descending trend, emphasize the idea of increasing the public’s level of knowledge (‘EM’, ‘SM’ and ‘ST’ serve other purposes, to which we return below).

1.4 Least Mentioned Terms Table 1.6 presents in decreasing order by country the maximum number of occurrences of a term for a given country (from left to right) and also in decreasing order the number of occurrences of a given term in the corresponding category (from top to bottom). This table shows, once again, that China (CN) occupies the first rank with

10

10

10 MX 62

TH

IN

PK

131

153

85.6%

258

65.9%

23.3%

170

RU 10

JP 11

3

PH 11

3

SG 13

IL 13

IE 23

NZ 29

3

4

5

50.3%

AU

BR

ZA

IT

RU

SC 13

DE 23

ZA 60

PE

55

85.5%

49.1%

47

NL 2

SC 2

NZ 2

IE 2 JM

IL 0

26

100%

100%

26

91

5

8

8

8

9

129

70.5%

17.8%

ZA

TR

TR 0 ZA 0

AU

IT 0

IN

FR 0 MY 15

TH 15

NL 0

SC

AR 12

IT 13

PT 19

CA 20

83

79.5%

26.5%

66

CA 3

IR 3

IL 4

96

5

6

121

79.3%

16.5%

ES

IL

FR 10

PT 5 MX 11

DE 5

IN 7

JP 17

GB 22

PK 23

IN 26

Denomination PUS

PA

ST

DE 3 CN 0

IT 3

KR 6

CA 27

PCST

SI

44

79.5%

34.1%

35

ZA 2

IL 2

TR 3

IN 3

IT 3

CN 3

FR 4

NL 15

SL

72

65.3%

18.1%

47

KR 4

IR 4

PT 4

IN 4

SG 5

AR 5

CA 8

CN 13 9

60

5

5

6

7

7

104

57.7%

10.6%

SC

TR

CN

GB

PT

CO

DE 10

IL 11

PT

SC 1

ZA 1

FR 1

IN 1

TH 2

US 10

EM

45

86.7%

22.2%

39

ES 2

SC 0

ZA 0

IN 0

TH 0

US 0

FR 1

CA 6

VS

7

7

SC 0

ZA 0

IN 0

TH 0

US 0

CA 0

DE 2

FR 5

SM

18

100%

7

100%

7

100%

55.6% 85.7% 71.4%

18

NZ 1 MX 0

CA 2 MX 1

IE 3

DE 4

US 5

NL 6

GB 7

SC 10

DS

SP = science popularization; SciC = science communication; PC = public communication; PE = public engagement; PCST = public communication of science and technology; ST = scientific temper; PA = public awareness; PUS = public understanding of science; SC = scientific culture; SI = scientific information; SL = science literacy; PT = public participation; DS = democratization of science; EM = empowerment; VS = vulgarization; SM = scientific mediation Notes n: Total number of occurrences for the eight countries r/tn: Shows which country used the term most frequently, and what percentage of total uses by all countries; for example, China, 123 uses, total uses 269 = 45.7% n/tn: Shows the percentage used by the top eight countries of total uses by all countries; for example, ‘SP’ (science popularization) used 226 times by top 8 countries; total uses by all countries 269 = 84% tn: Total uses by all countries

1685

33.1%

n/tn 84.0%

269

4.6%

r/tn 45.7%

tn

557

GH 60

NL 63

TH 68

226

n

8

14

MX

JP 76

21

KR

RU

US 74

EE 76

30

AR

PC

DE 78 MX 77

123

SciC

CN

SP

Table 1.6 Maximum number of occurrences for a given country, in decreasing order

22 B. Schiele et al.

1 Communicating Science: Heterogeneous, Multiform and Polysemic

23

123 occurrences of ‘SP’, followed by Mexico (MX; ‘PC’, 77 occurrences); South Africa (ZA; ‘PE’, 60 occurrences), and so on until the last category, ‘SM’. We also observe that values above 10 for a given country, regardless of the maximum number of occurrences by category, are limited to 6 countries for ‘SP’, 7 for ‘PE’, 5 for ‘SC’, 3 for ‘PA’, and 2 for ‘PUS’. The category ‘SciC’ is not taken into account for the reasons mentioned above (Table 1.6). This leads us to believe that the meaning given to each term, even if a number of terms are used across contributions (‘PE’, 31 countries; ‘PT’, 30 countries), is not the same for the authors who use them. In other words, if the number of countries that use a given term is an indicator of the term’s degree of penetration of the field, it cannot be assumed that every author uses it in the same sense. And, in order to identify the sense in which an author uses it, it is important to understand the specificities of each country. However, because of limited space, we shall limit ourselves to the most important values; that is, the terms for which the meaning is clearly distinct. We begin with the least mentioned terms (cf. Table 1.5).

1.4.1 Scientific Temper (ST) The case of India (IN) is interesting. We observe that India was the only country to use the term ‘scientific temper’, and does so 26 times in a total of 105 terms in the text (24.8%). This term, specific to the Indian context, has until now not been used by other researchers in the field, although a number of them have referred to the term in a distinct national context (Du Plessis 2013). We note that this term was not defined by the author, as if its meaning were self-evident. In the Indian context, ‘ST’ refers ‘to a broad set of values that are rooted in the European ideas of the “Enlightenment”. Those values touch areas of human cognition and actions beyond the boundaries of science and impinge upon the domain of extra-science’ (Raza 2015: 41–42). Historically, the term ‘ST’ is closely linked to the struggle for national independence and empowerment during the nineteenth century. Scientific temper, adopted by Nehru in 1946, stresses the promise of empowerment made possible by the scientific spirit (Raza 2012). In other words, the term ‘ST’, far from being an attempt at theorization, is in fact tributary to the Indian historical and political context.

1.4.2 Scientific Mediation (SM) In the same vein, we observe that ‘SM’ was used exclusively by France (FR, 5 times) and Germany (DE, 2 times). Bergeron (2016) specifies that the term ‘science communication’ was common in France during the 1970s and 1980s, when communication—both as utopia (Breton 1997) and an area of knowledge (Breton and Proulx 2002)—was on the rise. The term has since fallen into disuse. According to the author,

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the concept of ‘cultural mediation’, which has replaced it since the 1980s, is linked to the professionalization of the staff of cultural institutions, and notably of museum staff. It is on this concept of ‘cultural mediation’ that the concept of ‘scientific mediation was partly (built), itself linked to the issue of professional recognition’. In other words, the generalization of the term in France is directly linked to the evolution of the French context, explaining why it was nearly never used elsewhere. In France, in contrast to India, where the political project imposed a vision for the future of Indian society, it was the evolution of working relations that weighed on the evolution of the terminology. However, the author also uses the term ‘SC’ (10 occurrences), which we discuss below.

1.4.3 Science Vulgarization (VS) The use of ‘VS’ in Canada is, to some extent, tributary to the French context, since the term was common in the Francophonie (French-speaking countries) but not in other linguistic contexts. It must be underlined that in France the term ‘scientific vulgarization’ was at times used pejoratively because it derived from the Latin vulgus (the crowd; Jeanneret 1994). In a country that puts much stress on high culture, the valorization of science and scientific techniques long fell outside official circuits, until their entry into cultural institutions at the end of the 1960s (Bergeron 2020: 306 sq.). The term ‘science and technical culture’ (SC) then became predominant in France, and it is in this context that we can understand the persistence of ‘VS’ in Canada and its absence in other countries, with the exception of France (1 occurrence).

1.4.4 Empowerment (EM) The United States mentioned ‘EM’ (empowerment) 10 times. According to the author, the turn of the 1970s saw power structures increasingly challenged by political demands. For example, according to Bevan and Smith (2020), a number of episodes from the NOVA television series, first broadcast in 1974, clearly adopted ‘critical perspectives on how human progress and tools of sciences had put the planet and its inhabitants in various types of danger’ (p. 967), while science centres, then in development, aimed ‘to empower rather than strictly enlighten’ (p. 968). They stressed that ‘This emerging discourse of science as empowerment … aimed to support the populace to pay attention, to ask questions, to see science as something we all can do, and to use science to challenge authority’ (p. 968). ‘EM’ is embedded in the US context, which would explain why this term, contrary to the more neutral ‘PE’ (258 occurrences), is rarely used in other national contexts: only seven other countries did so, but it is decontextualized, as is the case with all the terms used by the authors.

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What is important for our discussion in the case of India, France, Canada and the United States is the fact that the authors were nearly alone in using these terms (see Table 1.5), even if their discourses were peppered here and there with other terms, as was the case for all the authors.

1.4.5 Democratization of Science (DS) A little under half of the authors used the term ‘democratization of science’ (Table 1.5), yet it is still sufficiently modern to hold currency in the field. Scandinavia mentioned ‘DS’ 10 times and ‘PC’ (public communication) 13 times. According to the author, science communication played an important role in the ‘formation of national identity’ (Hetland et al. 2020: 255): ‘At the core of society [is] the informed citizen, responsible for their own self-improvement and enlightenment’ (p. 256). According to the author, this enduring vision was the outgrowth of a consensus achieved as early as the 1930s. Scandinavia thus parallels India, since in both cases a citizen (citizenship being the determinant) cannot contribute to the construction of national identity unless they are informed and responsible for their own education, and the very success of the collective project rests upon the successful educational development of the citizen. To some extent, for Scandinavia and India, the issue is the perpetuation of the ideal of the Enlightenment transposed to different contexts. Its contemporary reformulation in Scandinavia stresses not only greater collaboration between the academic community and society but truly a convergence of expectations: ‘One of the challenges faced in all three countries is how to match the demands of the academic community … with the demands of society’ (Hetland et al. 2020: 273).

1.4.6 Public Communication of Science and Technology (PCST) Although tied to the French context, ‘PCST’, with 27 occurrences in the contribution from Canada, is almost exclusively used by francophone Canada. As mentioned, Pierre Fayard suggested in 1988 the term ‘public communication of science’ (PCS), to which ‘technology’ was later added, before it was translated into English as ‘PCST’. However, this term is not as widespread as it might be (given that it lends its name to the biennial PCST conference), since only 14 authors mobilized it, or a little over half. It is noteworthy that South Korea (KR), which ranked second with 6 mentions, hosted the 2006 PCST conference.

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1.5 Moderately Mentioned Terms 1.5.1 Scientific Information (SI) The term ‘scientific information’ was used 15 times by the Netherlands and by 15 other authors, although not with the same weight: 4 for France (FR), 2 for China (CN), and so on. Seven countries mentioned it only once (Table 1.5). Traditionally, ‘SI’ implied a transmission of knowledge in which universities had to play a part. However, the term took on a new meaning with the spread of ‘science shops’, which were developed in the Netherlands during the 1970s, which led to a new debate and a transformation of the mission of universities. As in Scandinavia, universities were now expected to play an important role in finding solutions to social problems. Even if the number of science shops has fallen since the 2000s, when nearly every university housed one, the idea that scholarly work could not be dissociated from the social context has endured. ‘Dutch universities have been reconsidering their relationship with society and are acknowledging that societal needs should be better incorporated in their research and policies’ (Dijkstra et al. 2020: 602). In other words, to limit oneself to the term’s literal meaning would distort its wider meaning in Dutch society.

1.5.2 Science Culture (SC) ‘Science culture’ was mentioned 20 times by Canada (CA), 19 times by Portugal (PT), 13 times by Italy (IT), 12 times by Argentina (AR), 11 times by Mexico (MX), 10 times by France (FR), 6 times by Israel (IL) and 5 times by Spain (ES). It must be stressed that, with the exception of Israel, all those countries speak romance languages. Together, they accounted for 96 occurrences out of 121, or 79.3%. In francophone countries, and more generally in European countries, ‘SC’ has a broader scope than ‘PUS’ or ‘SL’ since, contrary to the many approaches that dissociate science from culture, it stresses the social dimension of culture and science as an expression of culture. In this sense, ‘SC’ is a collective phenomenon; that is, it is not limited to individual knowledge or attitudes. Pace Burns et al. (2003), ‘SC’ is not limited to a value system that appreciates and promotes science. As an aside, we concur with Godin and Gingras that ‘SC’ ‘is the expression of all the modes through which individuals and society appropriate science and technology’ (2000: 44), with the keyword precisely being ‘appropriation’. However, no author thought it important to define ‘SC’.

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27

1.5.3 Public Understanding of Science (PUS) ‘Public understanding of science’ was mentioned 22 times by the United Kingdom and 17 times by Japan. The 17 other authors who made use of this term did so at most 7 times (IN). The case of ‘PUS’ is interesting, since that term played a major role in the field until very recently. It gained pre-eminence in the wake of the publication of the Royal Society report The public understanding of science (also called the Bodmer report). The report had tremendous influence in the United Kingdom, and its main effect was the creation of the Committee for the Public Understanding of Science (COPUS), the mission of which was to implement the report’s recommendations. The report ‘lamented the apparently low levels of public awareness and understanding of science in the UK, and it called upon the scientific community to make far greater efforts to communicate with the general public’ (Durant 1994a: 336) This was a project to which Durant subscribed, although he himself recognized that ‘PUS’ was a ‘notoriously ambiguous’ term (idem). It is useful to point out that the journal Public Understanding of Science was founded in 1992 in this context and can therefore be seen as an artefact of those events. The 2000 House of Lords reports took the Bodmer report one step further by promoting, as in the Netherlands and in Scandinavia, a model taking into account the participation of citizens and promoting open dialogue between scientists and the public (HLSCST 2000). It is very interesting to note (Table 1.5) that the author mentioned ‘PT’ 7 times, ‘DS’ 7 times and ‘PA’ once (all of which belong to the same semantic field), but not ‘PCST’, ‘SP’ or any other terms, with the exception, of course, of ‘SciC’. The term ‘PUS’ peaked in popularity in the 1990s and 2000s, focusing on the evolution of the science–society dynamic, with the aim of countering the discrediting of science and technology, which was then explained as a lack of understanding of scientific work by the general public. Durant et al. (1989: 11) forcefully expressed this goal: ‘common sense suggests that the scientific community would be unwise to presume upon the continued backing of a public that knows little of what scientists do’, echoing Isaac Asimov’s warning: ‘Without an informed public, scientists will not only be no longer supported financially, they will be actively persecuted’ (Asimov 1983). In the United Kingdom, as elsewhere, the specific context weighed upon the debates on (to simplify) science–society relations, and from those debates the term ‘PUS’ emerged. It was a term that, far from expressing a consensus, nonetheless received wide assent because it crystallized the zeitgeist—a buzzword that marginalized alternative terms. Subsequently, ‘PUS’ was itself displaced when the need to acculturate the public arose anew under the impact of a new wave of transformations spurred by the evolution of science and technology. The case of Japan, which added a ‘T’ (for technology) to form the compound ‘PUST’, deserves a special mention. The scope of the term has been retroactively applied back to 1960 when the Council for Science and Technology adopted a policy ‘to develop a talented workforce to drive its long-term pursuit of the sciences and technologies needed to grow the economy and improve lives’ (Watanabe and Kudo

28

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2020: 522). According to the author, ‘this policy marked the dawn of public administration aimed at boosting the public understanding of science and technology (PUST)’ (idem). However, it is plain that the meaning of ‘PUST’ in Japan differs from that of ‘PUS’ in the United Kingdom. The term ‘PEST’ replaced ‘PUST’ in Japan following the Fukushima nuclear disaster 11th March 2011), which revealed that the government had neither planned for such a contingency nor had on hand the necessary information for the public to deal with it. ‘The government and the scientific community experienced a great loss of public trust as a result of this disaster’ (p. 530). In other words, the meaning of ‘PEST’ parallels that of ‘PUS’, with the added element of ‘engagement’, since from the Fukushima disaster the ‘public gained the realization [that] people have to look out for themselves’ (p. 533). A final remark about moderately mentioned terms: we categorized ‘SC’ and ‘PUS’ as moderately mentioned terms because they were mobilized by only 19 of the 37 authors. We concur that they could have easily been categorized among the most mentioned expressions, since they are mentioned 121 times and 83 times, respectively. However, with such a methodology, ‘SL’, with 72 occurrences, would likewise have had to be categorized among the most mentioned expressions. It was, therefore, necessary to compromise between the number of authors and the number of occurrences, since the overall distribution was unequal: every author used various terms, yet favoured only a number of them. We settled on a mention by 20 different authors as the cut-off point between ‘moderately mentioned’ and ‘most mentioned’.

1.6 The Most Mentioned Terms Six terms (Tables 1.4 and 1.5) were used more than the others: ‘SP’ (20 authors, 269 occurrences); ‘SL’ (23 authors, 72 occurrences); ‘PC’ (23 authors, 153 occurrences); ‘PA’ (27 authors, 129 occurrences); ‘PT’ (30 authors, 104 occurrences); and ‘PE’ (31 authors, 258 occurrences).

1.6.1 Science Popularization (SP) China (CN) was the main user of the term ‘SP’, using it 123 times (Tables 1.5 and 1.6). The number of occurrences in the category ‘SP’ for the eight countries under consideration rose to 226 out of a total of 269 (Table 1.6), or 84% of occurrences, and China accounted for nearly half (45.7%). China also used ‘science literacy’ (‘SL’) the most (13 occurrences). Together, ‘SP’ and ‘SL’ accounted for 76.8% of all the terms China used (177, Table 1.3). ‘PT’ and ‘PE’, with 6 and 5 occurrences, respectively, accounted for only 6.2%. The author defined ‘SL’, which accounted for 7.3% of occurrences, but not ‘SP’, which accounted for 69.5%. The choice of this term is accounted for by the context: the author is affiliated with CRISP (the China Research Institute for Science Popularization), which is tasked with researching the

1 Communicating Science: Heterogeneous, Multiform and Polysemic

29

communication of science and technology in China and publishing a journal titled Studies on Science Popularization. Similarly to India, but more formally, the term ‘SP’ is enshrined in the 2002 Law of the People’s Republic of China on Popularization of Science and Technology (Yin and Li 2020: 214 sq.). Such a context, to an extent, excludes any form of theorization. We can add that ‘SP’ was also prevalent in the contribution on Argentina (30 occurrences, 21 for ‘SciC’ and 12 for ‘SC’). There again, the pervasiveness of culture and politics appeared determinant, since the term is present in official documents: ‘Science Culture Center (C3), an interactive space of popularisation. Its first director … was one of the country’s most prominent figures in popularisation … [F]rom 2013 onwards all those actions were unified in the National Program of Science and Innovation Popularisation’ (Cortessa and Rosen 2020: 113). South Korea mentioned ‘SP’ 21 times, but ‘SciC’ only 36 times and ‘PCST’ 6 times: again, the cultural and political context weighs on this discourse. As early as the 1960s, the transmission and socialization of scientific knowledge—seen as the key to economic development—had become the policy of the state and remains so to this day (Kim 2020: 802 sq.). Notwithstanding the differences in regime types, there is an unmistakable convergence between South Korea and China. However, we observe that the author’s use of the term declines with the emergence of current issues.

1.6.2 Science Literacy (SL) China was the main user of the term ‘science literacy’ (13 occurrences), followed by Canada (8 occurrences). Those two contributions accounted for 27.8% of occurrences out of the 23 authors who used the term.

1.6.3 Public Communication of Science (PC) ‘Public communication of science’ was mentioned 77 times by Mexico or 50.3% of the total number of occurrences among all countries, and 47% of the total number of occurrences in all contributions. It was followed by Germany (23 occurrences) and Scandinavia (13 occurrences). The gap between Mexico, Germany and Scandinavia is significant. Mexico used ‘SciC’ 62 times and ‘SC’ 11 times. The author stressed a continuity of scientific tradition which, though interrupted very recently, purportedly goes back to the Mayas. Thus, the same term is used to cover activities that took place in vastly different sociohistorical contexts (Maya and Aztec cultures, the Spanish conquest, the wars of independence and so on). The author explained that the first institutional manifestations of science communication took form at UNAM and CONACYT in the 1960s. Those two organizations would soon be joined by the AMC

30

B. Schiele et al.

and the SOMEDOCyT,11 and are collectively referred as the four ‘pillars’ (ReynosoHaynes et al. 2020: 571) of the beginnings of modern ‘PC’, that term superseding the former term ‘divulgation of science’. The authors stressed that, today, ‘PC’ is ‘the preferred term in Mexico’ (idem) and covers a wide range of activities. The term is less restrictive than its predecessor, which was indebted to the deficit model. In other words, as for many countries, it is a generic term accounted for by the specific context of Mexico. Germany (DE) used the expression ‘SciC’ the most (78 occurrences), followed by ‘PC’ (23 occurrences). As we have already pointed out, the last three terms (PC, SL and SP) have two things in common: they were the most mentioned, and they privilege public engagement and participation. They accounted for 491 occurrences, or 49.8% of the total number in the category of the most mentioned terms.

1.6.4 Public Awareness (PA) Paradoxically, of the 27 authors who mentioned ‘PA’, only three used it more than 10 times: Pakistan (PK, 23 occurrences), Thailand (TH, 15 occurrences) and Malaysia (MY, 15 occurrences). The others mentioned it fewer than 10 times, starting with India (9 occurrences).

1.6.5 Public Participation (PT) The discrepancy was even more acute with ‘public participation’, which only two authors used more than 10 times: Israel (IL, 11 times) and Germany (DE, 10 times). Another 28 authors did so fewer than 10 times, starting with Colombia (CO, 9 occurrences). It can be surmised that, since the terms ‘PA’ and ‘PT’ were among those occurring the most, they are now superseding the others, without necessarily echoing specific policies or practices. The exception may be Israel (IL), for which ‘PT’ (11 occurrences) and ‘PE’ (13 occurrences) accounted for 25% of the total number of occurrences, while ‘SciC’ largely dominated (57.3%). Are they, as Chilvers and Kearnes (2020) suggest, the sign of a contradiction between effective practices and the difficulty in laying down the conditions for a genuine participation? The question is still open.

11 UNAM = National Autonomous University of Mexico; CONACYT = National Council for Science and Technology; AMC = Mexican Academy for Science; SOMEDOCyT = Mexican Society for the Communication of Science.

1 Communicating Science: Heterogeneous, Multiform and Polysemic

31

1.6.6 Public Engagement (PE) ‘Public engagement’, with 258 occurrences, was the second most mentioned term after ‘SP’ when the total number of occurrences was taken into account, and yet held the first rank (with the exception of ‘SciC’) in terms of countries (31). Eight countries mentioned it 10 times or more (Table 1.6): South Africa (ZA, 60 times); Aotearoa New Zealand (NZ, 29 times); Ireland (IE, 23 times); Israel (IL, 13 times); Singapore (SG, 13 times); the Philippines (PH, 11 times); Japan (JP, 11 times); and Russia (RU, 10 times). The prevalence of ‘PE’ in South Africa (ZA) is linked to current government policies. ‘Current sciences policies, including new legislation, white papers and longterm strategic plans, demonstrate that policymakers see public engagement as a tool to democratize science, increase the social impact of science and sustain the public trust in science’ (Joubert and Mkansi 2020: 780). From that perspective, ‘PE’ overlaps partly with the aims of ‘PUS’ as formulated by Durant et al. (1989). And yet, ‘PE’ in South Africa takes into account transformations within society that are spurred by technological changes and changing public expectations: ‘Public engagement with science is regarded as a prerequisite for South Africa to become a knowledge-based society with a participatory mode of science governance’ (Joubert and Mkansi 2020: 780). In other words, similarly to ‘PUS’ in the United Kingdom, ‘SP’ in China and ‘ST’ in India, ‘PE’ reflects above all else a political vision. It is significant that those contributors were among those who used ‘SciC’ the least: India, 34; the United Kingdom, 32; China, 24; and South Africa, 22. Aotearoa New Zealand (NZ) mentioned ‘PE’ (29 times) and ‘SciC’ (45 times). It would seem that two factors imposed the term ‘PE’: on the one hand, the Nation of Curious Minds initiative (2018) ‘was designed to fund projects bringing science to society, thereby enabling better engagement with science and technology for all New Zealanders’ (Fleming et al. 2020: 76); and, on the other, social demands: ‘recent public engagement with scientific issues has been fueled by health-related issues and by grassroots environmental movements’ (Fleming et al. 2020: 77). Ireland (IE) closely paralleled Aotearoa New Zealand (23 occurrences of ‘PE’ and 42 occurrences of ‘SciC’, with barely any references to other terms). However, in contrast to the other contributions, the author questioned the latest initiative of the Science Foundation Ireland (2018), which reduces ‘PE’ ‘to engagement with IP, industry, global researchers and markets, and funding stakeholders’ (Murphy 2020: 431), thus attesting de facto to the pervasiveness of ‘PE’ in the discourse and to its structuring effect (even though Murphy hints at a diversion of its original meaning).

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1.7 Conclusion The starting point of this work was an assessment of research in science culture, which concluded that ➀ the field remains heterogeneous and multiform, and that that may very well be its fundamental structure. And it is for that reason that ➁ its research objects are hybrid, ➂ existing at the point of intersection and interaction of actors, discourses and practices, with ➃ a plurality of terms attempting to simultaneously qualify practices and characterize the objects constructed to understand them. The first draft of 37 contributions from as many countries—a worldwide survey of the state of ‘science communication’—constituted the corpus for a quantitative and qualitative content analysis of the terms used by the authors. The results show, within the limits of the corpus, that ➄ the authors construct their discourses around a number of terms, which in their overwhelming majority they never define. In other words, the terms are polysemic because they are imprecise, increasing the ambiguity of statements and contributing to the plurivocity of discourses. However, ➅ the authors, with a few exceptions, chose a number of terms above others. And yet, ➆ the preferred use of a term by a given author is only meaningful in relation to its degree of penetration of the field (that is, the number of authors who use it). The analysis distinguished ➇ between three groups of terms, organized according to their degree of penetration: least mentioned, moderately mentioned and most mentioned terms. The third part of the research focused on the most mentioned terms for a given category, and therefore for a given author, and revealed that ➈ they are overwhelmingly implicit anchoring points of meaning. And it is this implicit relation that is of importance, since the preferred use of one or more terms, regardless of their degree of penetration of the field, and therefore the probability of their use, ➉ points to their being accounted for by factors other than theoretical ones: ‘these expressions … are at the same time products of the national contexts in which they were coined and of the political (and cultural) preoccupations of the moment. Each of these expressions entails overlapping but nonetheless different activities that must similarly be evaluated according to related but different approaches. Far from being in contradiction, though they may be at some level, they are essentially complementary, although they might not be pursued at the same moment of historical development and are framed by the political [and cultural] preoccupations of the moment’ (Schiele 2015). In other words, notwithstanding discussions on whether science communication is an emerging discipline (Trench and Bucchi 2010), the very heteronomy of the discourses that underpin those attempts negates that endeavour. And, as Habermas (1990) previously argued in regard to science’s image of neutrality and objectivity, it would be more accurate to portray science, its objects and methods as overdetermined by the very context it seeks to externalize, since the ideological scope of rationality, incarnated by science, rests upon that very externalization. The various lines of research today united under the term ‘science communication’ have not succeeded in erasing that context, which is reified in their research objects and discourses.

1 Communicating Science: Heterogeneous, Multiform and Polysemic

33

Our aim is not to question the autonomy of the disciplines used by researchers in ‘science communication’, since that would only muddy the distinction between internal and external factors. Let us simply say, about internal factors, that each discipline draws its own norms and exclusively falls under them (Ben-David 1997: 280). ‘External constraints, regardless of their nature[,] are mediatized by [their] own internal logic’ (Bourdieu 1997: 15). That being said, it is obvious that no discipline can escape its context and its constraints. And that interdependency is even more acute in our modernity, which is characterized by complex regimes of interactions between science, society, culture and politics. That fact is just now being rediscovered by a number of researchers in ‘science communication’, such as Marcinkowski and Kohring (2014), Gluckman (2016), and especially Fähnirch and Ruser (2019): when they write: ‘[T]aken together, these diverse interactions, interrelations and interdependencies create a heterogenous and complex patchwork.’ We can add that the will of a number of countries to favour a convergence between research and social issues can only strengthen that dynamic. In other words, the perspective is reversed: the object is no longer the impossible task of founding a discipline, either by isolating the science communication field from the other fields of knowledge or by extending it to everything, but rather to conceive of it as a body of research focusing on one aspect of the publicization of science. The recent concepts of ‘science participation’ or ‘citizen science’, and the research associated with them, which question the way knowledge is produced, exchanged and mobilized by actors, are forcing a re-examination of science–society relations (Schiele 2020; Hecker et al. 2018) and reframing the evolution of the field of science communication in that process. On the one hand, researchers fall for the most part under the purview of social sciences, as Mulder et al. (2008) have shown, and, on the other, they are ‘objectoriented’: ‘This type of research focuses, as implied by its name, to specific (nondisciplinary) objects around which the necessary expertise to answer the issues raised is assembled’ (Gingras 2004: 20). It is neither applied science nor an opposition between pure and applied research—an opposition that has lost its meaning in the new context of knowledge production, which is often accomplished directly in its area of application (see, among others, Prat Lopez et al. 2020; Spicer et al. 2020; Wilmoth et al. 2020). This simply means that the problems to solve involve moving beyond a purely disciplinary standpoint; that is, the issues do not emerge from an endogenous disciplinary dynamic but from external causes. Thus, for example, the assessment of the scientific knowledge of the public, of its attitudes towards science, and more globally of public–science relations, mobilizes researchers from various disciplines (statisticians, linguists and others), but not to solve problems caused by the development of those disciplines. The theoretical issues specific to each discipline increasingly find their solutions in the contexts of their application; that is, in a reversal of polarity. Bauer et al. (2007), after assessing 25 years of surveys, reached a similar conclusion: ‘[A]n inter-disciplinary field of inquiry like PUS might offer an opportunity to make significant contributions to other disciplines by developing existing methods with longitudinal perspectives’ (p. 90). They gave an example: ‘[T]he analysis of science

34

B. Schiele et al.

reportage in mass media yields long-term indicators of public salience and issue framing and might contribute to a dynamic theory of social representation, a social psychology theory that deals more generally with the transformation of knowledge across communities’ (p. 90). There are still fundamental theoretical issues to solve, but most contemporary research aligns with the dominant—yet situational—mode of public valorization of science. That is why it can be surmised that its main effect is to legitimate and strengthen that mode, lending weight to Habermas’s conclusion that the validity of knowledge, manifest in its application or scope, does not entail its objectivity to the extent that knowledge presents itself as self-evident in its aim to unmask the real, while staying silent on the social and political context that presides over its creation.

Appendix See Tables 1.7 and 1.8.

0

3

0

21

49

21

32

60

42

55

34

55

39

12

76

36

62

AU

BR

CA

CN

CO

DE

EE

ES

3

4

5

6

7

8

9

10 FR

11 GB

12 GH

13 IE

14 IL

15 IN

16 IR

17 IT

18 JM

19 JP

20 KR

21 MX

76

78

37

24

59

59

56

8

4

5

6

10

0

0

8

0

0

2

3

123

1

0

0

30

SP

2

21

1

SciC

Code

AR

R

1

7

11

0

5

2

5

13

23

0

0

0

3

3

5

0

5

1

5

1

1

PE

77

0

1

0

4

1

0

1

1

0

0

0

2

1

23

3

0

0

3

3

2

PC

0

0

3

8

1

4

9

0

5

0

1

0

0

1

1

1

1

1

0

8

1

PA

11

0

0

0

13

2

3

6

3

0

0

10

5

0

1

0

0

20

0

0

12

SC

2

0

0

1

2

3

2

11

3

0

7

3

0

2

10

9

6

1

4

1

2

PT

0

3

17

0

0

3

7

4

1

0

22

0

0

0

5

0

1

3

0

0

1

PUS

1

4

1

0

2

4

4

1

4

1

0

0

0

0

0

0

13

8

0

0

5

0

6

1

0

3

1

1

0

2

0

0

1

2

0

3

0

0

27

0

0

0

SL PCST

Denomination

Table 1.7 Occurrences, by countries in alphabetical order, and categories, in descending order

1

0

0

0

0

0

0

0

3

0

7

0

2

0

4

1

1

2

0

0

1

DS

0

0

0

0

3

1

3

2

1

0

0

4

0

0

0

0

3

0

0

2

1

SI

0

0

0

0

0

0

26

0

0

0

0

0

0

0

0

0

0

0

0

0

0

ST

1

0

0

0

0

0

1

0

0

0

0

1

0

0

0

0

0

0

0

0

0

EM

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

0

6

0

0

0

VS

0

0

0

0

0

0

0

0

0

0

0

5

0

0

2

0

0

0

0

0

0

SM

P %/SciC

(continued)

164 37.8%

77 46.8%

110 69.1%

25 48.0%

77 50.6%

82 67.1%

105 32.4%

96 57.3%

88 47.7%

61 98.4%

69 46.4%

54 38.9%

63 77.8%

83 91.6%

134 58.2%

54 68.5%

177 13.6%

129 45.7%

71 83.1%

71 78.9%

77 27.3%

1 Communicating Science: Heterogeneous, Multiform and Polysemic 35

68

47

28

42

74

22

33 TR

34 TW

35 UG

36 US

37 ZA

53

31 SG

32 TH

52

44

30 SC

49

28 PT

29 RU

17

10

45

25 NZ

26 PH

63

24 NL

27 PK

38

23 NG

SciC

50

Code

22 MY

R

Table 1.7 (continued)

0

0

0

5

0

10

0

1

14

0

10

1

0

0

4

0

SP

0 3

60

0

1

0

0

2

13

5

2

2

0

1

1

1

0

PC

3

5

0

7

9

13

1

10

1

1

11

29

4

8

5

PE

1

5

0

4

1

8

15

2

0

2

0

3

4

3

1

0

0

0

19

0

1

2

4

1

0

0

0

SC

23

3

0

2

15

PA

2

1

3

4

5

1

1

5

0

7

0

1

2

2

0

1

PT

0

3

1

0

0

1

0

0

1

5

0

2

1

0

0

2

PUS

1

1

0

4

1

2

5

0

1

4

0

1

0

0

2

2

0

0

0

0

1

0

0

2

0

0

0

0

2

2

1

0

SL PCST

Denomination

0

5

0

1

0

0

0

10

0

1

0

0

0

6

0

0

DS

2

0

0

0

3

0

0

0

0

1

0

1

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

ST

15

1

SI

1

10

0

0

0

2

0

1

0

0

0

0

1

0

0

0

EM

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

VS

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

SM

P %/SciC

(continued)

98 22.4%

97 76.3%

58 72.4%

48 58.3%

75 62.7%

109 62.4%

76 69.7%

77 57.1%

84 61.9%

90 54.4%

46 21.7%

40 42.5%

85 52.9%

93 67.7%

57 66.7%

76 65.8%

36 B. Schiele et al.

1685

269

8.7%

258

8.4%

129 4.2%

153

5.0%

121 3.9%

104 3.4%

83 2.7%

72 2.3%

55 1.8%

45 1.5%

44 1.4%

26 0.8%

18 0.6%

7 0.2%

7

4.7%

9.3%

SciC = science communication; SP = science popularization; PE = public engagement; PC = public communication; PA = public awareness; SC = scientific culture; PT = public participation; PUS = public understanding of science; SL = science literacy; PCST = public communication of science and technology; DS = democratization of science; SI = scientific information; ST = scientific temper; EM = empowerment; VS = vulgarization; SM = scientific mediation Notes Column 1: line numbering Column 2: international coding (see Table 1.1) Columns 3–18: ‘SciC’ to ‘SM’: distribution, by categories Column 19: P: total number of occurrences, by countries Column 20: %/SciC: percentage of occurrences of ‘SciC’, by countries Line 30: ‘SC’ is an acronym created to refer to Scandinavia (Denmark, Norway and Sweden) Line 38: n: total of occurrences, by categories Line 39: %/n: percentage of one occurrence across countries; highlighted values show the maximum number of occurrences for any given category and country Line 40: %/Oc: percentage of the maximum number of occurrences (highlighted in grey) for a given category of the total number of occurrences Line 41: %/OcP: percentage of the maximum number of occurrences (highlighted in grey) for a given category of the total number of occurrences for a given country

7.3% 20.9% 13.0% 16.1% 24.8% 10.3%

3076 54.8%

0.2% 100.0%

4.6% 45.7% 23.3% 50.3% 17.8% 16.5% 10.6% 26.5% 18.1% 49.1% 22.2% 34.1% 100.0% 55.6% 85.7% 71.4%

54.8%

41 %/OcP 58.2% 69.5% 61.2% 47.0% 50.0% 15.5% 11.5% 31.9%

40 %/Oc

39 %/n

38 n

Table 1.7 (continued)

1 Communicating Science: Heterogeneous, Multiform and Polysemic 37

SG

KR

ES

CO

AU

PK

GB

EE

JM

BR

GH

Code

PT

4

SP

4

PT

2

PT

7

SP

10

PC

3

PE

5

PA

8

PE

3

PUS

22

SciC

10

PA

59

SciC

12

SciC

76

SciC

32

PA

23

SciC

13

53

7

21

SP

SciC

PE

5

49

36

SC

SciC

SciC

PE

9

37

5

SL

3

PE

3

SP

8

PT

56

SciC

2

PC

6

PCST

2

PC

3

PC

2

SI

2

PC

7

DS

1

PC

1

PT

3

PC

0

SciC

PE

0

1

60

SP

SL

SciC

0 SC

0 SP

0

2

PA

4

SL

2

PCST

1

PA

1

PE

1

PE

1

PA

1

PA

0

1

PT

3

PUS

2

DS

1

DS

1

PT

0

PA 0

SP 0 0 SC 0

0 SP 0

PA

0

0

PC

0 SC

0 PE

0 SC

0 SP

0 PUS

0 PT

0

PC

0

PUS

0

PUS

0

PUS

0

PT

SC

0 PE

0 SP

SC

0 PC

SC

0

PA

SP

0

SC

0 0

0

0

PUS

0

PCST

0

PT

SC 0

0

PUS

0

0

PT

0

SL

0 PUS

SL

0

PCST

PUS

0

SL

SL

0

SC

0

0 PCST

0 SL

0 PCST

0

PCST

0

PCST

SL

SL

0

PUS

Denomination

PE

0

PA

0

PC

Table 1.8 Order of categories, by occurrence of terms, by countries

0

DS

0

DS

0

SL

0

PCST

0

PCST

0

DS

0

PCST

0

DS

0

DS

0

DS

0

DS

0

SI

0

SI

0

SI

0

SI

0

DS

0

SI

0

SI

0

SI

0

SI

0

SI

0

SI

0

ST

0

ST

0

ST

0

ST

0

ST

0

ST

0

ST

0

ST

0

ST

0

ST

0

ST

0

EM

0

EM

0

EM

0

EM

0

EM

0

EM

0

EM

0

EM

0

EM

0

EM

0

EM

0

VS

0

VS

0

VS

0

VS

0

VS

0

VS

0

VS

0

VS

0

VS

0

VS

0

VS

0

SM

0

SM

0

SM

0

SM

0

SM

0

SM

0

SM

0

SM

0

SM

0

SM

0

SM

(continued)

76

77

63

54

71

46

69

83

25

71

61

n

38 B. Schiele et al.

CN

TW

TR

SC

NG

US

RU

NL

MY

JP

UG

Code

5

SciC

24

123

SP

SciC

28

8

47

SP

PA

SciC

4

10

PE

74

SciC

13

5

SP

14

EM

52

SciC

44

10

DS

15

SP

63

SciC

8

6

PE

SI

PC

5

DS

15

50

SciC

38

11

PE

17

PA

76

SciC

SciC

PE

PUS

SciC

PT 6

13

4

PT

5

SL

4

SC

7

PT

5

10

PE

PT

2

PA

3

PE

5

PC

4

PE

2

PUS

3

PA

3

SC

DS

4

5

42

PA

PE

SciC

Table 1.8 (continued)

5

PE

4

SL

3

SC

2

PCST

2

SL

3

PUS

1

PA

2

PT

2

SL

1

PC

3

PT

3

SI

1

PC

3

SI

1

SP

1

PC

1

PT

1

PUS

2

PCST

1

PT

1

SL

1

PUS

1

PA

1

PA

1

SL

1

PE

1

PCST

1

SL

1

SL

1

PC

1

SI

1

PCST

0

SP

1

PUS

1

DS

1

PCST

1

EM

1

SI

0

1

0

0 SC

0 PC

0 DS

0

PCST

PUS

PE

0

PUS 0

PC

SP

0

PUS

0

PUS

0

SC

0

DS

0

PUS

0

PCST

0

DS

0

DS

0

0

0 SC

0 PA 0

0 PT

0

PA

0

PCST

0

SC

0

SC

SC

0 PC

0 SP 0

0 PT

0 SC

0 PA

0 SP

0 PC

0

SC

SP SP

0

0 PT

PCST

SL

0

PC

Denomination

0

PCST

0

SI

0

DS

0

SL

0

DS

0

PCST

0

SI

0

SL

0

DS

0

ST

0

ST

0

ST

0

SI

0

ST

0

SI

0

ST

0

ST

0

ST

0

ST

SI 0

0

ST

0

SI

0

EM

0

EM

0

EM

0

ST

0

EM

0

ST

0

EM

0

0

VS

0

VS

0

VS

0

VS

0

VS

0

VS

0

VS

0

0 VS

0

VS

0

VS

0

VS

EM

EM

0

EM

0

EM

0

SM

0

SM

0

SM

0

SM

0

SM

0

SM

0

SM

0

SM

0

SM

0

SM

0

SM

(continued)

177

48

75

77

57

97

84

93

76

110

58

n

1 Communicating Science: Heterogeneous, Multiform and Polysemic 39

DE

CA

AR

PT

IT

ZA

TH

PH

NZ

MX

IL

FR

Code

23

78

20

27

PC

PCST

SciC

59

21

30

SciC

SC

SciC

SP

5

10

PT

12

SC

7

PT

19

5

SP

22

SC

60

SciC

49

10

PA

15

SciC

68

PE

13

4

SP

11

PA

17

SciC

SC

3

PA

29

PE

45

SciC

39

11

PA

62

PE

77

SciC

SciC

6

11

SC

13

SciC

55

PC

5

PE

8

SL

5

SL

5

PUS

5

PE

3

PC

9

PE

2

SC

2

PT

8

SP

5

SC

8

PT

10

PE

21

SciC

SM

SP

SC

SciC

Table 1.8 (continued)

5

PUS

6

VS

2

PC

4

SL

4

PC

2

SC

2

SL

2

PUS

2

PCST

2

PT

4

PUS

4

SI

4

DS

3

PUS

2

PT

2

PC

3

PCST

2

PT

2

EM

1

SP

1

PC

1

PE

3

SP

3

PT 1

3

PCST

2

DS

1

PE

1

PE

3

SI

2

SI

1

SC

1

PT

1

SC

1

SL

2

SI

2

SP

1

SP

1

PA

1

PA

2

PT

1

SL

1

PT

1

SL

1

PUS

1

DS

1

PC

1

EM

1

SL

1

VS

2

SM

1

PE

1

PUS

1

DS

2

SL

1

EM

1

PUS

1

SI

1

EM

1

EM

Denomination PCST

1

1

PA

1

PA

1

DS

1

SI

0

0

0 ST

0 PCST

0

1

SC

1

PT

1

0

0

SL

0

SI

0

SI

PC 0

0

0

ST

0 PCST

ST

0

DS

0

SI

0

ST

0

0

ST

0

ST

0

EM

0

EM

0

EM

0

ST

0

ST

0

EM

0

0 ST

0

0

SI

0 ST

SI

SI

EM

0 ST

SL

PUS

SP

0 DS

0

PCST

0

DS

0

DS

0

DS

0

PCST

0

DS

0

PA

PUS

0 PA

0 PUS

0 SP

0 PCST

0 PC

0 PCST

0 PC

0 SL

0 SP

0 PUS

0 PA

0 PCST

0

PC

PA

PE

0

EM

0

EM

0

VS

0

VS

0

VS

0

VS

0

VS

0

VS

0

VS

0

VS

0

VS

0

DS

0

VS

0

SM

0

SM

0

SM

0

SM

0

SM

0

SM

0

SM

0

SM

0

SM

0

SM

0

ST

(continued)

134

129

77

90

77

98

109

40

85

164

96

54

n

40 B. Schiele et al.

26

34

4

6

ST

55

SciC

PA

SP

SciC

10

SP

5

23

42

PA

PE

SciC

9

PA

4

SL

4

SL

7

PUS

3

PT

3

SC

5

PE

3

PUS

3

PT

4

SL

2

PE

3

DS

3

SC

2

SC

2

PCST

Denomination

3

SI

1

PC

1

PC

2

PT

1

PCST

1

PUS

1

PCST

1

SI

1

SI

1

EM

0

DS

0

SP

0

PC

0

ST

0

ST

0

DS

0

EM

0

EM

0

VS

0

VS

0

VS

0

SM

0

SM

0

SM

105

82

88

n

DS = democratization of science, EM = empowerment, PA = public awareness, PC = public communication, PCST = public communication of science and technology, PE = public engagement, PT = public participation, PUS = public understanding of science, SC = scientific culture, SciC = science communication, SI = scientific information, SL = science literacy, SM = scientific mediation, SP = science popularization, ST = scientific temper, VS = vulgarization Notes Highlight indicates at least one occurrence in a given category, gray its absence Column 1: international coding (see Table 1.1)

IN

IR

IE

Code

Table 1.8 (continued)

1 Communicating Science: Heterogeneous, Multiform and Polysemic 41

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Snow CP ([1959] 1961) The two cultures and the scientific revolution. Cambridge University Press, New York Spicer H, Nadolny D, Fraser E (2020) Going squirrelly: evaluating educational outcomes of a curriculum-aligned citizen science investigation of non-native squirrels. Citizen Science: Theory and Practice 5(1):1–13. https://doi.org/10.5334/cstp.275 Stilgoe J, Lock SJ, Wildson J (2014) Why should we promote public engagement with science? Public Underst Sci 23(1):4–15 Trench B, Bucchi M (2010) Science communication, an emerging discipline. JCOM 9(3). https:// doi.org/10.22323/2.09030303 Weaver W (1951) AAAS policy. Science, new series, 2 November, 114(2966):471–472 Watanabe M, Kudo M (2020) Japan—Western science and Japanese culture. In: Gascoigne T, Schiele B, Leach J, Riedlinger M, Lewenstein BV, Massarani L, Broks P (eds) Communicating science. A global perspective. Australian National University Press, Canberra, pp 521–538 Wilmoth E, Dumke J, Hueffmejer R (2020) Could a harvest-based citizen science program be an effective contribution to fisheries research? Citizen Science: Theory and Practice 5(1):1–11. https://doi.org/10.5334/cstp.301 Yin L, Li H (2020) China, science popularisation on the road forever. In: Gascoigne T, Schiele B, Leach J, Riedlinger M, Lewenstein BV, Massarani L, Broks P (eds) Communicating science. A global perspective. Australian National University Press, Canberra, pp 205–226

Bernard Schiele is a Professor of Communications in the Faculty of Communication at the University of Quebec at Montreal (Canada). At present, he is the co-editor-in-chief, with Ren Fujun (NAIS), of the new journal Cultures of Science. He is also a founding and current member of the Scientific Committee of the PCST network. He chaired the International Scientific Advisory Committee for the New China Science and Technology Museum (2006–2009). He was a member of the Expert Panel on the State of Canada’s Science Culture (2013–2014), which published Science culture: where Canada stands (Council of Canadian Academies, 2014). Among other books he has recently published as a co-editor are Musées, Mutations [Museums, Mutations] (OCIM, 2019) and, with Toss Gascoigne and other scholars, Communicating science. A global perspective (ANU Press, 2020). He is the recipient of the ICOM–Canada International Achievement Award (2012). Toss Gascoigne is a visiting fellow at the Centre for the Public Awareness of Science at the Australian National University. He has published on science advocacy, on whether science communication is a discipline, and on setting up ‘Science meets Parliament’. He recently edited a major work documenting modern science communication in 39 countries (Communicating science. A global perspective, ANU Press, 2020). He was elected inaugural president of the Network for the Public Understanding of Science and Technology in 2008 and worked to transform PCST into a body with a full international reach. Toss is a life member of both Australian Science Communicators and the PCST Network. Over the past 28 years, he has run 1,800 training workshops for scientists in Australia and 20 other countries. The workshops have focused on science communication and how to explain complex concepts to different audiences. Alexandre Schiele is a postdoctoral researcher at the Hebrew University of Jerusalem, Israel. He holds a PhD in communication science (Sorbonne Paris Cité, 2017) and another in political science (University of Quebec at Montreal, 2018). He pursues his research in two distinct directions. On the one hand, he studies science communication in the media, and has contributed to the Mapping the New Communication Landscape in Canada project (2017–2018). On the other hand, he studies classical and contemporary Chinese political thought. Among his latest publications, of note is Pseudoscience as media effect (2020).

Chapter 2

Citizen Science as Participatory Science Communication Per Hetland

Abstract Over the past 20 years, citizen science has been understood as either democratized citizen science or contributory citizen science. This chapter argues for a third understanding: citizen science as participatory science communication. Participatory science communication moves the focus of citizen science from doing science, be it either democratized or contributory, towards communicating science, whether the purpose is to achieve scientific aims, to contribute to environmental protection or to map activities. Participatory science communication is part of a larger participatory turn illustrated by concepts such as Science 2.0. It is on the one hand based on participatory processes, and on the other hand on knowledge infrastructures, media and interpersonal communication. Dialogue is facilitated among different stakeholders on a common science communication problem or goal, such as biodiversity mapping. Participants learn, with the objective of developing and implementing a set of activities to contribute with observations and validation activities and by co-producing meta-content, and the infrastructure evolves and supports that objective. Keywords Participatory science communication · Citizen science · Access · Interaction · Participation

2.1 Introduction Citizen science (CS) as participatory science communication (Metcalfe et al. 2008) moves the focus of CS from doing science or emancipating the pursuit of science, be it either contributory CS (Bonney 1996) or democratized CS (Irwin 1995), towards communicating science either to achieve scientific aims, to contribute to science policy or environmental governance or for other purposes. This is important, since many participate in CS activities not primarily to contribute to scientific aims (Hetland

P. Hetland (B) Department of Education, University of Oslo, Oslo, Norway e-mail: [email protected] © China Science and Technology Press 2021 B. Schiele et al. (eds.), Science Cultures in a Diverse World: Knowing, Sharing, Caring, https://doi.org/10.1007/978-981-16-5379-7_2

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P. Hetland

2020a). Participatory science communication (PSC) is part of a larger participatory turn, often characterized by concepts such as Science 2.0 (Shneiderman 2008; Waldrop 2008), Mode 2 (Gibbons et al. 1994; Nowotny et al. 2001) or Triple Helix (Leydesdorff and Etzkowitz 1998). I will claim that, while the traditionally one-way science communication models are closely linked to Science 1.0, PSC is closely linked to Science 2.0. PSC bridges the instrumentalist point of view (collect, participate and contribute) and the capacity-building point of view (openness, inclusiveness, responsiveness, democratic engagement, consultation, dialogue and commons) (Ceccaroni et al. 2017). This chapter highlights the interplay between both the science end and the citizens’ end of the fast-growing research field of CS. A colleague and I have earlier studied how the concepts we use to describe citizens’ activities undergo a processual development from access (transmission) through interaction (negotiation) to participation (empowerment) (Hetland and Schrøder 2020). Consequently, access, interaction and participation (the AIP model; Carpentier 2012, 2015) are central to understanding PSC.

2.2 Contextualizing Participatory Science Communication In studies of CS, three classification schemes organized around different features are often referred to: • the nature of the activities that participants engage in (Bonney et al. 2016) • the extent to which different publics participate in parts of the scientific process (Shirk et al. 2012) • the level of participation between professional scientists and amateurs (Haklay 2018). Consequently, there are a number of different definitions of CS. Ceccaroni et al. (2017:10) provide one definition that aims to bridge contributory and democratized CS: Citizen science is work undertaken by civic educators together with citizen communities to advance science, foster a broad scientific mentality, and/or encourage democratic engagement, which allows society to deal rationally with complex modern problems. Shared knowledge infrastructure fosters shared ontological commitments that distinguish the participants as a broad citizen-science community of practice (Ceccaroni et al. 2017). The quest for dialogue and participation stems from two interrelated discourses: the first concerns public understanding of science, and the second is based on the discourse on the new production of knowledge. Certainly, participation is something more than the rather loosely defined concept used in everyday language. I propose the following definition of PSC (Hetland 2020a:274–275): Participatory science communication is based on the one hand on participatory processes, and on the other hand on knowledge infrastructures, media and interpersonal communication. Dialogue is facilitated among different stakeholders, around

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a common science communication problem or goal, as well as local problems and goals. Participants learn, with the objective of developing and implementing a set of activities to contribute to a solution, or realization, and the infrastructure supports and accompanies this objective. Boundary or knowledge infrastructures represent ‘regimes and networks of boundary objects (and not unitary, well-defined objects) [They] have sufficient play to allow for local variation together with sufficient consistent structure to allow for the full array of bureaucratic tools (forms, statistics, and so forth) to be applied’ (Bowker and Star 1999:313–314) and thereby facilitate the cooperation of scientists, amateurs and civil servants across disciplines and organizational boundaries. CS and Science 2.0 become a manifestation of scientific culture articulated in the face of new technology (Hine 2008:34). Bowker argued that this layering of boundary objects creates a form of irreversibility or path dependency in the infrastructure for two reasons: ‘first because the infrastructure is performative; and second because the infrastructure is diffuse’ (Bowker 2000:648). Boundary work occurs when people contend for, legitimize or challenge the cognitive authority of those who control the knowledge production—and the credibility, prestige, power and material resources that attend such a privileged position (Gieryn 1995). To analyse PSC, I will use the access, interaction and participation model (Carpentier 2012, 2015) and focus my study on the Species Observation (SO) system in Norway. Access, interaction and participation have developed into important concepts describing how and which spaces citizens access, how citizens interact with each other socially and communicatively, and how we think about participation (Carpentier 2012, 2015). Carpentier claimed that ‘access becomes articulated as presence, in a variety of ways that are related to four areas: technology, content, people and organizations’ (2012:173), while interaction ‘has a long history in sociological theory, where it often refers to the establishment of socio-communicative relationships’ (2012:174). Finally, the ‘difference between participation on the one hand and access and interaction on the other is located within the key role that is attributed to power, and to equal(ized) power relations in decision-making processes’ (2012:174). First, access through well-functioning knowledge infrastructures is a precondition for joining the ranks of recorders, contributors, validators and institutional actors. Interesting content is necessary to maintain the interest of all relevant actors. One important aim is to motivate as many people as possible to participate, taking part in both dyadic and polyadic dialogues. Organizations participating in environmental governance are important as drivers. That includes academic institutions, the Global Biodiversity Information Facility (GBIF) and the amateur societies, which argue strongly for a service such as the SO system using the very successful Swedish species observation system, Artportalen, as a promising exemplar. Interaction is the second foundation stone of participation. Over time, the technology opens up for a growing number of species groups. The primary content added may also be used to produce secondary content such as private diaries, ranking lists, maps and so on. The movement in science from the field to the laboratory widens the gap between people, whether they are professional scientists or amateur naturalists. The concept ‘amateur’ has its roots in Latin (amator: lover) and is used here for people

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practising an activity without using it to earn a livelihood, even if some are highly skilled people holding science degrees. Nonetheless, amateur naturalists continue to contribute much local knowledge. Organizations are crucial to maintaining the general principles that the SO system has established. Participation signifies democratized CS. The choice of technology involves important dimensions of power, as technology structures actions. Most amateur naturalists understand that they are participating in a huge communal undertaking producing new content and at the same time being crucial actors promoting environmental governance. The quality of the content rests on their ability to avoid skewing and to collect well-validated data. However, the ability to build and sustain the infrastructure also illustrates that participation is organizational power, enacted both from the bottom up and from the top down. In my concluding discussion, I use Carpentier’s AIP model (2012, 2015) to explore PSC (see Table 2.1). In the following sections I first present method, then results, and finally the concluding discussion. Presenting the results, I deviate somewhat from the traditional approach and also introduce some relevant literature of a more empirical or conceptual nature.

2.3 Method This chapter builds on five case studies of citizen-science activities carried out by the author and colleagues: (A)

(B)

(C)

On behalf of the University Museums Commission, appointed by the Norwegian Ministry of Education and Research, a colleague and I evaluated university museums’ work in digitalizing their collections. Fifty people were interviewed, some of them several times. About half of them worked in natural history, while the other half worked in cultural history. More detailed references to the empirical material are given in Hetland and Borgen (2005). Later, in 2010, I did follow-up interviews with crucial actors within natural history at the GBIF both in Norway and at the international GBIF Secretariat at the Natural History Museum in Copenhagen, the Norwegian Biodiversity Network (Sabima) and the Norwegian Biodiversity Information Centre (NBIC). The follow-up interviews were selected to study critical issues in the process of building the new knowledge infrastructure, SO, which began operating in 2008 (Hetland 2011). Seventeen research scientists at two natural history research museums in Norway were interviewed about their public outreach activities, focusing on practices, settings, designated outcomes, scientists’ incentives to communicate science, and, finally, the speaking positions available for the different publics. The aim was to provide an understanding of the four constructed publics in museums’ science communication: the general public, the pure public, the affected public and the partisan public (Hetland 2019).

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(E)

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A web-based survey was developed in collaboration with the NBIC, Sabima and the Natural History Museum of the University of Oslo. The survey was posted on the SO website and consisted of 19 questions, of which seven were close-ended, eight were close-ended with an option for comments, and four were open-ended. In total, 404 respondents completed the survey within the deadline. In total, the respondents provided 1129 qualitative comments (Hetland 2020a). Finally, a study of biodiversity mapping used semi-structured interviews with participants to discuss CS access, interaction and participation as well as the ethnography of online communities (Hetland and Mørch 2016). We studied dialogues on SO and on Facebook pages belonging to different groups of amateur naturalists to understand how controversial issues such as, for example, validation and collecting and preserving specimens have been handled (Hetland 2020b). Eight very active amateur naturalists or ‘super users’ and four professional biologists were selected for this last part. The eight super users were recruited from three amateur societies: the Norwegian Entomological Society, the Norwegian Botanical Association and the Norwegian Ornithological Society.1 Of the four professional biologists, two were from Sabima, one was from GBIF–Norway2 and one was from the NBIC. As super users, all of the interviewees were acting as civic educators in collaboration with citizen communities. The semi-structured interviews explored three main topics: access, interaction and participation.

Consequently, PSC communication has been followed over more than 15 years and several aspects have been studied, before the new knowledge infrastructure was established, shortly afterward and 10 years after its establishment. In this chapter, the data presented is from the four case studies; however, more specific references to the particular studies are not included in the text. More exact references will be given to readers who request them.

2.4 Participatory Science Communication PSC has been described and studied using the AIP model and highlighting the interplay between the science end and the citizens’ end of the fast-growing research field of CS (Table 2.1). Consequently, the table emphasizes the communication element between what is traditionally understood as Science 1.0 and that part of Science 2.0 emphasizing popular participation, both of which elements are crucial for developing PSC.

1 2

The members of these three societies are among the most active on the SO portal (Hetland 2020a). GBIF–Norway, https://www.gbif.no/.

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Table 2.1 Participatory science communication: access, interaction, and participation Technology

Content

People

Organizations

Access (Presence) Production

Science-driven databases and GBIF ↑↓ New knowledge infrastructures (SO)

About 10 million digitalized records ↑↓ About 24 million observation records

Professional scientists and collectors ↑↓ 12,000 contributors and 160 validators

Academic institutions and GBIF ↑↓ NBIC, Sabima and five amateur societies

Reception

‘My museum’ or ‘my scientists’ ↑↓ Design of new infrastructures

Morphological and molecular traditions ↑↓ Morphological tradition

Dyadic dialogues ↑↓ Polyadic dialogues

‘My collections’ ↑↓ ‘My observations’

Production

Natural history mapping ↑↓ Mapping 11 predefined species groups

Field notes, validation of the scientific collections ↑↓ Field notes, validation of species observations

Scientists and affected publics ↑↓ Reciprocity and long-term engagement

Thesauruses, type specimens, synonyms ↑↓ Co-producing meta-content

Reception

Following recording activities ↑↓ Identifying biodiversity and ‘white spots’

Prioritized national mapping activities ↑↓ ‘Projects within the project’ as private diaries, local floras

Dialogues with affected publics ↑↓ Facebook pages for affected publics

Open validation (apomediation) ↑↓ Pre-validation of data before registration

Co-deciding on/with people (e.g. the five principles of participation, inclusion/ exclusion)

Co-deciding on/with organizational policy (e.g. conducting environmental citizenship)

Interaction (Socio-communicative relationships)

Participation (Co-deciding) Production (and reception)

Lobbying for a new knowledge infrastructure. Participating in new versions of the infrastructure

Adapted from Carpentier (2015:22)

Co-deciding on/with content (e.g. the temporality of knowledge, the challenge of validation)

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2.4.1 Access According to Carpentier (2012, 2015), access is understood as presence, for example in an organizational structure or a community, related to four areas: technology, content, people and organizations. Natural history research museums represent a social technology that has both a front stage addressing different publics and a backstage holding large collections, most of which is not accessible to the same publics. This archival role of natural history research museums in Norway has been essential for production in the form of a vast range of research in the past 200 years. Amateur naturalists have played an essential role in supplying the natural history collections with new items. For example, the vascular plant collection at the Natural History Museum in Oslo receives some 10,000 new objects each year, of which 7000 come from amateur naturalists. If the collectors felt that the museum took ‘ownership’ of their objects and forgot the origin, much of the motivation disappeared. Consequently, the amateur organizations worked to establish a common digital infrastructure, based on both the scientific collections and self-reported data, of which the amateur communities were the most important contributors. However, that was easier said than done, so in 2008 the SO was established, mostly including self-reported data from mostly amateur naturalists. This new knowledge infrastructure placed the collectors in a more visible role. The amateur naturalists found that their dependence on specific scientists or museums was now less important and that they could also influence the development of the new infrastructure both through personal engagement and through their own amateur societies. However, since Norway’s membership in the GBIF from 2004 and the establishment of the Norwegian node in the GBIF network (GBIF–Norway) from 2005, primary data on biological diversity from the Norwegian collections and observation databases is communicated for the benefit of mapping Norwegian biodiversity and the biodiversity sciences. Since 2008, researchers from Norway have contributed to more than 100 peer-reviewed articles citing GBIF use.3 Consequently, content is crucial, as well as access to that content. In 2020, the natural history collections had roughly 10 million digitalized records. The contents of the collections were originally not digitalized and often difficult to access. In the 1970s and 1980s, some pioneers started to digitalize parts of the collections, often driven by specific research interests. They usually started with the researcher assessing what they needed in their work, and then that was used as a basis for building a database. Historically, this way of thinking is based on a tradition in which the individual scientist had a very personal relationship with the collections or, as one of the informants, said: “The reason why individuals created databases was to get an overview of their own collections. You may want to put a line under your own: ‘It’s my collection and I need to know what’s in it so I can answer others who want to know what I have.”’. That line of thinking is nowadays regarded as somewhat 3

Global Biodiversity Information Facility (GBIF), Activity report: Norway, January 2021, https:// www.gbif.org/sites/default/files/gbif_analytics/country/NO/GBIF_CountryReport_NO.pdf.

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old-fashioned, but it had the consequence that the first databases were largely purely research focused. The SO database had a different primary aim: to include as many entries as possible in an urgent mapping activity. It was urgent because biodiversity loss was high on the agenda. In 2020, the observation records in the SO included 11 species groups, as defined by the SO: vascular plants; mosses; lichens; algae; fungi; invertebrates; birds; amphibians and reptiles; mammals (excluding bats); bats; and fish. More than 24 million records in 12 years from about 12,000 contributors imply two crucial challenges: how to validate so many records in such a short time, and how to avoid skewing. Validation is partly organized by the NBIC and partly by amateur naturalists themselves. Sabima recruits volunteers to validate species of national observance interest.4 In addition to the organized validation, many observers take different kinds of actions to validate their own observations by using the resources made available by SO, by using one of the Facebook pages that have been established to assist amateur naturalists before publishing, by simply asking friends and colleagues or by using many of the traditional handbooks available. Increasingly, social media make it possible to move from dialogues between one amateur naturalist and one scientist to more polyadic dialogues including a number of voices. The polyadic dialogues also imply a shared ontological commitment that distinguishes the participants as a broad citizen-science community of practice (Ceccaroni et al. 2017). This may also be seen as a move towards new forms of apomediation (Eysenbach 2008), which can be understood as the ‘wisdom of the crowd’. The main purpose of the validation activities by amateur naturalists, scientists and civil servants is to ensure a high level of trust in the quality of the data, as distrust would be detrimental to environmental governance. As a new knowledge infrastructure, SO depends on collaboration between a number of organizations. First, the Natural History Museum at University of Oslo is one of the oldest organizations mapping Norwegian biodiversity. Being also the Norwegian node of the GBIF, the museum makes information from Norwegian collections and other sources available to the international GBIF network and coordinates GBIF-related activities in Norway. GBIF–Norway operates in close cooperation with the NBIC. Sabima was formed when nine NGOs organized themselves to lobby for improved environmental policies and education for its members.

2.4.2 Interaction According to Carpentier (2012, 2015), interaction is understood as a socialcommunicative relationship that is established with other humans or objects and is related to four areas: technology, content, people and organizations.

4

Sabima, https://www.sabima.no.

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According to the NBIC, about 44,000 different species are described for Norway, and there are at least an estimated 60,000 altogether.5 Only around 73% have been found and described. Sixty-five percent of those already found and described belong to the kingdom of Animalia, and insects are the largest group within Animalia. A number of species are threatened by loss of habitat or other human activities, and at the same time species are moving and appearing in strange places. Among prioritized national mapping activities are the Red List and the Alien Species List. These risk assessments are periodically revised and provide an important tool for decisionmakers.6 Of all the observations recorded, 15.5% of the described species are now on the Norwegian Red List, and 1.2% are classified as invasive species on the Alien Species List. Within the inventories of mammals, birds, reptiles and amphibians, an estimated nine-tenths or more of existing species were known before 1950 (Kohler 2006:280–281), while the inventories of invertebrate groups are wildly uneven. Mapping is a technology that develops over time. More systematic mapping activities took off during the 1800s and involved a wide range of actors (Brenna 2011; Conniff 2011; Kohler 2006). Basically, there are two traditions within species mapping: unstructured and structured. Most amateur naturalists’ collecting is unstructured, as was most collecting done historically by scientists. Referring to North America, Kohler describes four periods of biodiversity mapping. The first, the Linnaean, covered roughly the second half of the eighteenth century. The second, the Humboldtian, was a period of rapid discovery from the 1830s to the 1850s. Those first two periods were marked by mapping those species that are ‘large, fierce, freakish, beautiful, edible, lovable, or dangerous’. They were collected using the catch-as-catch-can method (Kohler 2006:4–5). The third period was mainly between 1880 and 1930, involved what Kohler calls ‘survey’ collecting and was marked by collecting expeditions organized as scientific ventures, which mapped more species than had been mapped in the previous 200 years. Finally, in the present period of ‘project’ collecting, more targeted collecting tends to be ‘intensive, local, and focused on solving some particular problem’ (Kohler 2006:15). Therefore, when science became more professionalized, more structured collecting methods began to be used. More structured methods imply systematic collection across space and time and are crucial for describing how biodiversity develops within an ecological context. Both the scientific and observation databases contain material that has been collected in both ways, and most content in the observation databases is collected in an unstructured manner. However, the SO observation database also contains a number of local or private projects following species, places, or both, over time. Both the Red List and the Alien Species List are crucial collaborative mapping outcomes that affect environmental governance for amateur naturalists, scientists and civil servants.

5

‘Hvor mange arter finnes i Norge?’ [How many species are there in Norway?], Artsdatabanken, 6 April 2016, https://www.artsdatabanken.no/Pages/205713/Hvor_mange_arter_finnes_i. 6 ‘About Norwegian Biodiversity Information Centre, NBIC, 19 March 2014, https://www.biodiv ersity.no/Pages/135580/About_Norwegian_Biodiversity_Information_Centre?Key=1466165065.

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The SO facilitates the recording of 11 species groups at this time, while the scientific collections have no restrictions on mapping activity. Several of the scientists interviewed monitor recording activity in the system, and some record sightings in the system themselves, but usually not within species groups that they work with professionally. The amateur naturalists particularly enjoy identifying what they call ‘white spots’, which are places where a species has not been recorded before. Because the validation of content is critical, the scientific collections are validated by scientists, both when specimens are collected and when they are later used in research, when genomic information might be added. The records in the SO observation database are validated both systematically, focusing on species on the Red List or the Alien Species List, or by apomediation (the wisdom of the non-professional group: Facebook pages have been created for different species groups as amateur naturalists assist each other in validating observations). The first three periods of collecting, as defined by Kohler (2006), involved people collecting physical specimens, but the fourth has involved parallel collecting by amateurs who have more conservationist attitudes and are making self-reported observations and taking photographs or videos. This change has coincided with the establishment of the SO database. Individual amateur naturalists follow their own collection strategies, as well as participating in projects cataloguing local flora and fauna. Several types of people participate in the production of new knowledge. When interviewing scientists at two natural history museums, my colleagues and I found that many began their careers as amateur naturalists and considered that they should continue to nurture their relationship with amateurs. When communicating about science, scientists address four major constructions of the public: the general public, the pure public, the affected public and the partisan public (Braun and Schultz 2010; Hetland 2019). The general public is anonymous individuals; the pure public is specific people, often ‘naive’ citizens, as the subjects of education; the affected public is specific people, including experts with first-hand knowledge of a specific area; and the partisan public is interest groups with knowledge of the landscape of possible positions. The affected public, in the form of amateur naturalists and their organizations, has been very important in the SO production process. Its participation has been driven by reciprocity with the museums and the SO system, which has resulted in long-term engagement. According to Kohler, ‘the relevant actors are the middleclass people who attached values of learning and self-improvement to their leisure customs’ (Kohler 2006:49). Of those responding to our web survey in 2017, 78% were men. While 33% of the general population had higher education, the figure was 76% among the SO participants, and 45–66 was the most dominant age bracket. The more than 24 million records in the SO database come from more than 12,000 contributors. About 1% of the contributors have provided more than 40% of the records, while about 80% have contributed around 1% of the records. Most of those who answered the web survey are quite likely to be those who are most active and experienced in using the SO system. We found that participants’ involvement was driven equally by the desire

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for individual and collective outcomes. Furthermore, 37% of respondents focus on uploading information, while 62% do more downloading. Scientists follow recording activities within their own field of specialization, while amateur naturalists record new observations and use the database to identify interesting new places to record. Organizations are crucial to facilitating such interactions. Academic institutions and their collaborators standardize names and species thesauruses, building on the original type specimens, and work with synonyms, as disused names are not allowed to be forgotten. At the same time, academic organizations are drivers behind the collection activities. Organizations of amateur naturalists participate in the production activities and facilitate both individual and organizational participation, coproducing meta-content. Crucial meta-content includes the Species Map, the Norwegian Red List, the Alien Species List and several other services. The amateur societies participate in validation work through the SO system or various Facebook pages. Validation is partly organized by Sabima and partly by amateur naturalists.

2.4.3 Participation According to Carpentier (2012, 2015) participation is defined by power relations in decision-making and is related to the four areas of technology, content, people and organizations. The SO is a collaborative technology, and some amateur naturalists find its openness problematic because some species might become vulnerable to hunting or collecting as a result of the system. Protecting information that relates to vulnerable species is a legitimate concern, but not everyone trusts that this is done in the right manner. At the same time, scientists need to protect data before research results are published. Content is temporary, which is why validation is a never-ending activity. That temporality is also heightened by the movement of much biodiversity mapping from the field to the laboratory. Floristic and faunistic knowledge is built on the morphological tradition stemming mostly from Carl Linnaeus (1707–1778), while twentiethcentury science is strongly linked to molecular biology that relies on knowledge of DNA. Amateur naturalists are still mostly dependent on morphology, while professional scientists work with new technologies and methods, potentially weakening knowledge about ecological contexts that is integral to traditional methods. Some amateur naturalists also participate in larger projects, such as the Barcode of Life Data Systems, which is based on DNA coding. As Kohler writes: ‘One could say that museum and herbarium specimens are enjoying a second, molecular scientific life. Molecular taxonomists are recapitulating the field collecting of past centuries, but without going afield: their expeditions are to museum storerooms’ (Kohler 2006:282). Validation activity was a topic that was most frequently discussed by the amateur naturalists whom we interviewed. All who participated in validation indicated that validation is a job that deserve payment, even if only symbolic payment. According to the NBIC, there is no reason to believe that the quality of the data in the SO is

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lower than that of data in the databases of professional research institutions. Many of the collaborative activities involving amateur naturalists, scientists and civil servants aim to ensure a high level of trust in the collected data. People have to follow some rules, as the SO is built on the following general principles:7 (A) (B) (C)

(D)

(E)

Everyone may contribute, regardless of their skills. Some records are always validated, such as the ones found on the Red List and the Alien Species List. In general, all records are open. However, for some vulnerable species, there are different ways of hiding some of the recorded information. The main idea is that openness in itself leads to protection. Validation is partly organized by the NBIC and partly by amateur naturalists themselves. Sabima recruits volunteers to validate species of national observance interest. Roughly 100 volunteers participate in the validation of birds, while 60 participate in the validation of the remaining species. They include both skilled amateur naturalists and professional biologists. The SO has an environmental and political impact through such services as the Species Map Service, the Red List and the Alien Species List.

Several of the validators find it frustrating that ‘hopeless people’ are allowed to mess around. While some few people are subject to certain restrictions, they are seldom expelled. According to the NBIC, fewer than 10 users have misused the system.8 Organizations are important actors for the SO. For example, Sabima was formed when nine NGOs organized themselves to lobby for improved environmental policies and education for its members. With more than 19,000 members, those NGOs include both the professional and most skilled amateur naturalists in Norway. Sabima and five amateur societies (the Norwegian Ornithological Society, the Norwegian Botanical Society, the Norwegian Foraging and Mycology Society, the Norwegian Zoological Society and the Norwegian Entomological Society) are collaborating partners with the SO. The NBIC is responsible for running the SO from day to day and has, as mentioned, organized validation with the help of national coordinators and several interactive services. The goal of the NBIC is to serve as a national source of information on species and ecosystems in Norway and to make up-to-date information on biodiversity widely available and easily accessible to society. Furthermore, the establishment of the GBIF connects Norwegian records with an increasing number of international records.

7

‘Grunnprinsipper’ [Basic principles], Artsobservasjoner [Species observations], 5 January 2021, https://www.artsobservasjoner.no/Home/Fundamentals. 8 ‘Håndtering av avvikende rapporter i Artsobservasjoner’ [Handling of deviating reports in Species Observations], Artsobservasjoner [Species observations], 5 January 2021, https://www.artsobservas joner.no/Home/DeviatingReports.

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2.5 Conclusion In Norway, the natural history research museum collections are the backbone of taxonomic and biogeographical research. Building on the work of a large number of people over the past 200 years, they are a unique window into biodiversity history. Amateur naturalists have played a crucial role in contributing to the collections. Since 2008, they have also contributed to the SO database in impressive numbers. Consequently, it is important to understand participation. Participation moves from access (transmission) through interaction (negotiation) to participation (empowerment). Each stage involves four areas: technology, content, people and organizations. Moving from Science 1.0 to Science 2.0, access is achieved through a new digital knowledge infrastructure, and that new infrastructure changes the position of amateur naturalists as well as scientists. Amateur naturalists now play a more independent role and are able to interact and participate independently from scientists. At the same time, the gatekeeping role of scientists has become less important, and dyadic dialogues have changed into polyadic dialogues involving a number of voices—amateur naturalists, civil servants and scientists. The analogue and digital activities are in many respects symbiotic, and consequently the working of the infrastructure is paramount for a well-functioning case of Science 2.0. Of course, this huge effort is marked by history and is consequently skewed in a number of ways, both geographically and in the selection of species mapped. That skewing is of course a problem when it comes to making a representative map of Norwegian biodiversity, but it seems that the new digital infrastructure is leading to less skewing over time. Some crucial elements sustain the infrastructure over time: • Most important is the fact that the collaborating partners include both private and public institutions with the necessary resources to prevent this from being a transient activity. • The infrastructure facilitates smaller projects within the larger project, and consequently makes collaboration possible even if the actors have different aims and ambitions. • The infrastructure facilitates co-deciding on both the individual level and the organizational level. To conclude, PSC is based on the one hand on participatory processes that include amateur naturalists and their organizations and scientists and scientific organizations, and on the other hand on boundary infrastructures, media and interpersonal communication. Dialogue is facilitated among different stakeholders around a common science communication problem or goal, as well as local problems and goals. Participants learn with the objective of developing and implementing a set of activities to contribute to a solution, or realization, and the infrastructure supports and accompanies that objective.

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Per Hetland is a full professor at the Department of Education, University of Oslo, Norway. His research interests include public communication of science and technology; the development, design and use of ICT; and science and technology policy studies.

Chapter 3

Science Communication on Offer by Research Institutes in Eight Countries Marta Entradas

Abstract In this chapter, I offer some observations on the evolving communication functions of research universities in eight countries. I report on the MOREPE: Mobilisation of Resources for Public Engagement with Science research project (2016–2020), which examined the public communication activity of institutes within research universities and large research institutions in Germany, the United Kingdom, the Netherlands, Portugal, Italy, the United States, Brazil and Japan. I call this the meso-level of the organizations, where the research action is located but for which we have little or no empirical data. I describe communications practices, target audiences and rationales for communication by research institutes with a focus on country comparisons and make use of the data to advance our understanding of how science communication is growing at the institute level across regions of the globe. Keywords Institutional science communication · Cross-national studies · Meso-level of public communication

3.1 Introduction The communication function of research universities has entered the literature on corporate and marketing communication (see, for example, Hallahan et al. 2007; Clark 1998; Schultz 1992). Yet, it has hitherto received little attention in the public understanding of science (PUS) or science communication literature (Schäfer and Fähnrich 2020). That is somewhat surprising. Academic institutions are at the heart of the science–society relationship: they provide the resources for public communication, define and reflect research priorities and set agendas for how relationships with stakeholders and wider publics are established. Also, public communication has become increasingly important for research institutions that are publicly funded: requirements for institutions to tackle society’s economic and social problems (see, for example, EC 2013; HLSCST 2000) and to

M. Entradas (B) ISCTE-IUL, Instituto Universitário de Lisboa, Lisbon, Portugal © China Science and Technology Press 2021 B. Schiele et al. (eds.), Science Cultures in a Diverse World: Knowing, Sharing, Caring, https://doi.org/10.1007/978-981-16-5379-7_3

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cultivate relationships with non-specialists, including industry, policymakers, civilsociety organizations and the general public (Gibbons 1995; EC 2007) have become part of research activity. That is certainly the case in the countries studied here, where national calls for public engagement come from various sides, including government, funding agencies and national evaluation systems of research ‘impact’ on society (see, for example, the Research Excellence Framework in the United Kingdom; Watermeyer 2016). This has put significant pressure on scientific institutions to disseminate and engage the public in their research and manage their communications strategies to address broad audiences. But we know little about how public engagement is taking place within this evolving scenario in research universities and institutions. The emergence of this new function of university management has influenced the way institutions address society, with structural implications at different levels of the organization: the central level (university), the meso-level (research institutes) and the micro-level (individual researchers). (A)

(B)

(C)

At the central level, public relations (PR)/marketing/communications offices, under various names (hereafter ‘central communications offices’) have become common at universities and large research institutions. How common remains unknown. Central communications offices carry out such functions as branding, advertising and media relations through contacts with journalists, blogging platforms and social networks, while also encompassing science communication through the production of press releases and event making. A handful of past studies have examined aspects of the communication function at the central level (Buhler et al. 2007; Peters 2012; Kallfass 2008; Marcinkowski et al. 2014; Elken et al. 2018; Koso 2021; Schwetje et al. 2020). At the meso-level of research units, centres or institutes within larger academic and research institutions, communication activities are growing, as research by Martin Bauer and me suggests (Entradas 2015; Entradas and Bauer 2017). This level of communication remains underresearched. Our benchmark study of the Portuguese research system was the first to map communication activities at the meso-level; here, I expand that study to investigate communications practices at the meso-level in other countries. At the individual level, many researchers and scientists are communicating their work outside academic institutions and have done so for a long time. The individual level of communication has received the most attention in the PUS literature, and a growing body of data has emerged in recent decades. Those studies point to an increasing sense of duty and levels of activity among scientists in many disciplines and countries, although only a minority are active communicators, while also identifying barriers to greater mobilization of scientists (Peters et al. 2008; Bauer and Jensen 2011; Entradas and Bauer 2019).

In this study, I focus on the meso-level. My main thesis is that, in addition to the central communication function of universities and communication by individual researchers, communication structures are growing at the level of research institutes (Entradas and Bauer 2018). Our preliminary study of research institutes in Portuguese

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universities was a pioneer in investigating science communication at this level in a single country (Entradas and Bauer 2017). The study reported emerging capacitybuilding measures for public communication of the institutes’ research activities, in which public events and media interactions are led independently from the central university PR offices and locally resourced. In 2018, I, Bauer and colleagues implemented the study in seven other countries as part of the MORE-PE project (Mobilisation of Resources for Public Engagement)1 to investigate whether similarities existed in other countries or whether those observations were relevant only for the Portuguese institutional system and science communication in that country (Entradas et al. 2020). Here, I show that those features are not a peculiarity of the Portuguese research system, but a trend across other countries with distinct traditions of public engagement in science (Mejlgaard et al. 2018; EC 2005), scientific systems and R&D resources (OECD 2014). Investigating different contexts allows for a broader understanding of this capacity-building in contexts of internationally increasing public engagement demands (NASEM 2017; Fischhoff 2013; Stocklmayer 2014). In what follows, I describe public communication activities, target audiences and the main rationales for the communication of research institutes in the eight surveyed countries. Those are all important indicators of growing activity at the meso-level. The selection and comparison of countries was driven by an interest in analysing similarities across the globe. We selected countries that have embraced public communication in their national agendas, but they vary in relation to PUS traditions and practices, which could affect the development of institutional public communication. We mapped factors that are known to be associated with public communication (Entradas et al. 2020) to investigate whether different countries have reached a similar stage of development in public communication; that is, one of growing activity at the institute level. Our aim was not to examine or identify cultural factors, but to focus on communication-related characteristics that are important for public communication and study how they vary across the surveyed countries.

1

The MORE-PE Project (Mobilisation of Resources for Public Engagement) (2016–2019) was funded by Fundação para a Ciência e Technologia (grant agreement PTDC/IVCCOM/0290/2014) and coordinated by Marta Entradas (principal investigator). National collaborators were Martin Bauer (UK), Giuseppe Pellegrini (Italy), Frank Marcinwoski (Germany), John Besley (US), Pedro Russo (Netherlands), Luisa Massarani (Brazil), Osako Okamura (Japan), Liu Xuan (China) and Yui-Yuh Li (Taiwan, China).

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3.2 Methods 3.2.1 Data The data came from an international online survey of 2030 research institutes in Brazil (n = 169), Germany (n = 358), Italy (n = 366), Japan (n = 321), the Netherlands (n = 142), Portugal (n = 224), the United Kingdom (n = 188), and the United States (n = 262). The overall response rate was 25%. We used stratified probability sampling to generate representative samples of the institute populations comparable across countries, accounting for areas of research. One questionnaire, in the national language, was collected per research institute and completed by staff members who could speak for the public communication of the institute, such as directors, communications staff and administrative staff (Entradas et al. 2020 for a full description of methods).

3.2.2 Measurements Public Communication Activities We asked institutes how frequently they had organized or used various types of communication to address non-specialists in the 12 months before the study. A rating scale from ‘never’ (0) to ‘weekly’ (4) was used for events and traditional media; and ‘never’ (0) to ‘daily’ (5) for new media channels.

Public Events Public events included public lectures; public exhibitions; open days; science festivals or fairs; science cafes or debates; citizen science; participatory events in policymaking; events with local stakeholders (industry); and talks at schools (nine items).

Traditional News Channels Traditional news media use included interviews for newspapers; interviews for radio; interviews for TV; press conferences; press releases; newsletters; articles in magazines or newspapers; and policy briefings (8 items). New media channels included website updates, Facebook, blogs, Twitter, YouTube and podcasts (6 items). For these activities, frequency scales were recoded into numbers of activities (counts of times per year). ‘never’ was recoded into 0 times, quarterly (4 times), monthly (12 times), weekly (48 times), and daily (240 times). Public events and

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traditional news media interactions ranged from 0 to 48 events, and social media interactions ranged between 0 and 240.

Public Audiences We measured the frequency of contact with eight non-peer audiences in the previous year on a four-point scale from ‘never’ (0) to ‘frequently’ (4) (Table 3.2).

Rationales We asked institutes about the importance of nine rationales for engaging with external audiences, using a five-point scale from ‘strongly disagree’ (1) to ‘strongly agree’ (5) (Table 3.3).

3.3 Analysis We used descriptive analysis and reported the estimated average number of public events, the use of traditional media channels and new media, and rationales for communication across countries. To comparatively access differences in levels of communication activity, we estimated one-way ANOVA models by country: three dependent variables measuring levels of activity (three separate indexes for public events, traditional media and new media channels). Reliability analysis showed high internal consistency for the three indexes (Cronbach’s α = 0.70 for public events, 0.85 for traditional news media and 0.71 for new media). For all comparisons, we consider χ2 p > 0.05.

3.4 What: Public Communication Profile of Activities Types of Activities Figures 3.1 and 3.2 show the total activity in public events and traditional media channels, by country; Fig. 3.3 shows the frequency of activity in social media. Overall, the format of activities carried out by institutes is similar across the surveyed countries. That is, institutes in the different countries engaged in the same types of activities, and activities that were more popular in one country were also more popular in the others.

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18 16

Estimated average number

14 12 10 8

6 4 2 0 Germany Public lectures

Italy Public exhibitions

Portugal Open days

Science festivals

Netherlands

United Kingdom

Science cafes/discussions

United States of America

Policy events

Brazil

Events w. business/industry

Japan School talks

Citizen science

Estimated average number

Fig. 3.1 Institutional public events, by country 12 10 8 6 4 2 0 Germany

Magazine articles

Italy

Press releases

Portugal

Newspaper interviews

Netherlands

Newsletters

UK

Brochures

USA

Radio interviews

Brazil

TV interviews

Japan

Press conferences

Fig. 3.2 Traditional media channels, by country

Fig. 3.3 Frequency of social media channel use, by country

Public Events We reported the percentage of institutes participating in public events, the mean frequency per year (M) and the standard deviation (SD). Public events that were more popular in all countries were public lectures (84%, M = 10, SD = 15); open days (76%, M = 5.5, SD = 10.6); talks at schools (63%, M = 4.4, SD = 9.2); and events with local stakeholders, such as business and industry (59%, M = 3.0, SD = 6.4). Less popular were public exhibitions (56%, M = 2.3, SD = 5.4); science cafes

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and public discussions (47%, M = 2.1, SD = 5.1); science festivals and fairs (34.6%, M = 1.5, SD = 3.8); and policy events (42%, M = 2.0, SD = 5.6) (Fig. 3.1). Traditional News Channels The most common traditional news channels reported across countries were interviews for newspapers (76%, M = 6.5, SD = 11.7); articles in magazines or newspapers (73%, M = 5.8, SD = 11.1); press releases (70%, M = 6.5, SD = 11.6); newsletters (55%, M = 5.4, SD = 11.5); radio interviews (63%, M = 3.9, SD = 8.5); and TV interviews (61%, 3.5, SD = 8.0). Less popular were press conferences (34%, M = 1.3, SD = 3.9) and policy briefings (40%; M = 1.7, SD = 5.4) (Fig. 3.2). New Media Channels New media channels were used less. Online interactions were mostly done through institutional websites rather than social media networks. A total of 88% of the institutes updated their website regularly (M = 55 updates per year, SD = 81), and 46% and 60% never used Facebook or Twitter, respectively; only 13% reported using Facebook daily, and 10% reported using Twitter daily. About 30% used blogs (M = 8.7, SD = 33); 37% used YouTube (M = 6.6, SD = 27); and 14% used podcasts (M = 2.3, SD = 15) (Fig. 3.3). Patterns of public events were similar in most countries. For traditional and new media channels, we found some slightly different patterns. For example, Twitter was more popular in the UK, the US and the Netherlands, and Facebook was more popular in Italy, Portugal and Brazil. Figures 3.1 and 3.2 show the distribution of public communication activities (public events and traditional media use) among research institutes in the eight surveyed countries. The bars show the estimated number of activities (n = 2030). Figure 3.3 shows the frequency of social media channel use, by country. Institutes were asked how frequently they used each online means, using a 5-point scale from ‘never’ to ‘daily’ (see Entradas et al. 2020). The Intensity of Activities, by Country To compare the intensity of public events, traditional news media use and new media channel use between countries, we ran ANOVAs separately for our three main variables (Table 3.1). As a benchmark, the average institute engaged in around 57 face-toface (public events) and media activities together, and more frequently in traditional media (public events M = 24, media contacts M = 33). Use of those means was skewed towards lower activity (62% of all institutes were less active than the average institute), and institutes active in one type of means were also more active in the others, but high activity was concentrated in a subset of institutes. For example, the top 20% of all institutes organized 36 or more events and had 50 or more media contacts; the bottom 20% had 7 events and media contacts or fewer and similar media contacts (see Entradas et al. 2020 for detailed descriptions).

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Table 3.1 Analysis of variance, by country Sources of variation Public events Traditional news media New media

SS

df

F

p

Part Eta

24,804.3

17.99

0.000

0.24

7

57,099.2

13.84

0.000

0.21

7

966,772.3

22.38

0.000

0.27

173,630.2

7

399,694.6 6,767,406.2

MS

SS sum of squares; df degrees of freedom; MS mean square; F statistic; p significance value; Eta strength of the relationship.

Fig. 3.4 Public events and traditional media use, by country (n = 2030)

The F-ratio indicated significant variation between groups, but substantial differences were found between only some of the countries. Institutes in Brazil, Italy and the Netherlands organized more public events overall and used traditional news media more frequently compared to the average institute in Germany, the US, Portugal and the UK (around the average). Japan reported significantly lower activity than all the others (Fig. 3.4). Institutes in Portugal, Germany and Japan (in decreasing order) maintained a weaker presence on social media (Fig. 3.4), while Brazil, the US and the UK used that channel more frequently.

3.5 For Whom: Communication Audiences A second indicator that supports our thesis concerns target audiences. The data shows that institutes direct their activities to a broad spectrum of non-peers, ranging from the general public to schools, media and journalists. The main target audiences at the meso-level were the general public (50% reported addressing it frequently), followed by prospective students (49%) and schools (45%). Industry and media were addressed moderately. Less frequently addressed audiences were NGOs and policy actors (Table 3.2). Although that was the general pattern, there were differences both

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Table 3.2 Audiences addressed by research institutes, by country % frequently addressed

Germany Portugal (%) Italy (%) (%)

Netherlands (%) UK (%) US (%)

Brazil (%)

Japan (%)

Total (%)

General public

49

51

49

54

50

54

77

32

50

Schools

31

65

56

19

32

38

65

43

45

Prospective students

48

58

57

41

41

52

53

38

49

Local councils/associations

27

38

30

32

24

21

49

32

31

Industry

43

40

19

40

41

33

26

42

37

NGOs

24

27

15

44

36

31

42

15

27

Policymakers and government

15

11

20

32

30

32

30

11

21

Media and journalists

36

35

27

49

35

30

44

23

34

within and between countries, as shown in Table 3.2. For example, in the Netherlands, the UK and the US, schools were not among the main targets. In the Netherlands, NGOs and media were among the most addressed audiences. In the UK, Japan, Italy and Germany, industry was a top target for institutions. In contrast, Portugal, Brazil and the US were less likely to address industry. Counterintuitively, given the central communication functions focusing on media relations, the media and journalists were not the main target audiences for research institutes. Only about a third of the surveyed institutes reported frequently addressing media and journalists, compared with about half that frequently addressed schools and the general public. This is not to say that institutes do not value mass media communication. When asked about their expectations of media coverage, 80% of institutes agreed that ‘media visibility is important for their research’, 40% thought that ‘the media should give more visibility to their research’, and around 62% disagreed that ‘the research they do is of little interest to journalists’. Those are indicators of aspirations for more media coverage. Table 3.2 shows the audiences addressed by research institutes, by country. The table shows percentages for ‘frequently’ addressed audiences (the percentage of institutes that address each audience ‘frequently’). Dark grey highlights the more popular audiences within a country; light grey highlights the least popular audiences within that same country.

3.6 Why: Communication Rationales We found a broad range of rationales that drive institutions to public communication. The overwhelming majority of research institutes reported doing it to disseminate the results of their research to broad audiences (31% mentioned this as the most important rationale) and to respond to the institution’s mission and policy for public communication (21% mentioned this as the second main reason). Rationales such as ‘get public support for research’ (7.5% reported this as their main priority), ‘raise research profile’ (6.3%) and ‘attract funding’ (6%) were seen as less important.

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Table 3.3 Rationales for communicating with the public, by country We aim to

Germany Italy Portugal Netherla UK (%) US (%) (%) (%) nds (%) (%)

Brazil (%)

Japan (%)

Respond to university mission/policy

26

37

3

5

4

21

45

18

Respond to funding bodies’ policies

2

1

2

5

6

6

4

2

Respond to national policies for communications

2

6

17

1

1

3

4

10

Raise research profile

4

5

3

16

20

9

13

1

Attract funding

10

12

4

12

4

6

2

3

Get public support for research

12

7

1

10

7

10

5

14

Disseminate research

37

24

63

42

36

31

20

40

Listen to and involve the public in research

1

5

6

5

19

11

3

4

Recruit new generations of scientists

7

2

0

2

2

3

4

6

We also found differences between countries, as shown in Table 3.3. As mentioned, disseminating research is the most important goal for most countries’ institutes. The exception was Italian and Brazilian institutions, the primary goal of which is to respond to the university’s mission, and Portuguese institutions mostly aimed to respond to the national policy for public communication by research institutions in that country. ‘Listen to and involve the public in research’ was one of the most important rationales for institutions in the UK and the US, but not for institutes in other countries. Table 3.3 shows rationales for communicating with the public. Institutes were asked about their most important rationale for engaging in public communication; the percentages are of those who chose each option as the most important for their institution. Dark grey signifies the highest percentage for a given rationale, and light grey signifies the second highest percentage of responses for a given rationale.

3.7 Discussion Here I provide a brief descriptive analysis of activities and commitment to public engagement in the surveyed institutions in the eight countries considered. The interpretation of national differences based on the available data is undoubtedly more complex than I can describe here, and generalizations would be too simplistic to describe the variation that we found. Instead, I put forward a few observations on similarities and differences found in the data.

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First and foremost, the data points to a growing international phenomenon and a change in research institutes to open up their research results to unspecific publics. That change has been embraced across countries, but with somewhat varying intensity and commitment. Formats of activities are similar overall among the countries, but the intensity of activities, target audiences and goals of communication vary. While this study cannot be said to assess regional or global activity, the similarities found among the surveyed countries point to an international activity that might have similar characteristics in other countries, too. That observation deserves further investigation. Despite the diversity in PUS at the national level, the factors that allowed for the development of the meso-level communication structure are common; they are mainly the professionalization of the communication structure and the incorporation of public communication in the missions of institutions (in most countries, this was given as the most important reason for public communication). While there are differences among countries in the way they engage and their levels of professionalization, we can identify a trend of increasing activity among institutions, despite some being already well established in the practice of communicating science. Generally speaking, a great variety of communication activities is on offer from research institutes. The most popular events in all countries are public lectures, open days, talks at schools and events with stakeholders; less so are science festivals, public exhibitions and science policy events. Traditional media use focuses on press releases, newspapers and newsletters; less prominent are press conferences and policy briefings. Those patterns are not surprising, given the types of activities and the effort involved in them (annual events are less common). For online media, the institutional website gets the most attention from institutions; social media networks are less popular and are more frequently used by larger institutes with more communications and research resources. The intensity of activities varies among countries. However, despite that variation being significant, it is most pronounced among only some of the countries and less pronounced overall than expected. That may be an indicator that national cultures may be becoming less evident over time as the communication activity becomes professionalized, and factors other than traditions play a role in institutional public activity. We have shown elsewhere the importance of institutional factors intrinsic to an organization, which are likely to influence the level of its public communication (Entradas et al. 2020). The similar levels of communication activity across the countries surveyed allow us to say that differences are more in evidence if we compare global regions rather than individual countries. Europe and North America seem to perform similarly, compared to Brazil (South America) and Japan (Asia). This could suggest that science communication has continental features, but that needs further investigation, as our data is limited to a small number of countries. Second, two important observations emerge from the data on audiences: public engagement emerges as enlightening, educational activity, particularly in countries such as the Netherlands, the UK, the US and Brazil, and as a civic, stakeholder activity in more industrialized and scientifically developed countries such as Japan, Germany and the UK, where the intensity of contact with stakeholders from industry is higher

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compared to countries such as Brazil and Portugal. Relationships with industry are also at a lower level in institutions in the US, which may be a characteristic of research institutes at the meso-level and not necessarily reflect overall organizational relations with industry. Also, at the meso-level, and despite the role of the universities’ central communications offices, media and journalists are not the main target. Instead, institutes are putting their efforts into reaching general publics and schools, rather than stakeholders and policymakers. Nevertheless, those relationships are more important in countries where industrial research is more intense. Overall, research institutes engage in public communication because they want to disseminate their research to broader audiences and to respond to the mission statements of their parent organizations. This points to a certain commitment to public engagement, in most cases driven by goals of enlightenment and public dissemination, rather than public engagement in research, development or policy; Nonetheless, the data shows that institutes are putting their efforts into delivering the unit’s activities rather than into establishing media relations. While that might be an indication that media communication is not the institutes’ main priority, it might also indicate difficulties in reaching the media, which may in part be due to the types of activities that institutes engage in being of less interest to journalists. Finally, these findings provide evidence of the growing activity of public communication at the meso-level. This is a characteristic in all the countries surveyed and not merely a specific characteristic of the Portuguese system. It also suggests that institutions are decentralizing their communications to other levels of the organization, and that this activity is growing in practice and becoming more professionalized. Science communication has been increasingly used by institutions looking for visibility in the public and political spheres (Weingart and Maasen 2007). While that might sound like good news, we do not know what the content and narrative of that communication is, or what values science communicators base their practices on. It seems crucial that this ongoing development considers the autonomy and values of science rather than operating on a logic of competing for public visibility, which could lead to the unintended consequence of communication becoming a marketing tool detached from the original aims of public engagement.

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Marta Entradas is an assistant professor at ISCTE-IUL, Lisbon University Institute, Portugal, and a visiting fellow at the London School of Economics and Political Science (LSE), United Kingdom. She completed her PhD in STS (Science and Technology Studies) at University College London (UCL) in 2011. She is a former Marie Curie Fellow at LSE (2016–18) and Fulbright Scholar at Cornell University (2015–16). Her main research interests lie in science communication, public understanding of science, public attitudes towards science and technology and science policy. Marta’s current research focuses on institutional communication of science with society. She is the Principal Investigator (PI) for the international project MORE-PE: Mobilisation of resources for Public Engagement (2016–2020). Marta has published on science communication and public understanding of science in top journals, and her work has been awarded international competitive prizes. Marta was the 2016 European Young Researcher winner (awarded by Euroscience).

Chapter 4

Attempts to Categorize and Evaluate Science Festivals, a 30-Year-Old Science Communication Event: The Case of Greece Elpiniki Pappa and Dimitrios Koliopoulos Abstract Science festivals have their roots in the annual conference of the British Association for the Advancement of Science, which was founded in 1831 and later renamed the British Science Festival. The modern concept of a science festival, as we know it today, first emerged in Edinburgh, Scotland, in 1989. The prevalence of science festivals has grown dramatically within the past decade, cementing their status as a global phenomenon. Between them, they share a few common characteristics of transiency, a high level of public engagement, a time-limited nature and a heterogeneous target group. However, they do not constitute a uniform set of events, as different kinds of science festivals have thus far been developed. This chapter aims to review the notion of science festivals and highlight their diversity and main characteristics. Special attention is paid to science festivals in Greece. Moreover, a brief overview of recent research data, as well as an overview of the limitations of existing studies in the field of science festivals’ evaluation, is presented. Subsequently, a theoretical and methodological framework for the study of science festival activities’ analysis, design and evaluation is proposed. Finally, suggestions for future research in the field of science festivals are discussed. Keywords Science festival · Science communication · Scientific knowledge transformation · Evaluation of science festival events

4.1 Introduction The origins of science festivals can be traced back to 1831, to the annual conference of the British Association for the Advancement of Science, which has since been renamed the British Science Festival (BSA n.d. a). Between the 1980s and 2000s, the British Science Festival was transformed from a meeting where the major scientific E. Pappa (B) · D. Koliopoulos Department of Educational Sciences and Early Childhood Education, University of Patras, Patras, Greece D. Koliopoulos e-mail: [email protected] © China Science and Technology Press 2021 B. Schiele et al. (eds.), Science Cultures in a Diverse World: Knowing, Sharing, Caring, https://doi.org/10.1007/978-981-16-5379-7_4

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advances were announced into a medium for science communication using innovative activities to disseminate scientific knowledge to the general public. The activities included in this event are characterized by means of communication that are entertaining and familiar to the public. A few examples of such events are ‘evening science meets arts’ and theatre performances, as well as activities for schools, families and broader community audiences (BSA n.d. a). The popularity of these events started to increase in the 1990s, but the Edinburgh International Science Festival in 1989 was the first science festival with modern characteristics (Cassidy 2006). According to research conducted in 2008 and 2009, almost half of the 56 science festivals included in the survey were founded between 2006 and 2009 (Bultitude et al. 2011). During the twenty-first century, science festivals have gained an important position in public life and have evolved into a key tool for science communication and public engagement with science. A closer look at their impact on the science–society interface shows that the festivals have previously been recognized as a ‘prevailing mode of science communication’ (Kim 2007:307) and a ‘vital instrument for intervention’ within the ‘dimension of the scientific culture’ (Quaranta 2007:5). The first half of this chapter presents the significant diversity of such events and subsequently proposes a categorization pattern based on six principal characteristics of science festivals. Greece’s example is used as a case study, and a description of the evolution of science festivals over the years follows. In the second half of this chapter, current studies on the field of science festival evaluation and their limitations are reviewed. Furthermore, given the existing gap in systematically evaluating science festivals, a coherent theoretical framework is suggested. The authors propose that the establishment of such a theoretical model would facilitate the development of methodological tools for the analysis, design and evaluation of science festival activities and aid in answering current related research questions.

4.2 The Case Study of Greece 4.2.1 Historical Background In Greece, science communication first appeared in the late twentieth century, when museums’ educational activities started to familiarize young people and the general public with scientific subjects. Research institutes became involved in science outreach activities for the first time in 1993, when the National Hellenic Research Foundation (NHRF) organized a science communication programme called Science Society, aiming to disseminate scientific knowledge to the general public.1 Indicatively, in the period from 1993 to 2008, the NHRF carried out 89 lecture cycles in 1

Information retrieved from an informal interview conducted with the head of Educational and Outreach Events, Science Society of the National Research Foundation, for the years from 1993 to 2013.

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which more than 750 researchers, distinguished scientists and artistic and literary personalities from Greece and abroad participated as speakers (Science in Society 2010). From 2000 onward, the General Secretariat for Research and Technology also created several science and technology awareness initiatives, including Science and Technology Week. During that time, research centres, scientific associations, museums and educational institutions also began organizing their own science awareness events, such as public talks, science cafés, interactive exhibitions and screenings of scientific films.2 A few years later, in 2006, the Natural Sciences and Technology Fair was launched by a secondary school structure and the Hellenic coordinating committee of Science on Stage—Europe (Tsitopoulou-Christodoulidi 2007). In this well-established yearly event, school students and their teachers participate by presenting scientific and technologically related projects to their peers and the general public. The term ‘science festival’ was introduced into the Greek national consciousness only in 2011, when the NHRF, in collaboration with the British Council, organized the first Festival of Science and Technology at its facilities. According to the organizers, the aim of this event was ‘to familiarize young and older people with the concepts, methodologies and secrets of scientific thoughts as well as applications of research in everyday life’ (NHRF 2011). However, the first well-established science festival was founded in 2014. The Athens Science Festival (ASF) is organized annually by the educational organization Science Communication (SciCo), the British Council and the Technopolis of the City of Athens, with the invaluable contribution and participation of more than 120 academics as well as research and educational institutions. The ASF is conducted under the auspices of the Ministry of Education and Religious Affairs and the General Secretariat of Research and Technology. During this five-day event, 15 main scientific fields are represented through a plethora of activities, including kids’ labs, workshops, science cafés, talks, art exhibitions, live experiments, performances and the interactive exhibition, which is the main and most frequently visited activity of the festival. It is estimated that 120,000 visitors have attended the event over the past six years, and that students account for a quarter of the total visitor numbers. The number of visitors is an approximation reached by an internal evaluation carried out by the festival’s organizers every year. More specifically, during all five days of the event, the visitors who enter the venue are counted by volunteers using clickers. The numbers of school students visiting the ASF, however, are more precise since they are derived from detailed booking lists created by the organizers for operational purposes. Due to the success of the event, similar festivals have been founded by SciCo in other cities of Greece and in Cyprus as well (ASF n.d.). The budgets and funding models of science festivals vary from one event to another and depend mainly on the size of the event. The executive director of the ASF, who is also a member of SciCo, provided us with some context regarding the budget and funding sources needed in order to organize and implement a science festival. Among 2

‘Science in society’, Innovation, Research and Technology, 2010, 78:18–22, http://www.ekt.gr/ el/magazines/15847 (in Greek).

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the science festival events organized by SciCo, the ASF is the biggest, attracting visitors and participants from all over Greece and abroad. Its cost is estimated at e70–100,000 and is covered by a variety of sources: 40% by revenue derived from ticket purchases, 30% by sponsorships and 30% by organizers’ resources. On the other hand, the cost for a local event organized by SciCo is estimated at e30–40,000; there is no ticket fee for the visitors, and the expenses are exclusively covered by the organizers and sponsors at 70% and 30%, respectively. For example, in the case of the Thessaly Science Festival, the budget was mainly covered by the University of Thessaly, while the Patras Science Festival was funded primarily by the Hellenic Open University.

4.2.2 Attempts to Categorize Science Festival Events The term ‘science festival’ refers not to a specific activity but is rather used as an umbrella term. Science festivals are temporary events, lasting from one day to one month and include a wide range of activities (scientific lectures, exhibitions, workshops, live demonstrations of experiments, panel discussions, hands-on activities and more) (Rose et al. 2017). Unlike other science communication and educational forums, science festivals are interactive in a way that allows children to interrelate with STEM (science, technology, engineering, mathematics) professionals and also allows adults to ask questions directly of scientists (Rose et al. 2017). Moreover, science festivals differ from activities offered at science museums and centres because of their time-limited nature and their focus on current scientific research (Jensen and Buckley 2014). Science festivals appeal to a variety of audiences by offering them the opportunity to explore numerous scientific topics and activities with just one visit (Durant 2013). A common principle of most festivals’ activities is that they combine science with fun and entertainment (Kennedy et al. 2017). The main goal of such events is to foster positive attitudes towards science, educate participants and build relationships between science institutions and the community (SFA n.d.). Although there is not a widely accepted definition of a science festival, we employ Bultitude and colleagues’ characterization (Bultitude et al. 2011) of a science festival as having the following qualities: • It has as its focus the ‘celebration’ of science, technology, engineering, and related aspects. • It aims to engage non-specialists with scientific content. • It has a time-limited nature and reoccurs annually or biennially. A systematic science festival categorization has been attempted by a few research teams (such as Bultitude et al. 2011; EUSCEA 2005). This paper offers an overview of the wide science festival spectrum with six principal characteristics of those events: main objectives; venue type; organizations involved in managing and delivering the event; activities’ facilitators; target audience; and science communication activities’ formats. Table 4.1 categorizes science festival examples taking place in Greece. The

Research centre’s premises

Scientists, researchers, university students

Scientists, researchers, science communicators, school students, teachers

Universities and research centres’ premises

Familiarize with scientific world and research application in everyday life

Activities’ Scientists facilitators

Bars

Venue type

Familiarize with scientific world and latest science research occurring in Greece

Festival of science and technology

Universities, research foundations

Inform about the latest scientific research in an accessible way

Main objectives

Researchers night

Principal University-based Universities, organizers team research foundations

Pint of science festival

Examples of Greek science festivals

Science festival events for the general public Patras science festival

Thessaly science festival

Scientists, researchers, university students, school students, teachers, artists, staff of cultural and educational organizations

Non-profit organization, non-governmental organization, city council

Scientists, researchers, university students, school students, teachers, educators, artists

Non-profit organization, university

Hub of cultural Selected venues in Patras events (technopolis) city centre

Beach

Familiarize with the world of science

Kallithea festival of science, technology and environment

Scientists, researchers, educators, artists

School students, scientists, staff of scientific unions and educational foundations

Non-profit City council, organization, foundation, university, company city council

Hub of cultural events (mill of Papas)

Introduce the latest scientific and technological advancements in an entertaining way, link everyday life to science, encourage young people to consider a science-related career

Athens science festival

Table 4.1 Categorization of examples of Greek science festivals

(continued)

Educational organizations and museums’ educational staff

Company, non-profit organization

Shopping mall

Aware about scientific and technological topics in an entertaining way

Science and technology festival

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Pint of science festival

Adults

Scientific lectures

Examples of Greek science festivals

Target audience

Main activities

Scientific lectures, interactive exhibition, experiment demonstrations

University and school students, educators, families with kids, general public

Researchers night

Athens science festival

Patras science festival

Thessaly science festival

Scientific lectures, debates, workshops, guided tours, science theatre, science films

Interactive exhibition, experiments demonstration, scientific lectures, science café, workshops, science theatre/films/shows, science and art, star observation

Scientific lectures, science café, workshops, science theatre/films/ shows, science and art

University and School students, educators, families with kids, adults, general school students, public educators, young researchers, families with kids, general public

Festival of science and technology

Science festival events for the general public

Table 4.1 (continued)

Scientific lectures, interactive exhibition, experiment demonstrations, star observation, science and art

Families with kids, adults, general public

Kallithea festival of science, technology and environment

(continued)

Interactive exhibition, experiment demonstrations

Families with kids

Science and technology festival

82 E. Pappa and D. Koliopoulos

School

School

School students and teachers

School students and parents

Interactive exhibition, experiment demonstrations

School

School students and teachers

School students and parents

Interactive exhibition, experiment demonstrations, digital workshops

Interactive exhibition, experiment demonstrations

School students and parents, educators, general public

School students and teachers

Director of secondary education, EU program

School

Director of secondary education, city council

School, university’s premises, Cyclades Chamber of Commerce

School students and teachers, scientists, educators

School, city council, scientific union

Town hall

Popularize science

Interactive exhibition

Scientific lectures, workshops

Interactive exhibition, experiment demonstrations, lectures, workshops, star observation

School students and parents School students and School students and parents, educators, general parents, general public public

School students and Scientists, researchers, teachers, university students educators

Director of secondary education, scientific union

School

Aware about the role of natural sciences in education and society; popularize science

School

Aware about STEM education and innovation in the natural sciences

Aware about the connection of everyday life with the scientific phenomena

Aware about scientific and technological topics

Aware about scientific and technological topics

Natural science festival–Syros

Natural science fair

Mixed-form science festival events Lesvos STEM festival

Science and technology festival

Fair of natural sciences and technology

Natural sciences and technology fair

School-based science festival events

Table 4.1 (continued)

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marked diversity of the festivals’ characteristics makes each of them a special case. However, looking more closely at Table 4.1, we can recognize a few patterns that arise and distinguish between three types of science festivals: events for the general public, school-based events and mixed-form events. In the first category, science festivals are organized by universities or organizations related to non-formal science education and science communication (Bultitude et al. 2011; Jensen and Buckley 2014). In this group of events, audiences and the activities’ facilitators can range from school students to scientists, and the events can include a variety of activities. The main objectives and venue types for such events differ among organizers. Indeed, when the main organizer is a university, the science festival usually takes place in the university setting and aims to inform the public about the latest scientific research occurring in the reference country. On the other hand, science festivals organized by other organizations have more broad aims, such as to link everyday life to science and encourage young people to consider science-related careers. In this case, science festivals occur without relation to science venues and are commonly located in the city centre (such as in bars, cultural hubs, shopping malls and so on.). The second category comprises events that are primarily organized by the school community (such as schools or directors of secondary education) in cases where formal education recognizes the need to introduce non-formal education activities into the curriculum (Koliopoulos et al. 2005; McComas 2011). School-organized science festivals, taking place in a school setting, aim mainly to address pupils and their parents. Their main objective is for students to present scientific phenomena through interactive exhibitions or experimental demonstrations and thus understand the link between natural sciences and everyday life. In the third category of mixed-form events, science festivals that engage both the school community and the general public are included. Their activities’ facilitators are not only school students, but also people related to science (such as scientists). Such events occur out of the school setting and have mixed organizational patterns (for example, a school collaborating with a city council). Another categorization that can be made is based on science communication activities used in the science festival. The target audiences and formats of diverse science communication activities taking place in a science festival are shown in Fig. 4.1. Each of the activities has a principal target audience (shown on the y-axis, based on the examples of Greek science festivals listed in Table 4.1) and a specific activity format in relation to the degree of its formality (x-axis) based on the activities’ format categorization made by EUSCEA (2005). It is worth mentioning that specialized activities are used for different target audiences. For instance, science cafés, debates and lectures are addressed to adult audiences, while interactive exhibitions and demonstrations of experiments mostly target school-aged students and families with kids.

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Fig. 4.1 Overview of science festival activities related to their degree of formality (x-axis) and their target audiences (y-axis)

4.3 Attempts to Evaluate Science Festival Events Most current evaluation efforts attempted in the field of science festivals are based on participant self-reports or on event-generated reports and recommendations (for example, Dundee Science Centre 2016; SFA 2016; British Science Association 2017, 2018, 2019). A few efforts to evaluate science festivals’ social impact have attempted to measure visitors’ attitudes towards science and their learning gains after attending these events, or focused on attendees’ expectations and experiences (for example, DSC 2016; BOP Consulting 2016; SFA 2016; Sardo and Grand 2016; Fogg Rogers 2017; BSA 2017, 2018, 2019). However, systematic evaluative efforts lag behind (Rose et al. 2017). Most science festival evaluation studies are methodologically limited and are based mainly on closed questionnaires and a self-reporting approach that offer little insight into the impact or value of an activity or science festivals overall (Jensen and Buckley 2014). A few articles about school science festivals (science fairs) report positive and supportive attitudes from participating school students (Abernathy and Vineyard 2001). However, researchers generally agree that most of the articles written about the effectiveness of science fairs are based on opinion rather than on research (Yasar and Baker 2003). After all, very few studies have focused on visitors’ views and have subsequently been published in peer-reviewed journals (Jensen 2011). Another crucial issue that has not yet been highlighted in contemporary research is the aspect of the design of science festival activities and the transposition of scientific

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knowledge taking place in order to create forms of knowledge that are accessible to the public. In Greece, there is research in progress in this field that aims to assess the design of such activities and evaluate their potential cognitive impact on visitors, and particularly on school students. Considering the lack of a solid theoretical framework for the evaluation of science festivals, it is initially necessary to develop such a framework in order to permit the production of systematic and thorough research data in the field of science festival design and evaluation. We propose that such a theoretical and methodological framework could be based on the intersection of three research fields concerning different perspectives on the diffusion of scientific knowledge: (A)

(B)

(C)

The field of science communication (Stocklmayer et al. 2001; Schiele et al. 2012), which addresses, among other things, issues of public understanding of scientific knowledge and scientific knowledge diffusion to general audiences. The existing theoretical studies and methodological tools of this field may provide us with data about the popular image of science, its potential, its difficulties, and the limits of science popularization. Moreover, through this field, we can collect valuable information, not only regarding the gap between science and culture, but also about the process of communication as a twoway cross-cultural event. The field of science communication can serve as an ‘epistemological umbrella’, ensuring an epistemologically reliable version of science festival evaluation. The field of science museology (Guichard and Martinand 2000; Schiele 2001; Achiam and Marandino 2014; Filippoupoliti and Koliopoulos 2014), which offers a framework for the communication and transposition of scientific knowledge, in the cases of science exhibitions within science museums and centres. We argue that this framework can be adopted in the case of science festivals, and especially with regard to interactive exhibitions, experiments and demonstration activities. Science museum exhibitions (Triquet 1993) and science festivals’ interactive activities share several characteristics, the most important of which are an aim to not transmit specialized scientific knowledge but rather to promote the scientific literacy of people, in order to understand the everyday world; a mixed and diverse audience; an aim to educate through entertainment; and a presentation of a scene, rather than a simple text-to-knowledge correspondence. The field of science education (Astolfi and Develay 1989; Lederman and Abell 2014), which investigates, among other things, school students’ cognitive and emotional progress during formal and formal/non-formal interaction educational settings. Consequently, this field may offer fundamental theoretical knowledge and methodological solutions, particularly in the evaluation of school-based science festivals, but also for other forms of science festivals that target school students.

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4.4 Epilogue Despite the fast-paced growth in the numbers and types of science festivals all over the world, and the multi-year effort to assess the impact of such events, research in this field remains in its primary stages. An extensive number of research questions have not yet been adequately investigated, or in some cases, at all. Among the queries looking for answers are the following: (A) (B) (C)

What are the epistemological and pedagogical conceptions of science festival organizers? What is the cognitive impact of science festival activities on the general public? What is the potential role of science festivals in formal education settings as extracurricular activities?

Acknowledgements This research is co-financed by Greece and the European Union (European Social Fund—ESF) through the Operational Programme ‘Human Resources Development, Education and Lifelong Learning’ in the context of the project ‘Strengthening Human Resources Research Potential via Doctorate Research’ (MIS-5000432), implemented by the State Scholarships Foundation.

References Abernathy TV, Vineyard RN (2001) Academic competitions in science: what are the rewards for children? Clearing House 74(5):2692–2776. https://doi.org/10.1080/00098650109599206 Achiam M, Marandino M (2014) A framework for understanding the conditions of science representation and dissemination in museums. Museum Manage Curatorship 29(1):66–82. https://doi. org/10.1080/09647775.2013.869855 ASF (Athens Science Festival) (no date) Athens science festival. https://www.athens-science-fes tival.gr/en/festival/ Astolfi JP, Develay M (1989) La didactique des sciences. Presses Universitaires de France BOP Consulting (2016) Edinburgh festivals 2015 impact study. Edinburgh Festivals City. https:// www.edinburghfestivalcity.com/about/documents/156-research-reports BSA (British Science Association) (2017) The history of the festival. British Science Association. https://www.britishscienceassociation.org/the-history-of-the-festival BSA (British Science Association) (2018) British science festival: festival evaluation reports. British Science Association. https://www.britishscienceassociation.org/british-science-festival BSA (British Science Association) (2019) Our history. British Science Association. https://www. britishscienceassociation.org/history Bultitude K, McDonald D, Custead S (2011) The rise and rise of science festivals: an international review of organized events to celebrate science. Int J Sci Educ Part B 1(2):1651–1688. https:// doi.org/10.1080/21548455.2011.588851

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Cassidy A (2006) Evolutionary psychology as public science and boundary work. Public Underst Sci 15(2):175–205. https://doi.org/10.1177/0963662506059260 DSC (Dundee Science Centre) (2016) Evaluation report: Dundee science festival. Dundee Science Centre. http://sciencefestivals.uk/wp-content/uploads/2018/01/Dundee-Science-Festival-2016evaluation-report.pdf Durant J (2013) The role of science festivals. PNAS 110(8):2681. https://doi.org/10.1073/pnas.130 0182110 EUSCEA (European Science Events Association) (2005) Science communication events in Europe: white book. EUSCEA, Germany Fogg Rogers L (2017) UK science festival network pilot evaluation 2017. UK Science Festival Network. https://uwe-repository.worktribe.com/output/883350/uk-science-festival-net work-pilot-evaluation-2017 Filippoupoliti A, Koliopoulos D (2014) Informal and non-formal education: history of science in museums. In: Matthews M (ed) International handbook of research in history, philosophy and science teaching. Springer Guichard J, Martinand JL (2000) Médiatique des Sciences. Presses Universitaires de France Jensen E (2011) Evaluate impact of communication. Nature 469(162):1032–1033. https://doi.org/ 10.1038/469162c Jensen E, Buckley N (2014) Why people attend science festivals: interests, motivations and selfreported benefits of public engagement with research. Public Underst Sci 23(5):557–573. https:// doi.org/10.1177/0963662512458624 Kennedy EB, Jensen EA, Verbeke M (2017) Preaching to the scientific converted: evaluating inclusivity in science festival audiences. Int J Sci Educ Part B 8(1):14–21. https://doi.org/10.1080/215 48455.2017.1371356 Kim H-S (2007) PEP/IS: a new model for communicative effectiveness of science. Sci Commun 28(3):287–313. https://doi.org/10.1177/1075547006298645 Koliopoulos D, Constantinou C, Evagorou M (2005) The science fair: an example of non-formal education in science. Synchroni Ekpaideysi 141:109–119 (in Greek) Lederman NG, Abell SK (2014) Handbook of research on science education, vol 2. Routledge McComas W (2011) Science fairs: a new look at an old tradition. Sci Teach 78(8):343–348 NHRF (National Hellenic Research Foundation) (2011) Science Society: special educational events. National Hellenic Research Foundation. http://www.eie.gr/epistimiskoinonia/2011-2012/opensc ience-gr-videos_sciencefest2011.html (in Greek) Quaranta G (2007) Knowledge, responsibility and culture: food for thought on science communication. J Sci Commun 6(4):1–5. https://doi.org/10.22323/2.06040305 Rose KM, Korzekwa K, Brossard D et al (2017) Engaging the public at a science festival: findings from a panel on human gene editing. Sci Commun 39(2):2502–2577. https://doi.org/10.1177/107 5547017697981 Sardo AM, Grand A (2016) Science in culture: audiences’ perspective on engaging with science at a summer festival. Sci Commun 38(2):2512–2560. https://doi.org/10.1177/1075547016632537 Schiele, B (2001) Le musée de sciences. L’Harmattan Schiele B, Claessens M, Shi S (2012) Science communication in the world: practices, theories and trends. Springer. https://www.springer.com/gp/book/9789400742789 SFA (Science Festival Alliance) (2012) 2012 annual report. Science Festival Alliance. https://sci encefestivals.org/resource/2012-science-festival-alliance-annual-report/ SFA (Science Festival Alliance) (2016). 2016 annual report. Science Festival Alliance. https://sci encefestivals.org/resource/2016-annual-report/ SFA (Science Festival Alliance) (no date) Science festivals member map. Science Festival Alliance. https://sciencefestivals.org/festivals Stocklmayer S, Gore M, Bryant C (2001) Science communication in theory and practice. Kluwer Academic Publishers Triquet E (1993) Analyse de la genèse d’une exposition de science. PhD thesis, Université ClaudeBernard, Lyon (in French)

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Elpiniki Pappa is a PhD candidate at the University of Patras, where she studies science festivals and tries to develop a coherent theoretical framework as well as methodological tools for systematically designing and evaluating science festivals’ activities. She has worked for several years in a not-for-profit organization (SciCo), specializing in the field of public understanding of science. During that time, she gained significant experience in the development and implementation of science communication projects for the general public as well as of non-formal science education programmes for 9–15-year-old students. She is a biologist and an MSc in neuroscience. During her studies, she has acquired research experience in the field of molecular and cellular neurobiology and worked with different research teams around the world (Department of Animal and Human Physiology, University of Athens; Jean-Pierre Aubert Research Centre, Lille; Centre for Neurogenomics and Cognitive Research, Amsterdam; Pharmacology Department, Cambridge University). Dimitrios Koliopoulos is a professor at the Department of Educational Sciences and Early Childhood Education of the University of Patras. He holds a diploma in Physics from Aristotle University of Thessaloniki (Greece) and has done postgraduate studies in science museum education and science education at the Jussieu University of Paris (France) and at University of Patras (Greece). His research interests concern epistemological and educational aspects of the transformation of scientific knowledge to school science in formal and non-formal (for example, museums, science festivals) educational settings. He has also been involved for years in pre-service and in-service teachers’ training in primary and secondary education. He has been the head of the Department of Educational Sciences and Early Childhood Education (2016–2018) and the Department of Museum Studies (2019) of the University of Patras.

Chapter 5

Emerging Practices in Science Communication in Canada Michelle Riedlinger, Alexandre Schiele, and Germana Barata

Abstract The changing communication landscape and declining institutional support for science communication pose significant challenges for science communicators, including community disagreement about what counts as ‘good’ science communication practice. In this chapter, we investigate the emerging online practices of science communicators in Canada. We focus on how science communicators are adapting and thriving online and what they value. Using social media research tools and survey data gathered from communicators, we found that social media communicators of science in Canada are focused in areas including conservation advocacy, women in STEM, science-art and combating misinformation. Social media communicators of science were more likely to be involved in informal community networks rather than professional associations. While there were similarities, we found significant differences in emerging practices in Quebec and other provinces in Canada, and in the main representations and motivations of communicators. Popular social media communicators in Quebec tended to be associated with traditional science media platforms. Social media communicators in our study continued to value engagement, relevance, writing quality, accessibility and accuracy. However, some were also motivated to promote inclusivity, to represent diversity and to overcome marginalization through their communication. It will be important for researchers and professional organizations to better understand the role of online networks and networking for M. Riedlinger (B) School of Communication and the Digital Media Research Centre, Queensland University of Technology, Brisbane, QLD, Australia e-mail: [email protected] M. Riedlinger · G. Barata Schol-CommLab At Simon Fraser University, Vancouver, Canada e-mail: [email protected] A. Schiele Hebrew University of Jerusalem, Jerusalem, Israel e-mail: [email protected] G. Barata Laboratory of Advanced Studies in Journalism (Labjor), State University of Campinas, São Paulo, Brazil © China Science and Technology Press 2021 B. Schiele et al. (eds.), Science Cultures in a Diverse World: Knowing, Sharing, Caring, https://doi.org/10.1007/978-981-16-5379-7_5

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professional development and support for emerging science communication practices. Communication practices motivated by a desire to promote equity and inclusivity in STEM are also increasingly important and require more attention from science communication researchers and practitioners. Keywords Social media · Scicomm · Sci-art · Media systems · Values · Inclusiveness

5.1 One of the ‘Problems’ of Social Media Science Communication in Canada In 2018, a Canadian science Instagrammer and PhD student at the University of Toronto, Samantha Yammine, was criticized in an op-ed piece in Science for trivializing scientific endeavours on social media (Wright 2018). Yammine was one of a group of researchers who started a very successful campaign called ‘Scientists who Selfie’. The aims of the campaign were to present the diversity of people working in science and to investigate the impact of researchers’ selfies on public perceptions of science (Jarreau et al. 2019). Yammine was criticized in the Science op-ed piece for her ‘pretty selfies, fun videos, and microscope images captioned with accessible language and cute emojis’ (Wright 2018, paragraph 2). Critics of the Science article argued that Yammine was successfully responding to the Instagram medium; they applauded her attempts to help close the STEM gender gap by appealing to younger women to consider a career in science (see, for example, Chen 2018; Gordon 2018; Marks 2018; Strapagiel 2018; Zaringhalam et al. 2018). The editors of Science subsequently acknowledged that they are still grappling with how social media is used in science communication and have changed their editorial policy to reflect that. In addition to publishing many readers’ letters on this issue, they published an article by Yammine and other North American social media communicators describing the benefits of social media for science communication (Yammine et al. 2018).

5.2 The Changing Science Communication Landscape in Canada Responses to Yammine’s use of social media raised important issues for the Canadian science communication community: what counts as ‘good’ science communication in the fractured communication landscape, and how are communicators responding to the decline in institutional support for science communication? In 2008, 270 local Canadian news outlets closed or merged, and one-third of Canadian journalists lost their jobs. Canada’s Public Policy Forum published an influential report titled The shattered mirror, which documented the ailing state of Canada’s

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traditional media, particularly print media, and made a number of recommendations for federal government support.1 Of particular interest to science communication, the authors of The Shattered Mirror stated that ‘Canadians still seek to be informed— although at the time of their choosing and with little or no cost to themselves.’ Citizen journalists have filled this niche for local content left empty by a faltering mainstream media system. News reporting by those who do not identify as full-time journalists or broadcasters is now recognized as an integral part of the news cycle (Bruns et al. 2012). The same economic and technological opportunities and disruptions that have affected journalism have affected science communication. Along with the rise of social media science communication, there has been a reduction in federal and provincial government support for science and science communication in Canada (Boon 2017). For example, the Natural Scientific and Engineering Council of Canada has funding available for scientist training and activities directed towards school-aged children but nothing to support online science communicators or online science communication directed towards adults. In many countries, scientific researchers are increasingly encouraged to fill gaps in online communication left by faltering media systems (Barel-Ben David 2020; Nisbet 2017; Peters 2014),2 but there are new challenges associated with that approach. It can be difficult for researchers to integrate their scientific claims effectively into everyday concerns without professional mediators (Peters 2014), and the proliferation of free and immediately available online public relations materials from research institutions means that traditional mediators of science communication content are no longer the gatekeepers of quality. Bucchi (2013) calls this state of affairs ‘a crisis of mediators’. Others are calling for more attention to how science communication is regulated, arguing that public trust in science relies on trust in science communication (Weingart and Taubert 2017). Some researchers argue that the cultural authority of science is at stake (Bucchi 2017). But the regulation of science communication is not easily achieved. While the science communication research community is considered to be reflective and critical about the practices and impacts of science communication activities, there has never been a standardized set of norms and values for science communication (Davies and Horst 2016; Medvecky and Leach 2019). In regard to media disruption, Irwin and Horst (2016) also caution against seeing science communication as a past utopia of practices that science communicators have lost, as communicators blame social media science communication for mixing ‘objective science’ with strategic institutional communication. Davies and Horst (2016) call for a better understanding of the growing social media science communication landscape in order to fully appreciate emerging professional communication values, how science contributes to public sense making in online environments, and the diversity of practices of ‘good’ science communication.

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Public Policy Forum, The shattered mirror: news, democracy and trust in the digital age, 2017, https://shatteredmirror.ca/. 2 Resolve to engage in 2017, Nature, 2017, 541:5.

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In efforts to generate conversations about the emerging practices of ‘good’ online science communication in Canada, the curators of the blogging salon Science Borealis initiated social media discussions through Twitter and Facebook.3 They used the hashtag #SciComm100 to generate rich discussion about science communication in Canada and captured the views of 100 scientists, journalists, policymakers, communication specialists, government leaders, educators and artists. They presented a rich picture of the audiences, motivations, goals and practices of science communication in Canada and found that those working in this space were motivated to help publics critically evaluate social media content and to support researchers in harnessing the capabilities of new communication technologies, particularly to capture diverse voices and perspectives and reach traditionally underrepresented and overlooked groups. The Agence Science-Presse launched a similar online campaign in 2016, called #100LaScience, for the promotion of francophone science journalism in Quebec. The agency called upon dozens of major Quebecois personalities to express positive ideas about science journalism, and some of their quotes were illustrated by veteran Quebec science communication illustrator Jacques Goldstyn. More recently, science communication freelancer Alan Shapiro (2020) published a review of the changing anglophone Canadian science communication landscape over the past 10 years. He emphasized the growing number of anglophone Canadian Twitter and Instagram communities that have emerged and some of the more innovative science communication activities on Twitter, Instagram and Facebook. In his review, he argued that innovative and important online events, including the launch of Science Borealis in 2013, the formation of Art the Science (an online exhibition gallery) in 2015 and professional development opportunities for scientists through workshops and conferences such as Science TO and ComSciCon have encouraged greater participation in science communication through social media.

5.3 Mapping Social Media Science Communication in Canada Professional science communication associations in Canada are also responding to calls to better support emerging practices and critical innovation in online science communication. In 2017, the Canadian Science Writers Association changed its name to include ‘science communication’ as a response to changes happening in the Canadian media landscape. The association’s change of name to Science Writers and Communicators of Canada (SWCC) aims to recognize the diversity of individuals and organizations that make up the field. The association’s original mandate was built on the journalistic values of accuracy, factual integrity, originality, fairness and transparency, and it continues to maintain a commitment to promoting excellence in science journalism that is built on those values. The SWCC Board, which is made up 3

Reflections: 100 voices for Canadian science communication, Science Borealis, no date, https:// scienceborealis.ca/100-voices-for-canadian-science-communication/.

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of in-house journalists, freelancers, science communicators working within research institutions and universities, and outreach facilitators, was keen to know whether the association’s values resonated with the new membership and science communicators working in social media spaces. Those were the communicators that the SWCC wished to support and attract to the organization. As part of this initiative to support emerging practices and critical innovation in online science communication, the association launched the People’s Choice Award for online science communication in conjunction with Science Borealis to recognize the growing importance of emerging online science communication practices. Award winners in the past few years have included science bloggers, online news site producers, online outreach and education initiatives, and independent podcasters. Social media science communicators have been finalists in the awards but are yet to win one. Recent work in the field of journalism studies shows that social media logic prioritizes the values of connectivity (relationship building and personal recommendations) and popularity (through likes and forwards/retweets) over traditional news values (van Dijk and Poell 2013). British Columbian researcher Alfred Hermida (2019) argues that emerging values of immediacy and solidarity with readers or viewers compete with established news values of impact, proximity and conflict. He argues that, in online contexts, emotion, empathy, and personal experience are the currency of circulation, rather than evidence, facts, truth and reality. These changes could be significant for science communicators and online science communication activities in Canada, where shareable social media content can be an indicator of successful communication. To build on this growing body of research, we collaborated with the SWCC and its francophone equivalent—the Association des comunicateurs scientifiques du Québec (ACS)—to find out who is communicating about science through social media in Canada and what they value. We recognize science communication as a field of both activity and sociocultural research (Metcalfe and Riedlinger 2020) and, when considering it as a field of activity, we base our understanding on the widely accepted definition provided by Burns et al. (2003: 183): ‘the use of appropriate skills, media, activities, and dialogue to produce one or more of the following personal responses to science (the AEIOU vowel analogy): awareness, enjoyment, interest, opinion-forming, and understanding’. We also acknowledge online activity resisting what Dawson (2014, 2019) describes as the exclusion and reproduction of inequality inherent in science communication.

5.3.1 Social Media Science Communicators in Canada We started this research endeavour by identifying Canadian social media communicators of science using Twitter and Instagram, which are two of the most popular social media channels in Canada. Using Altmetrics, Netlytic software, webscraping and professional community tags, including ‘scicomm’, ‘comsci’, ‘sciart’, ‘artsci’ and ‘vulgarisation’, we identified and mapped 197 science communicators on Twitter,

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56 on Instagram and 52 writers of science blogs. Our methodologies (see Riedlinger et al. 2019) facilitated easier access to geolocation and biographical data for Twitter accounts compared to Instagram accounts, for which that information is not so readily available. After collecting the first sample, we cleaned the data to exclude private accounts and then searched for potential science communicators ‘followed’ by our first sample. In January 2021, the map had 296 Twitter accounts and 34 Instagram accounts. Instagram recently changed its API (application program interface), which limited our data to Instagram Professional accounts (business and creators) and excluded personal accounts. We found many Canadian social media science communicators in our collection were women (54.5%) living in Ontario (40%). They had between 500 and 2000 followers (40%) and worked mostly in the discipline of biology (more specifically, the fields of ecology, conservation biology, cell and molecular biology and neuroscience. In our collection, groups (rather than individuals) were more likely to have 10,000 to more than 100,000 followers (see Riedlinger et al. 2019: 56 for demographic comparisons). Groups (21.8% of the sample) represented in our collection included science centres and museums, festivals and science outreach projects, which is not surprising, considering that science communicators in those groups can engage with a large number of visitors on physical sites. The map of science communicators on social media in Canada is available online.4 It is updated using contributions from the community. In January 2021, it contained 330 entries: 34 on Instagram and 296 on Twitter. Only public accounts, the owners of which self-identify as science communicators working in Canada, are included. The aim is to provide visibility and support collaboration among science communicators and to recognize and value relevant and enriching efforts to communicate science on social media. The map’s maintenance is possible only through collaboration with Canada’s science communication community, which can draw our attention to new communicators and outdated information. Ninety-seven new Twitter accounts have been added in the past year, which has allowed us to better search for connections between science communicators. In what follows, we examine some of the key individual efforts to communicate science on Twitter and Instagram to better understand who is thriving in Canadian social media science communication spaces. Our collection contains a large number of artists who work with science and communicate through illustrations, infographics, cartoons, art–craft work, sculptures or petri dishes. We provide a sample that represents the diversity of communicators from around the country, and we have chosen five of the most popular communicators of science on social media in Canada and five science artists who focus on a range of topics.

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Mapping the new landscape of science communication in Canada, http://mapscicommcanada.lab jor.unicamp.br/.

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5.3.2 The Most Popular Social Media Science Communicators in Canada AsapScience (@asapscience) by Mitchell Moffitt and Gregory Brown has more than 31,000 and 27,000 followers, respectively, on Twitter. Their YouTube channel has more than 9.5 million subscribers, and on Tik Tok they have almost 688,000 followers. These communicators use the whiteboard animation technique to deal with a broad range of daily science questions, such as how coffee works on our brains, what it will take to make a Covid-19 vaccine, the use of make-up, abortion, and parodies of pop songs. They focus their videos on making science enjoyable for both children and adults. Samantha Yammine (@science.sam) has more than 95,000 followers on Instagram and 20,000 on Twitter. She shares her experiences as a neuroscientist and storyteller in her own words. She started communicating while she was doing her Ph.D. research at the University of Toronto. She deals with lab and science routines, women in science, cellular biology and molecular biology in general. She has been communicating about Covid-19 and has started posting to TikTok. Mika McKinnon (@mikamckinnon) has gathered more than 67,000 followers on Twitter. A geophysicist and physicist from the west coast, she describes herself as a disaster expert, a science writer, a sci-fi consultant and a freelancer. She uses pictures and threads to engage her audience and shares information, including on day-by-day science, biology and women. David Shiffman (@WhySharksMatter), who is a marine conservation biologist and science writer from British Columbia, is on Twitter. He has attracted almost 54,000 followers. His efforts have made him an important source for people interesting in shark science and conservation. He gathers, criticizes and shares research and public conversations about sharks. He has become an influencer in highlighting the dangers, conservation and policy issues associated with sharks. Sarah Habibi (@science.bae), who is a Ph.D. researcher in pharmacology and parasitology at Ontario Technology University of Canada, is on Instagram, where she is a science communicator, educator and make-up artist. She has almost 22,000 followers. She was the winner of Canada’s Three Minute Thesis competition in 2019. She uses make-up to communicate science on Instagram and TikTok, where she is one of the most popular science communicators and has more than 111,000 followers. She usually posts on TikTok without songs, which are an important feature of this emerging social media platform.

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5.3.3 Some Examples of Social Media Science Artists in Canada Samantha Stephens (@samanthastephens) has more than 13,000 followers on Instagram. She is a biologist and photojournalist of wild nature and ecology in Ottawa. She shares photos of animals, nature and the work of ecologists and conservation biologists in the field. Glendon Mellow (@FlyingTrilobite) has 10,000 followers on Twitter and lives in Toronto. He blogs (https://glendonmellow.com/blog) and is a sci-art freelancer who has done work ranging from tattoos, scientific illustrations of skeletons and animals to creative surrealistic pieces and science fiction. Dinosaur Dungeon (@dinosaurdungeon) has 8000 followers on Instagram and is a palaeoartist from Ontario. He creates realistic dinosaur sculptures. Since 2009, he has had a YouTube channel (https://www.youtube.com/user/drjre77/videos) where he shows the creating process to 1500 subscribers. Tahani Baakdhah (@Thepurplelilac) has 6800 followers on Twitter. She is a stem cell researcher in Toronto with a creative and unexpected way of communicating science through crochet. Her main topics are microbiology, neurology and anatomy. Pineapples and Whales (@pineappleswhalesci) has 200 followers on Instagram. Daisy and Chloé are from Winnipeg, Manitoba and draw science with humour using infographics. They deal mostly with ecology and conservation biology topics.

5.3.4 A Survey of the People Whose Accounts We Mapped After collecting 256 social media accounts for the map, we invited the people representing those accounts to answer a survey about their motivations and practices. We received 74 responses and compared them to the responses of science communicators who were members of professional organizations (SWCC and ACS) and who completed a similar survey (see Riedlinger et al. 2019). More precisely, we compared the demographics of those groups, their activities related to science writing and communication, their attitudes towards science writing and communication, and their social media practices. We found that the social media science communicators who answered our survey were demographically different (Riedlinger et al. 2019) from the professionals. They were younger (nearly half were under 30 years old), more of them were paid less (or not at all) for their science communication activities, and more of them were female. Moreover, members of this group were more likely to have formal qualifications in science (rather than communication, journalism or education) and more of them had been communicating science for less than 10 years compared to the respondents from the professional associations. The proportion of social media respondents who

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belonged to a professional science communication association was much smaller than the proportion of respondents from the SWCC and ACS groups. Social media group respondents were statistically more likely to be involved in an informal network of science communicators than SWCC and ACS members. Respondents described those informal networks as groups of trusted colleagues, groups who met at locally organized events (such as NerdNight, Curiosity Collider, ScicommTO, and VISquebec), academic networks (such as the Research Communicators Canada listserver), alumni from Laurentian University programmes, social media groups (such as FB comsci; science Twitter, CommSciCommCA, Facebook pages for scicomm alumni, jobs and so on) and the blogging salon Science Borealis.

5.4 The Distinctive Place of Quebec in the Canadian Science Communication Landscape In order to understand the present state of online science communication in Quebec, it is necessary to understand the specific traits constituting the distinctiveness of the Province of Quebec within Canada. Quebec occupies 15.4% of the total area of Canada (a little over 1.5 million square kilometres) and has 23.2% of the total population, or a little over 8 million people. Quebec is the second largest province or territory, behind Nunavut, and the second most populous, behind Ontario. Quebec stands as the sole majority francophone province within the confederation. Over half of the population of Quebec is concentrated in the city of Montreal, with nearly 4 million inhabitants, and Quebec City, the provincial capital, has more than 750,000 inhabitants. The pillars of culture, higher education and research are similarly developed in those two large cities, but also, to a lesser degree, in the cities of Gatineau (315,000) and Sherbrooke (202,000). Contacts, intellectual or otherwise, between francophone Quebec and the rest of Canada, or between francophone Quebec and anglophone Quebec, are limited, owing in large part to the language barrier. This situation has often been referred to as the ‘two solitudes’. Since 1977, the French language has been the sole official language of the province, although education can still be dispensed in English. Universities are key drivers of science communication in Quebec and, of the seven universities, three are anglophone. In 2015, 155,000 full-time university students were studying in the five Montreal-based universities, or 65% of the total university student population in Quebec. In 2018, 12% of Quebec university students were international, and Montreal was the third destination of choice for international students, behind Toronto and Vancouver (a quirk of francophone Quebec, since Montreal and Toronto are home to the same number of universities). Two of Quebec’s universities rank among the top universities in Canada and worldwide (McGill University and the University of

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Montreal, both located in Montreal).5 Quebec has also played a major role in the development of francophone culture and science communication (Pitre 1994). Out of the 18 science museums in the province, eight are in the Greater Montreal area, two in the Greater Quebec area and one is in Sherbrooke.6 However, at the turn of the new millennium, on the eve of the emergence of social media, the provincial government largely ceased to take a direct role in the promotion of science and technology. The differences between Quebec and other provinces and territories in Canada are, to some extent, reflected in the social media landscape. By 2018, 83% of those living in Quebec were using social media, and 65% were logging on at least once a day. The two most popular social media platforms in Quebec are Facebook (70% of adults were logging on in 2018) and YouTube (which was used by 64% of adults). The number for YouTube rose to 79% among adults who had children 12 years old or younger. By comparison, fewer adults accessed Instagram (24%), LinkedIn (18%), Pinterest (17%), Snapchat (16%), WhatsApp (14%), Twitter (12%) and various other platforms (8%) (CEFRIO 2018). Adults in other provinces and territories in Canada make use of a greater diversity of social media platforms in addition to the ones already mentioned: Google+, Reddit, Twitch, Tumbler, Yelp, Flickr and Foursquare. The rates of use for Facebook and YouTube are comparable between Quebec and other provinces and territories, but more people living in other provinces and territories in Canada are using other social media sites compared with those living in Quebec (25% and more: Instagram 43%, Pinterest 29%, Twitter 29%; 10% and more: Google+ 24%, Snapchat 23%, LinkedIn 21%, Reddit 14%).7 Quebec adults are fairly active users of social media: 66% report that they have published on a friend’s page or on a group page, 20% report that they regularly publish on group pages and 26% report that they publish occasionally. Although more than half of adults from 18 to 65 years old who are active on social media log on, more than 75% of 18–55-year-olds do, rising to 92% for 18–24-yearolds.

5.4.1 Social Media Science Communicators in Quebec As is to be expected, Quebec is second only to Ontario in the number of online science communicators we identified in this study (see Riedlinger et al. 2019). Figure 5.1 presents a demographic comparison of social media communicators of science and other science communicators in Quebec.

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Greater Montréal: the perfect place to study, Montréal International, March 2020, https://www. montrealinternational.com/app/uploads/2020/03/montreal_attractiveness-factors_students_20201.pdf. 6 Regrouper les musées scientifiques pour les sauver, Radio-Canada, 11 January 2019. 7 Social networking in Canada—statistics & facts, Statista, 2019, https://www.statista.com/topics/ 2729/social-networking-in-canada/.

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P eak age (31– 35)

No formal training 10 years+ experience Full-time permanent Self-employed Female Social media use 0%

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Fig. 5.1 A demographic comparison of social media communicators of science and other science communicators in Quebec

Only 55% of the science communicators we surveyed relied on social media for their communication activities; those who were 26–50 years old were the most active, peaking among 31–35-year-olds (25%). The three most favoured social media channels were Facebook (45%), Twitter (36%) and YouTube (29%), which correlates with general social media habits of the Quebec population. Significantly, 67% of online science communicators in Quebec in our study were women. Half reported that they post new content daily; that number rises to nearly 65% if ‘every other day’ posters are included. Although nearly 45% of online science communicators boast over 10 years of experience, more than 25% admit that they have no formal training in science journalism or communication. Their numbers of followers are also relatively low: 85% have 5000 followers or fewer, and 40% have between 1000 and 5000 (Schiele and Riedlinger 2018). Interestingly, only 25% of social media science communicators in Quebec in our study were self-employed science communicators. Just over 45% were fulltime permanent employees. This is a peculiarity of Quebec; in the rest of Canada, the percentages of self-employed and full-time permanent employees were similar (30%–35%). Permanent employees in Quebec were working in education, cultural organizations, news media, non-profits or the government. It would seem, from the social media platforms that they use, that online science communicators in Quebec derive little if any direct income from content views, and that most are either directly employed or contracted as science communicators or they engage in science communication as part of their job, whether they are under contractual obligation to do so or do so of their own volition. In other words, it appears that science communication in Quebec remains more institutionally formalized than elsewhere in Canada, with,

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some might say, a more traditional structure of employment (Schiele and Riedlinger 2018). This reality translates into the opinions expressed by online science communicators in Quebec, who overwhelmingly point to full-time permanent science journalists or science communicators working for major media outlets as examples of who is doing ‘good’ science communication. In fact, the most successful Quebec-based online science communicators have been shown to make the transition to more traditional Quebec-based media, print and, more generally, television. This situation also stems from the difficulty of establishing and sustaining a specifically francophone online presence from a Quebec perspective. The French language on the internet can be likened to ‘a French rose in an English garden’ in view of the history of the development of the internet and the global position of the United States, which skewed its architecture and use towards English. In March 2020, nearly 60% of global internet pages were in English, while pages in French accounted for only 2.8% of the total.8 The francophone internet is also clearly skewed towards France, with its 67 million population and strong centralized state heavily backing science communication. Smaller francophone nations have actively resisted the pull of both the English language and a France-oriented francophone internet for a long time through the promotion of local actors and local issues (OIF 2005). However, as mentioned above, the Quebec Government has since the turn of the 2000s taken a step back from the promotion of science communication. With the exception of online science communication activities supporting the mandates of institutions or occurring as part of the wider communication strategy of institutions, most online science communicators in Quebec work on their own time and with their own resources. However, they cannot be categorized as entrepreneurs endeavouring to make a living from their online science communication activities. They can be thought of as a pool of candidates, and potential commentators, for traditional media to draw on. The two best examples of this phenomenon are the Pharmachien and the Nutritionniste urbain.

5.4.2 The Most Popular Social Media Science Communicators in Quebec Le Pharmachien—a pun on the French words for pharmacist (pharmacien) and dog (chien)—is the alias of Olivier Bernard, a Montreal-based online science communicator since 2012. He has a website (www.lepharmachien.com; for the English version, www.thepharmafist.com), a Twitter account (@lepharmachien) with 24,300 followers, an Instagram account (le.pharmachien) with 22,600 followers, and a Facebook account (@lepharmachien) with 245,015 followers. Bernard is a pharmacologist who covers a wide range of science topics and debunks pseudoscience claims, 8

Historical trends in the usage of content languages for websites, W3techs.com, March 2020, https://w3techs.com/technologies/overview/content_language.

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with a focus on nutrition and health. He made the transition to more traditionally based media by publishing compilations of his online posts in book form. Since 2016, he has produced an animated TV show on Radio-Canada (the francophone equivalent of the Canadian Broadcasting Corporation): Les Aventures du Pharmachien (The Adventures of the Pharmadog), now in its fourth season. He has been awarded the Prix Sceptique des Sceptiques du Québec (Sceptic Prize of the Quebec Sceptics) in 2014, the Prix Innovation de l’Ordre des Phamarciens du Québec (Innovation Award of the Order of Pharmacists of Quebec) in 2015, and more recently the John Maddox Prize jointly awarded by British-based Sense about Science and the scientific journal Nature, in 2019. Le Nutritionniste Urbain (the Urban Nutrionist) is the alias of Bernard Lavallée, a Montreal-based online science communicator since 2014. He has a website (nutritionnisteurbain.ca), a twitter account (@b_lavallee) with 3,552 followers, an Instagram account (nutritionnisteurbain) with 23,500 followers and a Facebook account (@nutritionnisteurbain) with 90,879 followers. Lavallée is a nutritionist who focuses on sustainable nutrition, urban agriculture, food marketing and the environment and debunks fad diets. He has published an illustrated guide for environmentally sustainable nutrition (2015) and a critical introduction to fad diets (2018). In 2019, he made the jump to more traditional media, becoming a commentator on Moi j’mange (I eat; a Télé-Québec programme), and a radio columnist on Moteur de Recherche (Search Engine; a Radio-Canada Première Chaine radio programme on science and technology), and a contributor to two Quebec-based nutrition and cooking magazines. Other examples include of online science communication in Quebec include the following. Jean-François Cliche has been a science journalist at the Quebec City-based newspaper Le Soleil since 2007 and a columnist for the Montreal-based Québec Science magazine since 2015. He has had a Twitter account (@clicjf) since 2012, with 5231 followers. Agence Science-Presse is a Montreal-based press agency founded in 1978 with the express purpose of providing science news to the Quebec public. It went online in 1996 (www.sciencepresse.qc.ca) and ranks among the longest running francophone online science information websites. It has had a Twitter account (@SciencePresse) with 31,500 followers since 2009 and has a Facebook account (@AgenceSciencePresse) with 13,687 followers. Québec Science is a Montreal-based science magazine and, founded in 1962, the oldest continuously running science magazine in Quebec. It was the first Quebecbased medium to go online in 1995 (https://www.quebecscience.qc.ca). It has had a Twitter account (@QuebecScience) with 68,100 followers since 2019 and has a Facebook account (@QuebecScience) with 19,593 followers. Les Débrouillards (The defoggers) is a Montreal-based youth science magazine founded in 1978 under the name Hebdo Science. During the 1980s, the editors launched a successful series of science communication books, which became a

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science communication movement. Les Débrouillards has since become internationalized with branches in a dozen countries, five of them francophone. From 1990 to 2003, it ran a successful TV programme under the same name on RadioCanada. It launched a website in 1996 (https://www.lesdebrouillards.com). It has had a Twitter account (@debrouillards) with 3859 followers since 2009, a Facebook account (@debrouillards) with 10,625 followers, and an Instagram account (debrouillards) with 1218 followers. It also has a YouTube account (Débrouillards) with 5900 followers, on which are uploaded original videos of fun and safe experiments for children.

5.5 ‘Good’ Science Communication in Canada In our surveys, we asked professional association (SWCC and ASC) members and social media science communicators to tell us what makes ‘good’ science writing or communication. We conducted a thematic analysis of the open-ended responses we received to this question and we present the findings in Table 5.1. The top five attributes of ‘good’ science communication that social media science communicators valued were engagement, relevance, writing quality, accessibility and accuracy. Engagement and accuracy were two of the top five attributes valued by all three science communicator groups we surveyed. For social media communicators, the verb ‘engage’ was often used to signal dialogic communication and active user involvement. For example: Communication requires discussion, not one-way transmission of information, so engaging with your readers is key. … provide a way for that audience to engage rather than be informed alone. Participants in the social media survey group also used ‘engaging’ as an adjective to describe writing that they valued because the writer could distil complex ideas. For example: The ability to deconstruct the intricacies of a natural mechanism into a considered and engaging piece of writing. Social media communicators valued accuracy in relation to the ability of ‘good’ communication to engage and inform the publics: … to engage the public’s interest without a loss of scientific accuracy in the communication/writing. … maintaining the accuracy of the information without ‘dumbing it down’. Social media group survey participants included an additional attribute related to ‘good’ science communication: supporting ‘inclusivity’. Diversity was valued in relation to the ability of ‘good’ science writing and communication to be inclusive and overcome marginalization. For example: … engaging with diverse audiences so that they see themselves included. Impact on reach and diversity (including the voices of women in STEM, people of colour in STEM, marginalized voices in STEM, as well as communicating research and information that affects marginalized communities).

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Table 5.1 A comparison for values derived from a thematic analysis of the question, ‘What makes good science writing and/or science communication?’ Values

Social media communicators

SWCC members

ACS members

(n = 65)

%

(n = 124)

%

(n = 73)

%

Engagement

33

51

31

25

9

12

Relevance

32

49

32

26

6

8

Writing quality

28

43

40

32

4

5

Accessibility

22

34

15

12

8

11

Accuracy

15

23

30

24

9

12

Narration

15

23

22

18

5

7

Audience focus

13

20

29

23

15

21

Entertainment

6

9

18

15

9

12

Factual integrity

5

8

6

5

12

16

Motivating action

5

8

8

6

5

7

Respect

4

6

6

5

0

0

Informative

4

6

4

3

0

0

Visual quality

4

6

4

3

1

1

Inclusivity

3

5

0

0

0

0

Impartiality

2

3

2

2

1

1

Independence

2

3

3

2

0

0

Transparency

1

2

1

1

0

0

Vulgarization

0

0

0

0

10

14

Totala

194

299

251

202

94

127

a Total

add up to more than 100% because respondents could include more than one theme

Only ACS members used the term ‘vulgarisation’ to describe ‘good’ science writing and communication. However, vulgarisation is merely the French-language equivalent of ‘science communication’. For example: Rigueur scientifique et bon niveau de vulgarisation pour atteindre efficacement le public visé. [Scientific rigour and good level of vulgarization to efficiently reach the target audience.] S’adresser au public dans un langage qu’il comprend bien, expliquer des concepts complexes avec des mots simples. Bien vulgariser, quoi. [Talk to the public in a language it understands, explain complex concepts in simple words. To vulgarize efficiently, in other words.]

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5.6 Future Directions for Science Communication in Canada In this chapter, we have described efforts to map online science communication in Canada and to gain a better understanding of the emerging activities of online science communicators and what they value. Our social media mapping work shows that the Canadian science communication landscape is rich with innovative online practices, particularly in areas associated with conservation advocacy, women in STEM, science-art and combating misinformation. The niche for ‘scientist communicators’ and other social media communicators who might not describe their profession as ‘science communication’ is growing. We are observing concurrent streams of science communication activity with only some overlap between professional and informal networks, and only some communicators making a transition to what has traditionally been considered to be science communication. The popularity of social media networks and professional development activities aimed at scientist communicators, such as the ComSciCom workshop at McMaster University and ScicommTO at Ryerson University. demonstrate that the informal science communication community is a growing one. In March 2020, Julia Krolik, Executive Officer from Art the Science, a not-for-profit organization supporting connections between art and science, started a Slack networking group to bring together the Canadian #scicomm community. By January 2021, the group had 392 members and channels devoted to events, scicomm resources, equity and inclusiveness, Covid-19, sci-art and critiques. Members of this network identify themselves as outreach facilitators, researchers, writers, podcasters, educators, knowledge translators, illustrators, graduate students, illustrators, filmmakers, performers, social media communicators and game developers. Moving beyond professional member networks to focus on online networking will be a new direction for many professional associations supporting science communicators, but will be an important approach to consider, given the heterogeneous online environment in which emerging initiatives are meeting people’s desire to stay informed in their own time and at little or no cost to themselves. Researchers of science communication could also contribute to better understanding the place of online networking for science communication practice and the implications of online networking for the professional development of science communicators. Social media communicators in our study valued engagement, relevance, writing quality, accessibility and accuracy as markers of ‘good’ science writing and communication. Professional organizations have always provided professional development and peer recognition as ways to promote and celebrate those shared values. Our findings show that at least some social media communicators are driven by the desire to promote inclusiveness and equity in their writing and communication. Researchers could look more closely at emerging communication practices associated with Indigenous science, women in STEM, people of colour in STEM, LGBTQ+

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in STEM, DIY/STEM maker culture, and open science movements. The motivations of communicators in those areas will be important to consider for professional development and recognition activities. Medvecky and Leach (2019: 42) argue that ‘good’ science communication cannot be regulated from outside because it happens in particular contexts in which the ‘values of science, science communication and audiences align’. Researchers would also benefit from looking more closely at how social media science communicators in Canada are negotiating the often competing values of their communities to better understand where innovation in this field is happening and where institutional support might nurture it. Professional associations in Canada and elsewhere could also play important roles as advocates in this space. Future research in this area could help to identify where efforts are most needed by gathering data from institutional research managers, who can influence the strategic direction of science communication through policies and funding, on what they believe makes ‘good’ science communication. Acknowledgements This work was supported by a Social Science and Humanities Research Council (SSHRC) Partnership grant (892-2017–2019) held by Juan Pablo Alperin at Simon Fraser University (SFU), Michelle Riedlinger at the University of the Fraser Valley (UFV) and Science Writers and Communicators of Canada (SWCC). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. We are grateful for the continued support of Juan Pablo Alperin from the School of Publishing at SFU and the assistance of Shelley McIvor, Janice Benthin and Tim Lougheed from SWCC and Stéphanie Thibault from the Association des Communicateurs Scientifiques du Québec.

References Barel-Ben David Y, Garty ES, Baram-Tsabari A (2020) Can scientists fill the science journalism void? Online public engagement with science stories authored by scientists. Plos one 15(1):e0222250 Boon S (2017) Science funding in Canada should include science communication. Watershed moments: thoughts from the hydrosphere. https://snowhydro1.wordpress.com/2017/09/13/sci ence-funding-in-canada-should-include-science-communication/ Bruns A, Highfield T, Lind RA (2012) Blogs, Twitter, and breaking news: The produsage of citizen journalism. In: Lind RA (ed) Produsing theory in a digital world: the intersection of audiences and production in contemporary theory, vol 80, Digital Formations. Peter Lang Publishing, pp 15–32 Burns TW, O’Connor DJ, Stocklmayer SM (2003) Science communication: a contemporary definition. Public Underst Sci 12(2):183–202 Bucchi M (2013) Style in science communication. Public Underst Sci 22(8):904–915 Bucchi M (2017) Credibility, expertise and the challenges of science communication 2.0. Public Underst Sci 26(8):890–893 CEFRIO (2018) L’usage des médias sociaux au Québec, NETendances 9(5). https://cefrio.qc.ca/ media/2023/netendances-2018_medias-sociaux.pdf Chen A (2018) Scolding female scientists for embracing Instagram doesn’t solve the gender gap in STEM. The Verge, 16 May. https://www.theverge.com/2018/3/16/17128808/scicomm-genderdiversity-women-stem-instagram

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Davies SR, Horst M (2016) Science communication: culture, identity and citizenship. Springer, Berlin Dawson E (2014) ‘Not designed for us’: how science museums and science centers socially exclude low-income, minority ethnic groups. Sci Educ 98(6):981–1008 Dawson E (2019) Equity, exclusion and everyday science learning: the experiences of minoritised groups. Routledge, London Gordon B (2018) Instagram should not be dismissed for scicomm. Science, 29 March. https://sci ence.sciencemag.org/content/instagram-should-not-be-dismissed-scicomm Hermida A (2019) The existential predicament when journalism moves beyond journalism. Journalism 20(1):177–180 Irwin A, Horst M (2016) Communicating trust and trusting science communication-some critical remarks. J Sci Commun 15(6):L01 Jarreau PB, Cancellare IA, Carmichael BJ, Porter L, Toker D, Yammine SZ (2019) Using selfies to challenge public stereotypes of scientists. PLoS ONE 14(5):1–23 Marks GS (2018) A scientist responds to that ‘Science’ Instagram essay. Massive Science, 20 March. https://massivesci.com/articles/instagram-science-sam-women-representation/ Medvecky F, Leach J (2019) An ethics of science communication. Springer Nature Metcalfe J, Riedlinger M (2020) Public understanding of science: popularisation, perceptions and publics. In: Gruber DR, Olman LC (eds) The Routledge handbook of language and science. Routledge, Abingdon, Oxon, pp 32–46 Nisbet M (2017) Ending the crisis of complacency in science. Am Sci 105(1):18–20 OIF (Organisation international de la francophonie) (2005) La Charte TV5. https://www.bakom. admin.ch/dam/bakom/fr/dokumente/ir/internat_akt/charta_von_tv5_monde.pdf.download.pdf/ charte_tv5_monde.pdf Peters HP (2014) Scientists as public experts: expectations and responsibilities. In: Bucchi M, Trench B (eds) Routledge handbook of public communication of science and technology. Routledge, pp 86–98 Pitre R (1994) La culture scientifique et technique et les politiques scientifiques au Québec: le rôle de l’OCDE, In: Schiele B (ed) When science becomes culture, Proceedings II, Multimondes, Sainte-Foy Riedlinger M, Barata G, Schiele A (2019) The landscape of science communication in contemporary Canada: a focus on anglophone actors and networks. Cultures Sci 2(1):51–63. https://doi.org/10. 1177/209660831900200105 Schiele A, Riedlinger M (2018) Science communication in Canada: initial findings from a survey of ACS affiliates and their communication activities, A report for the Association des communicateurs scientifiques du Québec. University of the Fraser Valley Shapiro A (2020) Looking back: a d of Canadian science communication. https://medium.com/ @alanyshapiro/looking-back-a-decade-of-canadian-science-communication-79afd8431afd Strapagiel L (2018) These women scientists refuse to stop taking selfies for science. Buzz Feed News, 23 April. https://www.buzzfeednews.com/article/laurenstrapagiel/women-scientistsselfies Van Dijck J, Poell T (2013) Understanding social media logic. Media Commun 1(1):2–14 Weingart P, Taubert N (2017) The future of scholarly publishing. African Minds, Cape Town Wright M (2018) Instagram won’t solve inequality. Science 359(6381):1294–1294 Yammine SZ, Liu C, Jarreau PB, Coe IR (2018) Social media for social change in science. Science 360(6385):162–163 Zaringhalam M, Vijayaraghavan R, Simonis J, Ramirez K, Zelikova J (2018) Journal editors should not divide scientists. Science 360(6385):163–164

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Michelle Riedlinger (Ph.D., University of Queensland, 2005) is a chief investigator in the Digital Media Research Centre and a Senior Lecturer in the School of Communication at the Queensland University of Technology, Australia. She has worked as a science and environmental communicator for over 20 years. That professional experience developed her interest in online science communication and evidence-informed public advocacy. Her research focuses on public engagement in science and technology and on and environmental and health science writing. She is currently investigating science–society relationships and public risk assessment in online science communication environments in Canada and Australia. She is the secretary for the Public Communication of Science and Technology (PCST) Global Network. Alexandre Schiele is a postdoctoral researcher at the Hebrew University of Jerusalem, Israel. He holds a PhD in communication science (Sorbonne Paris Cité, 2017) and another in political science (University of Quebec at Montreal, 2018). He pursues his research in two distinct directions. On the one hand, he studies science communication in the media, and has contributed to the Mapping the New Communication Landscape in Canada project (2017–2018). On the other hand, he studies classical and contemporary Chinese political thought. Among his latest publications, of note is Pseudoscience as media effect (2020). Germana Barata (Ph.D., University of São Paulo, 2010) is a researcher in science communication at the Laboratory of Advanced Studies in Journalism (Labjor) at the State University of Campinas (Unicamp), Brazil. She was a visiting scholar at the Simon Fraser University (SFU, 2017–18) and is a collaborator of the ScholCommLab at SFU. She has coordinated the Science Journalism course at Unicamp since 2018, and her research has focused on science communication, social media, altmetrics and scholarly communication. She took part in the scientific committee of the Public Communication of Science and Technology (PCST) Global Network (2018–2021) and is a member of the Board of the Brazilian Association of Science Editors (ABEC) in Brazil (2020–2022).

Part II

Science–Society Dynamics

Chapter 6

Meeting the Needs of Society: Experiences from Practices at the Science–Society Interface Anne M. Dijkstra

Abstract The notion of science demonstrating responsibility to society by meeting the needs of society is key in current policymaking. Under the label of ‘responsible research and innovation’, many projects have been funded to study and stimulate practices of responsible science–society relationships, both within and outside Europe. Those projects collected insights into what constitutes a responsible science–society relationship and indicated how changes in that relationship are evolving, such as the roles and responsibilities of researchers and research institutes. In this chapter, findings are discussed to provide a broader and enriched cultural and international perspective on the changing science–society relationship. More specifically, results are derived from case studies in the Netherlands, South Africa and China. Keywords Science-society relationship · Responsible innovation · Science communication · Roles for researchers · Practices of responsible research and innovation

6.1 Introduction In November 2018, citizens from 11 households in the city of Enschede in the Netherlands met with two researchers from the University of Twente and Saxion University of Applied Sciences, a civil servant from the city, a salesman from the company VRM and two volunteers from the civil society organization Things Network Twente. The team of experts and the citizens talked about an urgent issue for the citizens, which had received coverage in the local newspaper in February 2018. In Enschede, rising groundwater levels cause many problems for private houses. Along with gardens being too wet, cellars regularly overflow, and water enters homes and persists in cellars for long periods. Flooding leads to mildew on walls, and some occupants develop respiratory problems. In recent years, this inconvenience has increased considerably. No standard solution is available, the responsibilities of local A. M. Dijkstra (B) Science Communication, University of Twente, Enschede, The Netherlands e-mail: [email protected] © China Science and Technology Press 2021 B. Schiele et al. (eds.), Science Cultures in a Diverse World: Knowing, Sharing, Caring, https://doi.org/10.1007/978-981-16-5379-7_6

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government regarding groundwater levels in domestic dwellings are limited, and no governmental interventions are possible, at least formally. The meeting of the group of experts and citizens was the beginning of a pilot project aiming to explore whether and how measuring groundwater levels with sensors enabled with ‘internet of things’ (IoT) technology could help the citizens to find tailor-made solutions for their problem (Dijkstra et al. 2019). The MerriamWebster dictionary describes the IoT as: ‘the networking capability that allows information to be sent to and received from objects and devices (such as fixtures and kitchen appliances) using the Internet’. In other words, the sensors were controlled via internet connections and measures could be read from citizens’ own devices. In this chapter, I explore at the science–society interface what meeting the needs of society means in practice. Insights have been collected from emerging practices in the Netherlands, South Africa and China. In particular, the examples explore what the practices mean for the communication process and the roles of the researchers and citizens involved. The examples were collected, among others, as part of a series of activities exploring broader and enriched cultural and international perspectives of responsible research and innovation (RRI) for an EU-funded project called NUCLEUS.1 NUCLEUS was a four-year project funded by the European Union through the Horizon 2020 Science with and for Society programme, which ran from 2014 until 2019. The acronym stands for New Understanding of Communication, Learning, and Engagement in Universities and Scientific Institutions. The project aimed to gather enriched perspectives on the notion of RRI. Therefore, in the first phase of the project, an analysis was conducted of the way in which the relationship between science and society was shaped in various contexts; in the second phase, activities to foster the relationship were implemented at 10 universities and research institutes around the world. In the next section, I describe the theoretical framework on which this chapter builds. I then offer various examples in order to provide an analysis of experiences in which responsible science–society relationships are practised. The chapter ends with a discussion and conclusions and offers lessons learned for science communication.

6.2 A Theoretical Perspective on Responsible Science–Society Relationships Theoretical notions about the relationship between science and society are embedded within various research areas and include motivations for science communication, ideas about developments in science communication and recent deliberations about RRI. Regarding motivations for science communication, in particular in current times, it is acknowledged that science is part of our daily culture and that science communication is therefore important. For example, in many countries around the 1

NUCLEUS: Bringing RRI to life, www.nucleus-project.eu/.

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world, at the start of the COVID-19 outbreak, policy measures were taken with reference to scientific knowledge. Scientists translated scientific evidence into advice and possible actions for decision-making on dealing with the coronavirus. Politicians decided what to do with that knowledge, leading to diverse approaches to addressing the pandemic in various countries. Only with hindsight can it be known which measures have been successful and which kinds of scientific knowledge have been most usefully translated into measures. However, what is already clear is that communication about the (albeit scarce and still developing) scientific knowledge plays an important role in the current pandemic. Science communication influences our way of dealing with such matters and, more generally, plays a prominent role in any science–society relationship. Cultural motivations (science is around us and connected to society) as described above are an important rationale for science communication. In addition, economic motivations (communication is beneficial for the economy), substantive motivations (communication can improve the quality of life) and democratic motivations (citizens have the right to be informed about developments) constitute rationales for science communication (see, for example, Fiorino 1990; Wilsdon and Willis 2004). Indeed, science communication plays an important role in the current science– society relationship. On many of the contested issues in the twenty-first century, such as climate change, vaccination or artificial intelligence, that have developed at the interface between science and society, communicating about the science and technology behind those issues is considered key. While science and technology develop and are often considered beneficial for society, the complexity of the relationship between society and science and technology is also becoming clearer. This raises further questions about how to communicate, with whom, and the role of actors in the science–society relationship and the communication process. According to a report by the US National Academy of Sciences, Engineering and Medicine (NAS 2017), a greater understanding of those complex science–society relationships will help in communicating science more effectively. The report reviews the evidence about effective approaches to science communication and offers an agenda for possible future research in this area. It states that more knowledge and awareness of what communication can do or will do are needed as part of understanding the science–society relationship better, in addition to enhanced skills to help researchers in their communication about science and technology. Increasingly, developments in science communication place emphasis on the role and responsibility of researchers in communicating science, which, in turn, aligns with developments in thinking about RRI that reflect on the role of researchers, among others. Theoretical ideas about RRI have frequently been addressed in academic literature since the concept evolved, and the first experiences from RRI practices have been published (Schuijff and Dijkstra 2019), but the notion of RRI is still developing (see, for example, Burget et al. 2017). Both Arie Rip (2014) and Clare ShelleyEgan (2018) have described how notions about responsible innovation in the field of nanotechnologies were derived from strategies proposed in a report by the British Royal Society and Royal Academy of Engineering (RSRAE 2004). That report called

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for the promotion and implementation of a wider dialogue with all societal actors as an approach to the responsible development of nanotechnologies. At that time, it was not yet labelled ‘RRI’. Later definitions of RRI called for the inclusion of societal actors to advance the alignment of research and innovation outcomes with the needs and expectations of society (Stilgoe et al. 2013; Von Schomberg 2013; European Commission 2018; Owen et al. 2013). For example, according to the definition provided by Stilgoe et al. (2013: 1570), researchers are encouraged to open up to other voices such as those of stakeholders and the public by taking care and collective stewardship: Responsible innovation means taking care of the future through collective stewardship of science and innovation in the present. Von Schomberg (2013: 63) emphasizes RRI as an interactive and mutually responsive process in his definition: A transparent, interactive process by which societal actors and innovators become mutually responsive to each other with a view to the (ethical) acceptability, sustainability and societal desirability of the innovation process and its marketable products (in order to allow a proper embedding of scientific and technological advances in our society). The European Commission (EC 2018) declared that societal actors, such as researchers, citizens, policymakers, businesses and third sector organizations, should work together during the whole research and innovation process in order to align both the research process and its outcomes to the needs and expectations of society. To foster that alignment and make it more tangible, the commission emphasized five key dimensions of RRI. Public engagement is one, as are ethics, science education, gender and open access, while governance is a guiding principle. The European Commission has dedicated a considerable budget to exploring RRI and putting theory into practice. While De Saille (2015) acknowledged that the translation of the academic theory of RRI into the daily practice of European policy faces challenges because structures for meaningful exchanges between policy and practices are not yet in place, De Saille (2015) and other authors have also called for learning from practical perspectives of RRI. Current practices of RRI were analysed and mapped in a recent review study by Schuijff and Dijkstra (2019). In that study, practices could be categorized as follows. First, some practices explore inclusion or opening up research and innovation to all stakeholders through, for example, science education and outreach. Second, practices can stimulate reflection at the start of or during the process via sharing insights or collecting knowledge. A third group of practices aim at managing ethical, legal and social issues of research and include various methods to enable the implementation of those issues. Finally, the fourth group of practices look at institutionalization, which can happen, for example, at the governance level or by applying soft or hard policy measures. The authors concluded that more understanding of which practices are suited for which circumstances can aid future practitioners in implementing RRI elements. Furthermore, additional reflection on implementation will contribute to advancing the theoretical development of RRI, while learning from other practices is recommended (Schuijff and Dijkstra 2019).

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As Rip (2014) noted, better embedding of research and innovation in society is increasingly seen as part of the professional responsibility of researchers. It is part of thinking about the changing position of science and thus of researchers and research institutes in society, which is in itself part of a broader movement towards increased social accountability of professionals.

6.3 Practices of Science–Society Interactions in the Netherlands In this section, I discuss findings from three RRI practices in the Netherlands and distil lessons to be learned from them.

6.3.1 The Groundwater Pilot Project The first example is the groundwater pilot project, which applied IoT technology to investigate how experts might guide citizens in searching for ways to tackle rising groundwater levels (Dijkstra et al. 2019). Throughout the project, and after the initial meeting, in parallel with a series of experts–citizens meetings, a survey was conducted in which citizens from the wider area were asked to report on their experiences with rising groundwater levels, their willingness to be involved in participatory solutions and their possible roles in those solutions. The results of both studies were presented during a public meeting attended by the project participants, media, policymakers, decision-makers and other citizens. In the project, both the experts and the citizens started a journey exploring how expert knowledge could help citizens with their problems; in this sense, this was about meeting the needs of society. However, in the end, it also worked the other way around. The experts started with expectations, which they had to adapt. For example, implementing IoT technology in the measurement instruments was not as easy as initially anticipated. The experts needed the input of citizens to design the instruments in a way that was appropriate for the citizens. Moreover, development of the software by the volunteers of the Things Network Twente took more effort and time than expected. This aspect of mutual learning and mutual engagement may have been a reason why, after the pilot phase, both groups continued working together to further explore how to make the most out of the mutual knowledge they were building up. It is remarkable that, two years after the pilot project, the original group of citizens still meets with some of the experts to continue working on means to deal with their groundwater issues. From a community of practice perspective, both groups of actors were involved in a joint enterprise in which they mutually engaged and were working on gaining a shared repertoire of knowledge (Wenger 1998).

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6.3.2 The Think Tank Event A second example is the organization of a Think Tank event in the summer of 2018 to discuss the topic of universities’ engagement with society, and in particular with the region (Fonseca et al. 2018). This event was organized as part of a summer school that took place at the University of Twente. The organizers contributed to the event on behalf of two EU-funded projects: the RUNIN project2 and the NUCLEUS project. The event used a world café format in which six tables were moderated by PhD students. Each of the 40 participants discussed three out of six questions in three rounds of discussion. The six questions explored, first, how the university can connect societal considerations in research and teaching, and, second, how the university can facilitate questions from society and, in particular, regional actors. Participants’ backgrounds varied. They ranged from first-year students to professors from the University of Twente and the University of Applied Sciences. They had international backgrounds and came from different research areas. Other participants had backgrounds as policymakers and politicians and included the mayor of a regional municipality, representing all of the mayors of the surrounding cities. After the three rounds of discussion, plenary reporting of each table was followed by a Q&A session and a public response from the mayor. After the event, a full report of the event, including an analysis of the discussions, was written and presented to the board of the University of Twente and other relevant stakeholders (Fonseca et al. 2018; Ahoba-Sam et al. 2019). The main conclusions from the report were that incorporating societal interests in teaching and research activities is seen as primarily a responsibility of the university itself. Establishing a culture of engaging with society requires approaches that operate both top down and bottom up and should be supported at strategic and operational levels by both individual staff and students. Although a number of mechanisms are already in place to foster and improve societal engagement, the university could further foster such mechanisms in the region. At the individual level, researchers and students are often not aware of current possibilities for incorporating societal activities in their research, while citizens and civil society organizations are not well connected to the university. Additional internal and external communication efforts could help (Fonseca et al. 2018). Furthermore, to facilitate societal engagement, a university should be supported by other regional stakeholders, including local governments, industry, local media, civil society organizations and citizens. However, the discussions at the Think Tank event showed the complexity of including those different societal partners and their varied interests and the means needed to enable societal engagement. According to the participants in the event, engagements need to be based on strong commitment from all contributing actors, need to be accessible, need to build trust and should

2

The Role of Universities in Innovation and Regional Development (RUNIN), https://runinproj ect.eu/.

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be facilitated by two-way communication. They also argued that a sustainable relationship among stakeholders requires a collaboration in which power structures are balanced (Fonseca et al. 2018; Ahoba-Sam et al. 2019).

6.3.3 The Development of Training Material A third example is the development of training material to stimulate reflection about science and society and the role of researchers in both. First, for students who are admitted to a research honours programme at the master’s level, a course of five European credits (140 h) was developed. The course aims to stimulate their thinking about their future role as researchers and increase their knowledge of and insight about communication processes in relation to innovation and research and about the scientific conduct of researchers. Therefore, students are encouraged to consider developments in science communication as well as in RRI and broader aspects related to science and society. In addition, they reflect upon ways of communicating about (emerging) scientific and technological knowledge and the kinds of roles and responsibilities researchers and research institutes can have in the science–society relationship. They learn about and discuss the main theoretical concepts and apply their insights in a written essay about the positions they envisage for researchers and their research institutes in current times. They also develop their communication skills by writing and presenting a communication plan, in pairs, about their own research projects. Each year, about 15 students participate. The course is part of the research honours programme at the university, to which a limited number of students from different master’s programmes and research backgrounds are admitted. In this rich and varied context, students learn to understand multiple perspectives on research and research practices. Other training material that was developed included a training module of 1.5 European credits (42 h) on the topic of academic integrity. The module is for Ph.D. students and aims to raise their awareness and increase their knowledge about academic integrity. After three introductory in-person lectures, the students follow 10 units online in which different aspects of academic or scientific integrity are presented and discussed. Their knowledge is assessed with quizzes, while they also contribute to a discussion board. At the end of the units, the students collect and describe a case of academic misconduct from their own research area, which they discuss in a focused group discussion with Ph.D. students from other research fields. Due to coronavirus restrictions, this face-to-face discussion has been transformed into a written assignment. The board of the university has made the module mandatory for all new Ph.D. students, which means that every year about 250–300 students participate. Both the master’s course and the Ph.D. training module have become institutionalized at the university and are supported by top management. In addition, basic training about academic integrity, not only for those new in the field but also for their supervisors and those at senior levels, has recently been developed and offered. Both

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training modules are examples of practices to stimulate students’ reflection on their research areas and research more broadly and to enhance their skills in dealing with society.

6.4 Practices from Outside Europe Both South Africa and China were the stage for two other NUCLEUS studies to enrich and contextualize RRI. Findings from both practices are discussed in this section.

6.4.1 South Africa The South African Institute for Aquatic Biology (SAIAB) explored how science engagement and communication could contribute to putting RRI into practice in South Africa (Haworth and Dijkstra 2019). The South African approach to RRI translated the European Commission’s five key RRI practices into six ways in which RRI can be put into action (DST 2019). The engagement of all societal actors throughout the process of framing societal challenges and developing joint solutions is one such approach. Another approach is maintaining a high level of ethics. Developing the required governance framework to drive the RRI agenda will help to institutionalize the South African approach. South Africa was also one of the studied contexts in the NUCLEUS project in which, among others, the perspective of civil society was considered by means of interviews during a field trip to South Africa (Doran 2016). Outcomes showed enthusiasm for engagement with civil society actors by museum staff and educators. In addition, the interviewees reflected that taking up these tasks was only possible within their job roles and when budgets were available. The interviews highlighted that striving for diversity and access to education was challenging. A key question concerned how existing science–society relationships can be brought to the next level to embrace responsibilities within limited budgets. At the same time, researchers and civil society can engage fruitfully via citizen-science projects, which was demonstrated by the Cradle of Humankind project, in which researchers aimed for mutual learning outcomes by means of an open approach to social media and a coordinated communication effort to gain global coverage of the research. One conclusion from the interviews was that such engagements should be mutually beneficial (Doran 2016; Haworth and Dijkstra 2019). At SAIAB, involvement in the NUCLEUS project stimulated researchers’ longrecognized responsibility to contribute to awareness and action towards sustaining biological diversity. To that end, closer working relationships between its researchers were further developed and communication processes were improved. The project enabled better articulation of RRI elements in the institute’s strategy. Elements such

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as diversity and dealing with inequality stimulated collaborations with other actors, and, with that, continued work on strengthening science–society relationships. In all, the project enabled SAIAB to build on its strengths, share its findings and learn from others’ experiences. It also enabled involvement in follow-up projects, further stimulating the translation of RRI elements into practice (for further details, see Haworth and Dijkstra 2019).

6.4.2 China China was also included in the NUCLEUS studies to explore practices of RRI. A field trip to Beijing with an emphasis on public engagement was organized, and a cultural adaptation study that considered the take-up of society’s needs in the Chinese context was conducted (Dijkstra et al. 2017; Dijkstra and Yin 2019; Mordon and Skeldon 2016). The field trip included visits to the science museum and science festival in Beijing and a round-table conference. The trip was organized by the Beijing Association of Science and Technology and the China Research Institute for Science Popularization. In addition to the visits, interviews were held with representatives from key organizations in Beijing dealing with engagement. The cultural adaptation study was based on a literature review of various sources (such as Ren and Zhai 2014) and semi-structured interviews with leading scientists, such as professors, associate professors, deans and directors (Dijkstra et al. 2017). The main findings from the cultural adaptation study showed that the concept of RRI has recently come into use in China, and responsibility is mainly conceptualized via researchers’ social responsibility. Research should serve society and advance societal progress. In China, science popularization is the tool for showing such responsibility and is highly stimulated by the Chinese Government, as shown in policy documents. Turnheim et al. (2014) noted that, next to science education and public engagement, other key elements, such as research ethics are increasingly attracting attention by means of codes of conduct. At the institutional level, stimulating scientific literacy through science popularization and communication is supported by the research institutes. Offices of science communication are tasked with this work. Science museums, exhibitions and various other facilities have tasks in science communication, while media channels, such as television and newspapers, also popularize science in various ways. Ren and Zhai, in their overview of science communication and popularization (2014), stressed that it is also important to train researchers in science communication. Additionally, in the interviews from the cultural adaptation study, respondents said that research institutes and universities could provide researchers with platforms for science communication and online courses or training programmes to support them in the development of communication skills. The respondents supported the idea that researchers have a responsibility to participate in science communication (Ren and Zhai 2014; Dijkstra and Yin 2019), and processes for research could be improved to better enable researchers to communicate their research.

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The Institute of Wetlands Research was included as one the research institutes implementing RRI practices. It organized, among other things, a science communication festival on Beijing Wetland Day, an exhibition and a science communication salon. The importance of transdisciplinary research in new projects was acknowledged, while researchers were informally recognized for bringing RRI into practice in their activities. The institute aims to build bridges between the research community, stakeholders, the general public and, in particular, local government (Genome Research Ltd et al. 2019).

6.5 Discussion and Conclusions: Reflection on Practices Examples of practices from the Netherlands, South Africa and China reveal that researchers in different situations are becoming more aware of their responsibilities as researchers towards society. They engage with society, are involved in science education and communication and reflect on ethical conduct at the beginning of projects or during their research. Research institutes and universities play a role in those processes and are fostering opportunities to communicate and engage with groups in society in various ways. Supportive training is offered to enable researchers to enhance their skills in engaging with publics and to stimulate reflection about their stance vis-a-vis society. The examples show that the take-up of responsible innovation can take place in all RRI key areas, such as public engagement, science education and ethics. Moreover, take-up differs among the various countries, while changing responsibilities are recognized by researchers in all situations. Researchers both acknowledge that and take up RRI. While, for example, Cormick (2012) has argued that many researchers see engagement primarily as educating the public by means of communicating about their research, the examples here show that many researchers are open to reflection on their broader role in and towards society. According to Cormick (2012), engaging in many different ways and with many different publics is preferred. He adds that obtaining insights into as many different perspectives as possible and collating those findings to get a better picture of what the public wants, whom they trust and what they accept is important. That also applies to other key areas, such as ethical conduct. The examples provide insights into a broader cultural, international and enriched perspective on the changing science–society relationship, but further research is recommended. In line with the recommendations of the US National Academies of Sciences, Engineering and Medicine (NAS 2017), Wickson et al. (2010), and as Cormick (2012) has stated: ‘We need to develop more complex ways of viewing the public.’ Collecting a variety of possible practices of RRI will contribute to understanding the complexity of science–society relationships. For example, research could study in more detail how roles for actors develop in the science–society relationship, such as for journalists, but also for researchers and citizens. Other relevant topics for future research are, for example, how different frames support different views of technology. Also, more understanding of the role and position of scientific

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knowledge in the public domain can further aid our understanding of changes in the science–society relationship, as the current pandemic shows. Acknowledgements This chapter is based, among other projects, on work from the NUCLEUS project that was funded by the European Union in the Horizon 2020 Science with and for Society programme (grant agreement number 664932). The Think Tank event was organized as a collaboration between the RUNIN project and NUCLEUS. The groundwater pilot project was a collaboration between researchers from the University of Twente, Saxion Applied University, Things Network Twente, the municipality of Enschede and VRM, and was financially supported by Twente47 and the province of Overijssel. I thank Clare Shelley-Egan for her feedback on the manuscript.

References Ahoba-Sam R, Atta Owusu K, Evers G, Fonseca L, Kopelyan S, Meloyan A, Nguyen H, Salomaa M, Alpaydin U, Cinar R, Fernandez-Guerrero D, Germain-Alamartine E, Manrique S, MoghadamSaman S, Nieth L, Schuijff M (2019) Higher education institutes and the Twente Board: policy report. RUNIN Working Paper Series, no. 1. Centre for Higher Education Policy Studies, Enschede. doi: https://doi.org/10.3990/4.2535-5686.2019.01 Burget M, Bardone E, Pedaste M (2017) Definitions and conceptual dimensions of responsible research and innovation: a literature review. Sci Eng Ethics 23:1–19 Cormick C (2012) The complexity of public engagement. Nat Nanotechnol 7:77–78 European Commission (2019) Responsible research and innovation. https://ec.europa.eu/progra mmes/ horizon2020/en/h2020-section/responsible-research-innovation#Article De Saille S (2015) Innovating innovation policy: the emergence of ‘responsible research and innovation.’ Journal of Responsible Innovation 2:152–168 Dijkstra A, Heerink R, Van Den Berg M (2019) Pilot Samen grondwaterpeilen. Rapportage onderzoek WP4. Universiteit Twente, Enschede Dijkstra AM, Schuijff M, Yin L, Mkansi S (2017) RRI in China and South Africa: cultural adaptation report. University of Twente, Enschede Dijkstra AM, Yin L (2019) Insights from China for a global perspective on a responsible science– society relationship. Cultures of Science 2:65–76 Doran H (2016) NUCLEUS field trip report: civil society (Pretoria). Deliverable 4.4. University of Aberdeen, Aberdeen DST (Department of Science and Technology) (2019) White Paper on Science, Technology and Innovation: science, technology and innovation enabling inclusive and sustainable South African development in a changing world. Pretoria, Republic of South Africa, Department of Science and Technology Dublin City University, Genome Research Limited, Science View, University of Delft, RhineWaal University (2019) Final recommendations: institutionalised nuclei for RRI. Deliverable 5.5, NUCLEUS project Fiorino DJ (1990) Citizen participation and environmental risk: a survey of institutional mechanisms. Sci Technol Human Values 15:226–243 Fonseca L, Manrique S, Nguyen H, Benneworth P, Atta-Owusu K, Alpaydin U, Cinar R, Evers G, Fernandez Guerrero D, Germain-Alamartine E, Kopelyan S, Meloyan A, Moghadam-Saman S, Nieth L, Salomaa M, Schuijff M (2018) Reconnecting the university to the region of Twente: findings from the RUNIN – Design Lab Think Tank Genome Research Ltd, Institute of Wetlands Research, Rhine-Waal University, Ruhr University Bochum, University of Malta, Dublin City University (2019) Embedded nuclei implementation report 1: China, Germany and Malta. Deliverable 5.4, NUCLEUS project

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Haworth PS, Dijkstra AM (2019) Putting responsible research and innovation into practice at a local level in South Africa. In: Weingart P, Joubert M, Falade B (eds) Science communication in South Africa: reflections on current issues. African Minds, Cape Town Mordan C, Skeldon K (2016) Field trip report: Beijing: RRI and public engagement. NAS (National Academies of Sciences, Engineering and Medicine) (2017) Communicating science effectively: a research agenda. National Academy of Sciences, Engineering and Medicine, Washington DC Owen R, Stilgoe J, Macnaghten P, Gorman M, Fisher E, Guston D (2013) A framework for responsible innovation. In: Owen R, Bessant J, Heintz M (eds) Responsible innovation: managing the responsible emergence of science and innovation in society. John Wiley & Sons Ltd, Chichester Ren F, Zhai J (2014) Communication and popularization of science and technology in China. Springer, Berlin, Heidelberg Rip A (2014) The past and future of RRI. Life Sciences, Society and Policy 10:17 Schuijff M, Dijkstra AM (2020) Practices of responsible research and innovation: a review. Sci Eng Ethics 26:533–574. https://doi.org/10.1007/s11948-019-00167-3 Shelley-Egan C, Bowman DM, Robinson DKR (2018) Devices of responsibility: over a decade of responsible research and innovation initiatives for nanotechnologies. Sci Eng Ethics 24:1719– 1746 Stilgoe J, Owen R, Macnaghten P (2013) Developing a framework for responsible innovation. Res Policy 42:1568–1580 Von Schomberg R (2013) A vision of responsible research and innovation. In: Owen R, Bessant J, Heintz M (eds) Responsible innovation: managing the responsible emergence of science and innovation in society. John Wiley & Sons Ltd, Chichester Wickson F, Delgado A, Kjølberg KL (2010) Who or what is the public? Nat Nanotechnol 5:757 Wilsdon J, Willis R (2004) See-through science: why public engagement needs to move upstream. Demos, London

Anne M. Dijkstra (Ph.D.) is an assistant professor in Science Communication at the University of Twente in the Netherlands. She studies the changing science–society relationship from a communication perspective. Her studies often relate to emerging technologies. She is editor of Science communication: an introduction (2020) and wrote the Dutch chapter in Communicating science: a global perspective (2020). She is involved in European funded projects, such as, ENJOI (101006407; 2021–2023); RRI2SCALE (872526; 2020–2022); NUCLEUS (664932; 2015–2019) and GoNano (768622; 2017–2020). Anne was a visiting researcher at Newcastle University and a visitor at the Institute of Advanced Study at Durham University. She teaches courses about science communication, science journalism and responsible innovation. Prior to her academic work, she was a science communication adviser. She is a volunteer at Science Café Deventer.

Chapter 7

Science Communication in Nigeria and South Africa: Beliefs, Social Groups and the Social Space of Science Bankole Adebayo Falade and Refilwe Mary-Jane Ramohlale

Abstract Science communication addresses a diversity of social groups within and across nation-states. Some of those groups are manifest, while others do not exist as real groups but can explain the probability of individuals constituting themselves as ‘practical groups’ in what Pierre Bourdieu describes as a ‘symbolic’ social space. This chapter uses data from the World Values Survey (Wave 6) to construct the social space of attitudes to science in Nigeria and South Africa. It also uses case studies from across Africa to highlight the role of beliefs and social groups in the diffusion of science and the diversity of science communication activities in both countries. The case studies show that religion can have an initial influence on the take-up of science, evidencing the impact of prior beliefs and a defence of the group in the adoption of the unfamiliar, but that influence is not permanent. The differences in the composition of the three factors in the reduction of the attitude variables for both countries and the different levels of coexistence of social groups with science and ‘progress’ are indicative of cultural differences in the public understanding of science in both countries. The bi-plot of social space also shows the proximity of different manifest and ‘practical’ groups to increasing levels of attitudes to science as ‘progress’ and is indicative of the coexistence of science and religion. These differences in the two countries and across social groups indicate the need to vary science communication approaches to meet local peculiarities and needs. Keywords Social groups · Social space · Social representations · Science communication · South Africa · Nigeria

B. A. Falade (B) Centre for Research On Evaluation, Science and Technology (CREST), Stellenbosch University, Stellenbosch, South Africa Department of Psychological and Behavioural Sciences, London School of Economics and Political Science, London, UK R. M.-J. Ramohlale Science Education Centre, School of Physical and Mineral Sciences, Faculty of Science and Agriculture, University of Limpopo, Limpopo, South Africa e-mail: [email protected] © China Science and Technology Press 2021 B. Schiele et al. (eds.), Science Cultures in a Diverse World: Knowing, Sharing, Caring, https://doi.org/10.1007/978-981-16-5379-7_7

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7.1 Introduction Science is a global affair, but science culture is local (Bauer et al. 2018). Therefore, understanding the ‘cultural repertoire’ of a society, which provides local symbols of meaning and practices, is important in science and society studies. For many years, researchers worldwide, using surveys, focused largely on the relationship between knowledge of scientific facts and attitudes to science (see Bauer and Falade 2020; Allum et al. 2008), using data from those surveys to make comparisons among cultures to reveal variations and the influence of demographics. The approach of using survey methodology led to the phrase ‘cognitive deficit model’ and subsequent debates about its pros and cons (see Wynne 1982; Einsiedel 2000; Sturgis and Allum 2004; Bauer et al. 2007). More recent studies have focused on segmenting the diverse publics of science and, while there are methodological issues with segmentation analyses, they are indicative of cultural influences (Füchslin 2019) and require qualitative validation (Bauer and Falade 2020). Using the Eurobarometer 63.1 of 32 countries and latent class analysis, Mejlgaard and Stares (2010) categorized European publics as ‘involved citizens’, ‘detached citizens’ and ‘attentive public’. Schafer et al. (2018), in a study in Switzerland, also using latent class analysis, found publics that are ‘Sciencephiles’, ‘critically engaged’ ‘passive supporters’ and ‘disengaged’ (see also Nisbet and Markowitz 2014; Maibach et al. 2011). Publics also include self-identifying social groups informed by religious beliefs (Christians, Muslims and others), ethnic affiliations (Zulu, Hausa, Igbo, Xhosa, Maasai, Yoruba and so on), income status (low, middle and high) and age bracket (baby boomers, generation X, generation Z, millennials and so on). Such groups or publics can come together, for example, to address concerns over vaccines (Falade 2015; Feldman-Savelsberg et al. 2000), but their composition and nature will vary with the circumstances under which science and the public meet (Einseidel 2000, 2007; Wagner 2007). The ‘publics’ of science are thus complex, diverse and culture and context dependent, and understanding their relationship with science remains a central concern for researchers and science communication practitioners.

7.2 Science Culture is Local: The African Publics Glanz et al. (2008) argue that effective public education should be designed with an understanding of target audiences’ social characteristics, beliefs, attitudes, values and skills, among other things. Those audiences, they argue, can be characterized through sociodemographics, ethnic or racial background, age or other factors. Science communication in Africa occurs in the context of social divisions created by language, tribal affiliations, cultural and traditional practices and religious beliefs. Given that the initial direction with which social groups engage with a new scientific phenomenon is usually informed by loyalty to those groups (see Moscovici 1984), that diversity has implications for the diffusion of science. There are more

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than 1,000 mother tongues across Africa and there is also a wide diversity of religious beliefs (Christianity, Islam, African religions, agnosticism and others) and varieties within denominations. Within Christendom, there are several denominations (Catholics, Anglicans, Pentecostals, Jehovah Witnesses and so on) with deep theological differences. Islam is equally diverse (see Carlisle et al. 2019; Unsworth 2019), as it involves two main groups (the Sunni and Shia) and the lesser known Kharjites. Those strains of Islam have also given birth to several theological leanings: Asha’ri, Qadariyyah, Jahmiyyah, Ahmadiyya, Wahhabism/Salafism and so on. Many Africans also retain beliefs in African religions, while the Abrahamic religions in Africa rest on African traditions (Lugo and Cooperman 2010: 147; Ellis 2008; Paden 2005; Abimbola 1994). Africa is also home to some of the world’s poorest people, most of whom have no access to higher education and the scientific method and many of whom continue to rely on unreliable but entrenched African beliefs and practices for explanations of health and well-being. These multi-faith, polyethnic and relatively poor publics create diverse contexts for science communication in Africa, manifesting in a variety of impacts as social groups appropriate science differently. First, we compare some of the demographics of Africa’s largest economies: South Africa and Nigeria.

7.2.1 South Africa South Africa is the ninth largest country in Africa, with an estimated population of 57.73 million in 2018 (see Table 7.1). More than 41 million are black, 4.5 million are white, 4.6 million are mixed race and about 1.3 million are Indian or Asian. The black population of South Africa is divided into four major ethnic groups: Nguni, Sotho, Shangaan-Tsonga and Venda. There are numerous subgroups within those, of which the Zulu and Xhosa, of the Nguni group, are the largest. There are at least 35 individual languages, of which 11 are official: isiZulu is the most common language (spoken at home by 24.6% of the population), followed by isiXhosa (17%) and Afrikaans (12.1%). South Africans subscribe to various religious belief systems, including Christianity, Islam, traditional African religion or the sangoma (see Wetford 2005; Van Binsbergen 2003).

7.2.2 Nigeria In 2019, Nigeria had an estimated population of 193 million, accounting for roughly one-fifth of the population of Africa. The country has more than 200 ethnic groups speaking diverse languages, but the official language is English. The Yoruba in the southwest, the Igbo in the southeast and the Hausa/Fulani in the north are the dominant ethnic groups. The north is predominantly Muslim but has Christian minorities, the South is mainly Christian, but the Yoruba practice both religions and the Igbo are

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Table 7.1 Population indices for Nigeria and South Africa Key facts

Nigeria

South Africa

Population

193 million

57.73 million

Land area

923,768 km2

1,213,090 km2

km2

48 per km2

Population density

209 per

Population under 15 years old

41%

30%

GDP

(2019)a

US$444,916 million

US$371,298 million

GDP per capitaa

US$2233

US$6331

GDP per capita PPPa

US$6098

US$13,865

HDIb

0.532

0.699

Life expectancy at birth2

53.9 years

63.4 years

Political structure

Federal system

Parliamentary system

States/provinces

36 states

9 provinces

Languages spoken

200+

35

Official language(s)

1

11

Ethnic nationalities

200+

4+

Religions

Christians 48.3%; Muslims 48.9; African religion; others

Christians 80%; Muslims 1.5%; Hindus; African religion; others

a International

Monetary Fund country-level data, https://www.imf.org/external/pubs/ft/weo/2019/ 01/weodata/weoselgr.aspx b UN Development Programme, Human development report, http://hdr.undp.org/en/2018-update

mainly Roman Catholics. The Christian Yoruba are mainly Protestants, and most of them are Anglicans. There are also several minority Christian populations in north, and the past three decades have seen the emergence of Pentecostal movements in the south with millions of followers. Over 95% of Nigeria’s Muslims are Sunni; the others are a Shia minority. As in other parts of Africa, many Nigerians remain adherents of African religious practices (see Lugo and Cooperman 2010; Paden 2005; Abimbola 1994).

7.3 Science, Religion and Traditions Some studies have focused on the interaction between religion, non-religion and science (Jones et al. 2019; Scheitle et al. 2018; Clément 2015; Falade and Bauer 2018; Falade and Guenther 2020), and others have shown high levels of religious beliefs in Africa compared with other parts of the world.1 Those studies indicate that, while religion is global, types and levels of belief (and non-belief) are local, and 1

What the world thinks of God, BBC News, 11 November 2005, http://news.bbc.co.uk/2/hi/progra mmes/wtwtgod/default.stm.

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that levels of interaction of belief with science vary across cultures. Mental health practices in Ghana, sangoma and HIV treatment in South Africa, the tetanus toxoid controversy in Cameroon and the oral polio vaccine controversy in Nigeria illustrate the complex relationship between science, religion and traditions across Africa.

7.3.1 Beliefs, Traditions and Mental Health in Ghana Religious practices for mental health care in Ghana are very widespread (Ae-Ngibise et al. 2010) and the first port of call for most people in the rural areas, who are constrained by poor access to health care and by the cost of hospital treatment (Tabi et al. 2006). Mental health issues are often perceived in Africa as having spiritual origins, so, while traditional healers use herbs and other spiritual forms, their Christian and Muslim counterparts believe in the efficacy of prayers to cast out the ‘demons’ behind the ailment. Ae-Ngibise et al. observed that many of the respondents they interviewed stressed that traditional and faith healers are like clinical psychologists, providing counselling, in contrast to the curative approach of clinical medicine. They cited a government official who said that ‘healers have been part of our societies for a very long time and whether we like it or not people with mental health problems are going to go to them.’ In Ghana, traditional practices, religious beliefs and clinical medicine coexist in the treatment of mental ill-health.

7.3.2 Sangomas and HIV Treatment in South Africa HIV/AIDS presents a major health crisis in South Africa but, despite the availability of antiretroviral therapy, many ill with the disease still consult traditional healers called sangomas. The South African Government recognizes traditional healers and promulgated the South African Traditional Health Practitioners Act 35 of 2004, which seeks to formally recognize an estimated 200,000 to 350,000 traditional healers.2 Also, the United States provided the Nelson Mandela School of Medicine at the University of KwaZulu-Natal with $700,000 to train 375 traditional healers (see Cook 2009). But, while the government’s rule is that the healers cannot diagnose or treat AIDS patients, many traditional healers believe that their treatment works and, like their counterparts in other parts of Africa, advertise their claims openly to the public. Cook observed that the traditional healers also charge less than Western healthcare practitioners and that patients do not pay the sangomas if the patients’ health does not improve, making them more attractive to the poor. Their numbers, Cook observed, can be an asset to the healthcare system but, without training, they may become its problem. 2

Traditional Health Practitioners Act 35 of 2004, https://www.gov.za/documents/traditional-hea lth-practitioners-act-0.

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7.3.3 Politics, Religion and the Tetanus Toxoid Vaccine in Cameroon In Cameroon, a vaccination campaign was launched simultaneously with a major shift in state population policy—specifically, the legalization of contraception and a campaign promoting family planning. The launch was during a period of heightened political tension between the West and Northwest provinces and the central government. It was also a period of public disagreement between a pro-life Catholic group (the Family Life Association) and the central government over the safety of the tetanus toxoid vaccine compulsorily administered to girls of childbearing age only. Rumours that the vaccine contained sterilizing substances were interpreted by the West and Northwest provinces as a deliberate attempt to reduce their population for electoral reasons; this was an indication of the influence of prior beliefs and the defence of group identity. The controversy was fuelled by political and religious groups and rumours (Feldman-Savelsberg et al. 2000).

7.3.4 Oral Polio Vaccine in Northern Nigeria The global effort to eradicate polio was resisted by some religious leaders in northern Nigeria, who described the exercise as being against Islamic injunctions. The debate split the country into two (the south and the north) and along religious lines. The crisis was aggravated in July 2003 when, following rumours that the vaccine can cause infertility, two very influential Islamic groups in the north (the Supreme Council for Shari’ah in Nigeria and the Kaduna State Council of Imams and Ulamas) declared that the vaccine was part of a Western conspiracy to reduce the population of the Muslims and the developing world. The political class soon joined in the controversy, and some states in northern Nigeria, led by Kano State, banned the use of the vaccine. The controversy was fuelled by religious and political groups acting together and by rumours. The controversy over contamination was eventually resolved, but the issue of compatibility with Islam remained in public discourse for a few more years (Falade 2015). These case studies show how religious, political and ethnic groups often combine to form ‘issue publics’ and that their resort to prayers and African traditional practices may be due to affordability or people’s belief in the efficacy of both. Thus, the positions of these social and cultural groups are sometimes anchored in the protection of values and traditions, economic imperatives, beliefs and the coexistence of multiple rationalities (Moscovici 1984) and at other times act as ‘voices and images’ of public concern (Bauer and Gaskell 1999).

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7.4 Science Communication We now examine the practices of science communication in Nigeria and South Africa. This is illustrated with the science centre approach in South Africa and a non-government organization (NGO) approach to health communication in Nigeria. The science centre approach has not taken off in Nigeria, where science communication remains spread across different fields: agriculture, environment, health and so on. Agricultural extension work in Nigeria dates back several decades, while health and environmental communication are more recent (see Falade et al. 2020).

7.4.1 Science Centres About 23 science centres spread across South Africa form an important part of the country’s science, technology, engineering and mathematics (STEM) awareness landscape and are charged with the transformation of STEM in a post-apartheid society. The strategic goals are to promote science literacy and careers, enhance learner participation and nurture youth talent (DST 2005: 1–10; SAASTA 2015). The science centres are owned by the government or its agencies, NGOs, individuals and communities but have to be accredited by the Department of Science and Technology (DST). The accreditation process is repeated every five years. The science centres sponsored by international bodies are, however, not entitled to DST funds and other benefits available to their local counterparts. Institutions designated as science centres in South Africa include the South African Astronomical Observatory and the South African National Space Agency in Western Cape; the Radio Astronomy Observatory; Johannesburg City Parks; the South African Nuclear Energy Corporation; the National Zoological Gardens in Gauteng Province; the Anglo-American Science Centre; and the Mondi Science, Career Guidance and FET Skills Centre in Mpumalanga. Two of the science centres located in Limpopo Province are in focus here, to highlight the variability in programmes designed for the wider public and their use to arouse interest in science among the younger generation (see Ramohlale 2019). They are the Giyani Science Centre and the Vuwani Science Resource Centre. The Giyani Science Centre was established in 1989, following a proposal by a homeland leader for the purpose of bringing science and technology closer to the communities around Giyani and in nearby areas. It is currently managed by Mr. Norman Mthembi. The centre runs an enrichment programme for primary and high school learners on science subjects and provides support to educators from surrounding schools in subjects they struggle with. It also carries out outreach programmes to surrounding schools using a mobile laboratory and the general public at the local shopping mall through exhibitions and science shows. In addition, the centre runs an information and communications technology programme supported

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by one of the mobile telephony companies, which offers certificates in computer literacy programmes to the general public. The Vuwani Science Resource Centre was established in 1999 in Vuwani village in Venda. It was built using funds donated by Zenex Foundation and the DST and is currently managed by Dr. Eric Maluta. In addition to its science exhibitions, the centre conducts curriculum-based practical experiments for school learners in physics, chemistry and the life sciences and runs a computer literacy programme for which certificates are issued by the University of Venda. Its outreach programmes target schools deep in the rural communities, where it conducts curriculum-based practical experiments, science shows, motivational talks and career guidance. It also runs science competitions and debates, a teachers’ upgrade programme and exhibitions at the local shopping mall for the wider community.

7.4.2 NGO: DRASA Health Trust DRASA Health Trust is an NGO established and named in memory of the late Dr. Ameyo Stella Adadevoh, who identified and quarantined Nigeria’s first Ebola fever patient but lost her life to the disease. DRASA works with government, communities, students, health workers and international partners organizing programmes directed at curtailing the spread of infectious diseases and strengthening emergency preparedness. The trust conducts training programmes, simulation exercises, community education and outreach and is also involved in advocacy and policy development. Information on the trust’s website indicates that it uses health communication to drive behaviour change to get the public to understand ‘why’ and to dispel myths and rumours about infectious diseases.3 It says that its Health and Hygiene Club programme was designed to transform healthy behaviour patterns into habits and social norms in communities using several approaches to turn scientific evidence into digestible information tailored to the needs of different stakeholders. The organization also trains students and health workers to extend health-enhancing behaviourchange strategies to the wider community. For students, the training is intended to drive positive health- and hygiene-related behaviour change within their schools, their families and the wider community; for health workers, the focus is on understanding why practising universal infection control precautions for all patients is the key to protecting themselves and the wider society and how an infectious disease contracted from a patient while on the job can be carried into the home and potentially infect their families and community members.

3

Dr Ameyo Stella Adadevoh (DRASA) Health Trust, https://www.drasatrust.org/.

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7.5 Social Groups, Social Space and Science as Progress Moscovici (2008), in his study of the reception of psychoanalysis in France in the 1950s, showed that the conversations of Catholics, communists and liberals were informed by common sense and a defence of each group’s position. While the communists called for a rejection of psychoanalysis, the Catholics, who found similarities between confession and psychoanalysis and recognized that some of their members were engaging with the phenomenon, called for its integration into religious doctrine. The liberals encouraged its acceptance by society. Moscovici described those different but collective approaches as ‘social representations’, which are essentially cognitive structures that facilitate communication between members of a collective because they are consensual and are also public rhetoric used by groups to engender cohesiveness and manoeuvre relative to other groups (Breakwell 1993). The integration or accommodation approach taken by the Catholics is of interest in this paper because it shows the coexistence of two different rationalities—science and religion—in a social group. Moscovici proposed the concept of ‘cognitive polyphasia’ (Moscovici and Makova 1998), arguing that a plurality of modes of thought can coexist within the same individual or group, and researchers have shown that to be true across cultures. In Ghana, traditional practices, religious beliefs and clinical practices coexist in the treatment of mental health (Tabi et al. 2006; AeHgibise et al. 2010) in what Aikins (2005), in her study of diabetes in Ghana, describes as ‘healer shopping’. In South Africa, traditional and spiritual healers, the sangomas, are recognized by the government in health care (Cook 2009; Traditional Health Practitioners Act 35 of 2004), and the notion of ‘medical pluralism’, whereby the public consults both spiritual healers and clinical medicine, has been documented (Moshabela et al. 2011, 2017). Legare and Gelman (2008) found a coexistence of natural and supernatural explanations for illness and disease transmission in two Sesotho-speaking South African communities, and Wanyama et al. (2017) showed that HIV-positive patients undergoing antiretroviral therapy in Tanzania, Zambia and Uganda also consulted traditional healers. In a study of the Chinese community in England, Gervais and Jovchelovitch (1998) found a hybrid representation that combines Chinese traditions and Western biomedical knowledge, while Priego-Hernandez (2015), in a study in Mexico, found the coexistence of both religious and medical knowledge in health-care systems. Jovchelovitch and PriegoHernandez (2015:163) suggested three varieties of cognitive polyphasia (selective prevalence, hybridization and displacement), while Falade and Bauer (2018) suggested hierarchical, complementary and transformative coexistence. For Pierre Bourdieu (1984, 1985), representations or perceptions of the social world are products of subjective and objective social construction. Bourdieu argued that objects in the social world can be perceived and uttered in different ways because, like objects in the natural world, they always include a degree of indeterminacy and fuzziness, and that element of uncertainty is what provides a basis for the plurality of world views. For Bourdieu, the work of representation, of categorizations and classification, is performed continually as the public clashes over meaning in the social

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world and its position within that world. Representations are thus sites of symbolic struggles, and the social world is a symbolic system organized according to the logic of difference. For Bourdieu, the social space and its spontaneous differences thus function symbolically as a ‘space of lifestyles’ of groups characterized by different lifestyles. For this chapter, we are interested in the symbolic ‘space of science’ of groups characterized by their attitudes to science.

7.5.1 Visualizing the Social Space of Science Pierre Bourdieu (1985) argued that the social world can be represented as a multidimensional space of positions constructed on the principles of differentiation, and that agents or groups of agents are thus defined by their relative positions within that space. Based on positioning in the multidimensional space, one can separate out ‘sets of agents’ who occupy similar positions and have every likelihood of having similar dispositions and interests (common sense) and therefore of producing similar practices and adopting similar stances. That space, he explained, determines compatibilities and incompatibilities, proximities and distances. He argued that, although sets of agents with common sense do not exist as real groups, the space they occupy can explain the probability of individuals constituting themselves as practical (or latent) groups. The probability of coming together thus rises when they are closer together in social space, although alliance between those who are closest is never necessary and between those most distant is never impossible. Multivariate analysis Various quantitative approaches have been used for the study of social representations. Doise et al. (1993) list automatic cluster analysis, correspondence analysis, discriminant analysis and multidimensional scaling (see also Breakwell and Canter 1993). The approach here, of multivariate analysis, is thus not entirely new, as it has been used in the past to study social representations among manifest groups. This is, however, an attempt to identify practical social groups necessitating a novel combination of two research approaches: Moscovici’s, focusing on the importance of social groups in public communication, and Bourdieu’s, focusing on identifying practical social groups using relationships among variables in a two-dimensional space. The social groups in Moscovici’s approach are manifest groups that can be identified, and what Bourdieu adds to that is the possibility of identifying practical groups through the social space they occupy (see Clausen 1998). Bourdieu used correspondence analysis to explore and visualize the social space. Correspondence analysis is a multivariate statistical tool that shows relationships among variables in a multidimensional space using tabular data, which it converts into graphical displays, which then reveal features of the data. This means that one can find clusters of categories as symbolic common sense. Correspondence analysis is based on a triplet of information for a dataset: the objects in a multidimensional space, their weights and the distances between them (see Greenacre 2010; Bartholomew et al. 2008; Clausen 1998; Greenacre and Blasius 1994).

7 Science Communication in Nigeria and South Africa … Table 7.2 Manifest variables used in the analysis

Code

Variable

V144

Religious denomination

V152

How important is God in your life

V229

Employment status

V239

Scale of Income

V240

Gender

V242

Age

V248

Highest education attained

135

For this analysis, we are using data from the World Values Survey, Wave 6 (Inglehart et al. 2014), selecting those variables that describe the population and their association with variables that self-report agents’ attitudes to science. The ‘manifest’ variables (Table 7.2) considered are V144 religious denomination, V152 how important is God in your life, V229 employment status, V239 scale of income, V240 gender, V242 age and V248 highest education level attained. A recently published study (Falade and Guenther 2020) shows religiosity (How important is God in your life) as a strong predictor of the relationship between science and religion using the World Values Survey data and the proposition that ‘When science and religion meet, religion is always right’. Religiosity as a significant predictor is constant across four countries in the comparative analysis: South Africa, Zimbabwe, the United States and the United Kingdom. The analysis compared the effects of a ‘trust’ index, religiosity and sociodemographic variables, and the qualitative interviews indicated that choosing either science or religion is not always an outright rejection of the other. The relationships between science and religion were classified as those informed by cognitive dissonance, often expressed in hierarchical associations, and those influenced by cognitive polyphasia, a complementary and transformative coexistence. Similar findings were made by Falade and Bauer (2018) in their study of science and religion in Nigeria. This study examines relationships between levels of religiosity, the notion of science as ‘promise’ and sociodemographic variables visualizing this as practical groups in a two-dimensional space. Science as promise. The attitude variables in the study are the six asked by the survey using Likert scale answer options of 1 to 10: • V192: Science and technology are making our lives healthier, easier, and more comfortable. • V193: Because of science and technology, there will be more opportunities for the next generation. • V194: We depend too much on science and not enough on faith. • V195: One of the bad effects of science is that it breaks down people’s ideas of right and wrong. • V196: It is not important for me to know about science in my daily life.

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• V197: The world is better off, or worse off, because of science and technology (Table 7.3). V152 was recoded from 10 levels of the importance of God to four, V229 was recoded to reduce the number of employment categories to five, V239 was recoded from 10 scales of incomes to five, V242 was recoded to five age groups, and V248 was recoded from nine to five levels of education. V144 was recoded by bringing similar faiths together to reduce large numbers of categories, but the recoding differs for both countries (see Tables 7.7 and 7.8 in the appendix to this chapter). SPSS factor analysis was used to reduce the attitude variables to latent groups and to create a new variable (Progress) with four values. Three factors were stable across the two countries using maximum likelihood for extraction and Promax with Kaiser normalization for rotation, and values below 0.30 were suppressed. For South Africa, the three-factor solution explained 47% of the variance (KMO = 0.7; chi-square = 3426.9; p < 0.001), while for Nigeria, it explained 67% of the variance (KMO = 0.6; chi-square = 2823.8; p < 0.001). The pattern matrix output for each of the two countries is below. We considered using summative scores instead of factor scores but we ran the risk of overlooking cultural differences in the publics of both countries (see Wagner et al. 2014; Falade 2018), and that was clearly indicated by the outcome of the analysis, which showed differences in the loading of two of the attitude variables. V192 and V193 were consistent across both countries as indicators of progress, but, while V197 loaded on progress in Nigeria, it was separated in South Africa as the third factor. Also, V196 was the third factor for Nigeria but it merged with the second factor for South Africa (Table 7.3). Regression scores were saved for each respondent and, using visual binning, grouped into four values: ProgN, Prog1, Prog2 and Prog3; ProgN (none) for those with regression scores less than zero and 1 to 3 in increasing equal levels of agreement on the factor. Tables 7.4 and 7.5 show the correlations between all the variables used in the analysis. For the correspondence analysis, the age variable was split by gender to distinguish between men and women of different age groups. The four values in the Progress factor were cross-tabulated with the selected variables and concatenated into a table for the correspondence analysis produced using the correspondence analysis function in R-Project, and the bi-plots were generated.

7.5.2 Social Groups and Attitudes to Science in Spatial Dimensions We are interested in proximities and distances and the ‘classes’ in social space (Bourdieu 1984,1985), which can explain the probability of individuals constituting themselves as practical groups. Our focus is on the ‘Progress/promise’ factor, although

Values

0.53

V195 (reversed) science breaks down people’s ideas of right and wrong

0.461

V197 the world is better off, or worse off 0.939

0.887

V192 makes our lives healthier, easier, and more comfortable

V194 (reversed) we depend too much on science and not enough on faith

0.893

V193 more opportunities for the next generation 0.917

0.605

Progress / promise

Morality

Progress/promise

Reservation

South Africa

Nigeria

Table 7.3 Three-factor solutions for the aggregation of attitude variables

0.717

0.525

Morality

Reservation

0.604

Concern

7 Science Communication in Nigeria and South Africa … 137

0.005 −0.013 0.119**

−0.046** −0.291** 0.090** −0.055**

0.02

0.088**

0.033

0.420**

Denomination

Age

Sex

* Correlation

is significant at the 0.01 level (2-tailed) is significant at the 0.05 level (2-tailed)

** Correlation

Progress

−0.035*

0.041*

−0.137**

0.069**

Education

0.101**

−0.287**

0.210**

−0.194** 0.016

Education

−0.046**

Income

Income

Employment

−0.078**

Importance of God

Employment

Importance of God

Table 7.4 Correlations between variables for South Africa

−0.025

0.040*

0.043*

Denomination

−0.01

0.056**

Age

0.009

Sex

138 B. A. Falade and R. M.-J. Ramohlale

7 Science Communication in Nigeria and South Africa …

139

Table 7.5 Correlations between variables for Nigeria Importance Employment Income of God

Education Denomination Age

Gender

Importance of God Employment

−0.076**

Income

−0.162**

−0.01

Education

0.036

−0.031

0.334**

Denomination 0.096**

−0.006

0.128**

0.272**

0.076**

−0.286**

−0.170**

−0.219** −0.022

Gender

−0.013

0.108**

−0.060*

−0.168** −0.008

−0.052*

Progress

0.271**

−0.138**

0.196**

0.278**

−0.046

Age

0.237**

−0.047

** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed)

the same method can be applied to all three factors. Figures 7.1 and 7.2 show the bi-plots of the concatenated tables for Nigeria and South Africa, respectively, on the Progress factor and give a strictly descriptive picture of the probabilities of which social groups are related to which levels of progress. The likelihood of belonging to a practical group is denoted by proximity of profiles: those being more likely are closer than those further away. Here we focus on the profiles close to the different levels of ‘Progress’. Nigeria For Nigeria (Fig. 7.1), dimension1 accounts for 84.59% of the inertia (variance explained), while dimension 2 accounts for 10.83%, totalling 95.42%. Thus, a twodimensional solution represents the data well. The figure shows that Progress (ProgN,

Fig. 7.1 Bi-plot of concatenated table for Nigeria

140

B. A. Falade and R. M.-J. Ramohlale

Fig. 7.2 Bi-plot of concatenated table for South Africa

Prog1, Prog2 and Prog3) increases along the first dimension from left to right but in the manner of the horseshoe or Guttman effect, denoting a very dominating first dimension (see Clausen 1998). Dimension 1 splits the importance of God in respondents’ lives into two; high importance with positive values ImG3 and ImG4, on the right, with profiles far from the centre and low importance, ImG1 and ImG2, on the left. The centroid (centre) represents the average, and profiles distant from the average are represented by points far from the centre. Negative values for Progress (NProgress) are relatively more prevalent among those who self-identify as low income (SI1) and with primary education (EDPri). In proximity are males 40 to 50, Muslim, no education (EdNo), retired persons and housewives (Hem) and low importance of God (ImG1). High positivity about Progress (Prog3) is further away from the centre/averages than Progress 1 (Prog1) and 2 (Prog2) and is positioned close to those with very high income (SI4) and high school students on the university education track (EdSU). Also in close proximity but towards the centre are high importance of God (ImG4) and males aged between 30 and 39. Protestants are closer to Progress 2 than 3, while Catholics are in between Progress 1 and 2. Also in proximity to Progress 2 are university education (EdU) and the employed (Emp). Those groups have every likelihood of having similar dispositions and interests and therefore of producing similar practices and adopting similar stances on science. The proximity of high importance of God (ImG4) and Progress (Prog3, Prog 2, Prog1) and the distance from ProgN is indicative of cognitive polyphasia (belief in progress coexisting with religious beliefs). This further confirms earlier studies in Nigeria (Falade and Bauer 2017) and South Africa (Falade and Guenther 2020). Also in proximity to these factors is high income (SI4), university education (EdU) and high school students on the university education track (EdSU). This indicates that those agents with high education, high income and strong religious beliefs are more

7 Science Communication in Nigeria and South Africa …

141

likely to believe in the notion of progress than those with low education, a low image of God and low income. South Africa For South Africa (Fig. 7.2), the bi-plot shows Progress also exhibiting the Guttman effect, with a dominating first dimension explaining 67.79% of the variance and the second dimension accounting for 27.22%, totalling 95%. The two-dimensional solution is also a good representation of the data. Progress increases from left to right, and the importance of God also increases from left to right. Both indicate that the notion of progress increases with the perceived importance of God. The highest level of progress (Prog3) and importance of God (ImG4) are in close proximity, which is also an indication of cognitive polyphasia, as seen in the Nigerian data. Prog3 is also in close proximity to university education (EdUni), Protestants and the self-employed (Sem). The highest level of income, SI4, is closely associated with Progress 1 and 2. Also positioned close to Progress 1 are males aged 25–29. NProgress is much closer to the centroid than Progress 3 and is in close proximity and thus relatively more prevalent among those who identify as having no education (EdNo), having no religion (NRel), not knowing about religion (RelDK) and having low income (S1 and S2).

7.5.3 Limitations of the Research Approach We used secondary data and are conscious of its limitations. While Christianity is broken down into denominations in the Nigerian data, Islam is monolithic. We also note that there were only six attitude variables, which is a small number compared with about 12 in many science and society surveys. Also, while all the answer options in the attitude variables (V193 to V197) were on a Likert scale of 1 to 10, the wording in all but V197 was ‘from disagree to agree’. The answer options for V197 (The world is better off or worse off) were denoted from 1 (a lot worse off) to 10 (a lot better off). This may have implications for the interpretation of scales for respondents in different cultures. It is noteworthy that this variable loads differently in both datasets.

7.6 Conclusion Comparing South Africa and Nigeria, our findings show different ‘practical groups’ with varying levels of religious beliefs, denominations, attitudes, levels of education and age for the two countries, all of which are indicative of cultural differences. The differences in the composition of the three factors in the reduction of the attitude variables for both countries also provide further evidence of cultural differences in the public understanding of science (Wagner et al. 2014; Falade 2018).

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Within each country, the findings show that the levels of agreement with science as progress vary across the profiles for gender, age group, religious denomination, level of income, level of education and employment status. The findings also show that lower levels of income and education and some types of religious belief are more closely associated with low levels of views of science as progress but, as Bourdieu pointed out, alliance between those who are closest is never necessary and between those most distant is never impossible. The bi-plots validate the coexistence between science and religious beliefs, which is indicative of cognitive polyphasia. However, they also show that being highly religious is not anathema to the notion of science as progress: religious belief does not make the public anti-science, but levels of acceptance of science as progress vary across faiths. Competition with science, however, has implications for the diffusion of innovations in science, as shown by the case studies, which show that, despite competing reference points as in the lighthouse model or occasional disputes leading to a plunge into the abyss, science often always prevails (see Bauer et al. 2019). This chapter stresses the need for the development and deployment of varying approaches to accommodate the peculiarities of each practical group for more effective science communication. That does not invalidate general awareness programmes such as science centres but highlights the importance of some of their specific functions being aimed at target groups in recognition of those groups’ distinctiveness. The agents and groups who do not view science as contributing to progress require different strategies compared with those who associate it with high levels of progress. Our recommendation is that science communication stands better chances of success if its design is informed by such an analytical approach and messages are tailored for both manifest and practical groups.

Appendix See Tables 7.6, 7.7 and 7.8.

7 Science Communication in Nigeria and South Africa …

143

Table 7.6 Abbreviations used in the analysis Nigeria

South Africa

Variable

Abbreviation

Abbreviation

Importance of God

ImG1

ImG1

Importance of God

ImG2

ImG2

Importance of God

ImG3

ImG3

Importance of God

ImG4

ImG4

Employed

Emp

Emp

Self employed

Sem

Sem

Retired and housewife

Hem

Hem

Students/employment

Stem

Stem

Unemployed

Uepm

Uepm

Income

SI1

SI1

Income

SI2

SI2

Income

SI3

SI3

Income

SI4

SI4

No Education

EdNo

EdNo

Primary Education

EdPri

EdPri

Secondary vocational

EdSV

EdSV

Secondary university

EdSU

EdSU

University education

EdU

EdUni

Male 18 to 24

M18t24

MA18t24

Male 25 to 29

M25t29

MA25t29

Male 30 to 39

M30t39

MA30t39

Male 40 to 49

M40t49

MA40t49

Male over 50

M50plus

MA50t85

Female 18 to 24

F18t24

FA18t24

Female 25 to 29

F25t29

FA25t29

Female 30 to 39

F30t39

FA30t39

Female 40 to 49

F40t49

FA40t49

Female over 50

F50plus

FA50Plus

No Religion

Nrel

NRel

Protestant

Protes

Protes

Catholic

Catho

Cathol

Religion Others

RelOth

RelO (minorities/unspecified)

Muslim

Muslim

Apostolic

Aposto

African Pentecostal/pentecostal

AfrRel

Religion Don’t Know

RelDK

African Pentecostal

Afrpen

124

121

19

Protes

Catho

RelOth

212

106

469

ImG2

ImG3

ImG4

368

170

175

71

Sem

Hem

Stem

Uepm

160

231

289

SI1

SI2

SI3

Scale of income

61

Emp

Employment status

59

ImG1

Importance of God

65

517

Muslim

ProgN

Nrel

Religious affiliation

123

124

39

25

70

34

187

82

242

122

24

10

18

96

109

135

41

Prog1

95

45

27

18

48

15

100

73

182

61

6

4

15

60

100

58

21

Prog2

70

64

16

12

65

19

91

74

226

23

1

9

27

59

98

47

29

Prog3

Table 7.7 Nigeria concatenated table and correspondence analysis output

0.054661

0.043956

0.022925

0.011936

0.033914

0.022546

0.070671

0.027473

0.106006

0.029557

0.02302

0.007768

0.007484

0.03183

0.04083

0.071713

0.014778

Mass

0.096644

0.155313

0.373005

0.19113

0.112307

0.470365

0.090775

0.568871

0.174104

0.465408

0.793487

0.489522

0.622655

0.243125

0.42012

0.420383

0.157155

ChiDist

0.000511

0.00106

0.00319

0.000436

0.000428

0.004988

0.000582

0.00889

0.003213

0.006402

0.014494

0.001861

0.002902

0.001881

0.007206

0.012673

0.000365

Inertia

−0.69164 −0.21487

−0.13723

(continued)

0.086503

−1.25587

−0.25348

−0.21148

1.040755 −0.58815

0.758705

−1.60434 0.024886

0.172776 −0.75285

1.960502

0.873317

−0.15505

0.512786

−4.06877

0.584858 0.673408

1.589592 −2.73571

2.549399

−0.75407

0.36463

−1.58273

1.900611

0.795457

1.429327

−0.06567 −0.15102

0.428618

Dim. 21

−1.45386

Dim. 1

144 B. A. Falade and R. M.-J. Ramohlale

ProgN

146

381

100

59

EdPri

EdSV

EdSU

EdU

107

106

59

51

M25t29

M30t39

M40t49

M50plus

152

100

65

45

54

F18t24

F25t29

F30t39

F40t49

F50plus

Female and age

109

M18t24

Male and age

160

167

EdNo

Education

SI4

Table 7.7 (continued)

19

20

55

57

59

11

11

50

47

69

67

62

197

36

37

113

Prog1

7

11

20

42

45

13

18

42

19

37

48

64

116

20

6

87

Prog2

5

8

33

30

30

14

9

51

33

49

48

67

113

19

14

111

Prog3

0.008052

0.007958

0.016389

0.021694

0.027094

0.008431

0.009189

0.023588

0.019515

0.025009

0.021031

0.027757

0.076449

0.020936

0.020557

0.045282

Mass

0.360474

0.164132

0.279097

0.137502

0.144587

0.254813

0.350176

0.187287

0.151072

0.156866

0.434173

0.351338

0.044538

0.362011

0.540251

0.306645

ChiDist

0.001046

0.000214

0.001277

0.00041

0.000566

0.000547

0.001127

0.000827

0.000445

0.000615

0.003964

0.003426

0.000152

0.002744

0.006

0.004258

Inertia

Dim. 21

0.406248

1.905339

−0.47142

−0.8883 −0.90111 −0.99897

−0.46108 −1.19253

−0.76024 0.625697

0.273336

−0.30247

1.041893

−0.36056

1.16116 −0.75268

0.314625

−0.27973 0.496505

−0.06303

−0.58677

1.143534

0.459366

1.487842

1.115123

−0.41775

−1.2429 0.026138

0.18235

0.885587

−1.83938

1.008449

Dim. 1

7 Science Communication in Nigeria and South Africa … 145

238

150

72

183

Protes

Cathol

Aposto

AfrRel

RelDK

447

248

395

ImG2

ImG3

ImG4

46

255

153

568

Sem

Hem

Stem

Uepm

Scale of income

468

Emp

Employment status

408

ImG1

Importance of God

179

141

RelO

287

247

Afrpen

ProgN

NRel

Religious affiliation

245

101

123

18

250

238

280

179

41

79

32

84

123

90

69

147

114

Prog1

125

47

78

14

151

210

143

47

15

26

24

64

51

67

57

63

66

Prog2

169

68

79

33

189

416

63

42

20

37

22

48

72

106

85

111

60

Prog3

0.058071

0.019357

0.028065

0.005823

0.0555

0.066044

0.038504

0.037507

0.025389

0.017049

0.007869

0.01815

0.025389

0.021193

0.020458

0.029796

0.027645

Mass

Table 7.8 South Africa concatenated table and correspondence analysis output

0.09142

0.125151

0.067233

0.354381

0.058497

0.474214

0.454461

0.396058

0.749699

0.237775

0.105796

0.177136

0.102164

0.304959

0.171497

0.113955

0.17603

ChiDist

0.000485

0.000303

0.000127

0.000731

0.00019

0.014852

0.007952

0.005883

0.01427

0.000964

0.000088

0.00057

0.000265

0.001971

0.000602

0.000387

0.000857

Inertia

(continued)

−0.48945 0.164603

0.427403 −0.42971

2.068083 −0.25734

−0.12081

−0.09011

1.60587

1.120904

0.272889

2.091018

−3.38976

−0.63191 0.529845

1.988858

−0.2073

−1.09286 −3.44957

−0.12616

−0.09914

−1.86777

−0.82268 0.226813

0.581073 −0.29978

−0.34673

1.078381

−0.05221

−0.15558

Dim. 2

1.448982

0.423414

0.313733

−0.82256

Dim.1

146 B. A. Falade and R. M.-J. Ramohlale

586

333

SI3

SI4

155

250

939

107

EdPri

EdSV

EdSU

EdUni

71

158

101

164

MA25t29

MA30t39

MA40t49

MA50Pl

170

100

178

147

187

FA18t24

FA25t29

FA30t39

FA40t49

FA50Pl

Female and age

223

MA18t24

Male and age

37

EdNo

Education

327

SI2

ProgN

232

SI1

Table 7.8 (continued)

80

56

97

57

92

67

54

66

56

113

62

470

116

70

13

303

203

145

79

Prog1

58

34

39

26

45

58

24

53

21

56

45

270

66

25

8

159

148

64

40

Prog2

67

50

67

36

78

61

27

45

29

83

79

349

55

44

6

184

194

74

66

Prog3

0.020563

0.015055

0.019986

0.011488

0.020196

0.01836

0.010806

0.016891

0.009285

0.024917

0.01537

0.106384

0.025547

0.015423

0.003357

0.051356

0.05933

0.031999

0.021875

Mass

0.075726

0.104276

0.093228

0.07146

0.100876

0.128986

0.121816

0.133608

0.205752

0.040174

0.299179

0.014729

0.151214

0.158846

0.249111

0.268343

0.129432

0.166951

0.182936

ChiDist

0.000118

0.000164

0.000174

0.000059

0.000206

0.000305

0.00016

0.000302

0.000393

0.00004

0.001376

0.000023

0.000584

0.000389

0.000208

0.003698

0.000994

0.000892

0.000732

Inertia −0.26176 0.799545

−0.79327 −0.28318

−0.57061

0.293292

0.681467

−0.27224 0.02739

−0.37454 −0.07405

−0.03739

0.254924 0.013847

0.336739

0.371883

−0.64278

−0.40856 0.16177

−1.22045 −0.08959

−0.19246

0.047817

0.899582

0.355529

−0.00517

1.350916

0.001605

0.105282

−0.63172 −0.59848 0.071003

−0.11101

−1.1559

−1.26946

0.81787

−0.72262

1.033744

Dim. 2

Dim.1

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Falade BA, Guenther L (2020) Dissonance and polyphasia as strategies for resolving the potential conflict between science and religion among South Africans. Minerva 1(22) Falade B, Batta H, Onifade D (2020) Nigeria: battling the odds: science communication in an African state. In: Gascoigne T, Schiele B, Leach J, Reiflinger M, Lewenstein BV, Massarani L, Broks P (eds) Communicating science: a global perspective. Australian National University Press, Canberra Feldman-Savelsberg P, Ndonko F, Schmidt-Ehry B (2000) Sterilizing vaccines or the politics of the womb: retrospective study of a rumour in Cameroon. Med Anthropol Q 14(2):159–179 Füchslin T (2019) Science communication scholars use more and more segmentation analyses: can we take them to the next level? Public Understanding of Science, 19 May, doi: 0963662519850086 Gervais MC, Jovchelovitch S (1998) Health and identity: the case of the Chinese community in England. Soc Sci Inf 37(4):709–729 Glanz et al. (2008) Preface. In: Glanz K, Rimer BK, Viswanath K (eds) Health behaviour and health education: theory, research, and practice. Wiley Greenacre M (2010) Biplots in practice. Fundación BBVA Greenacre MJ, Blasius J (1994) Correspondence analysis in the social sciences: recent developments and applications. Academic Press, London Inglehart RC, Haerpfer A, Moreno C, Welzel K, Kizilova J, Diez-Medrano M et al (2014) Editors world values survey: round six: Country-pooled datafile version. http://www.worldvaluessurvey. org/WVSDocumentationWV6.jsp. JD Systems Institute, Madrid Jones S, Kaden T, Catto R (2019) Science, belief and society: international perspectives on religion, modernity and the public understanding of science. Policy Press Jovchelovitch S, Priego-Hernandez J (2015) Cognitive polyphasia, knowledge encounters and public spheres. The Cambridge handbook of social representations. Cambridge University Press, Cambridge Lugo L, Cooperman A (2010) Tolerance and tension: Islam and Christianity in sub-Saharan Africa. Pew Research Center, Washington DC Maibach EW, Leiserowitz A, Roser-Renouf C, Mertz CK (2011) Identifying like-minded audiences for global warming public engagement campaigns: an audience segmentation analysis and tool development. PloS one 6(3):e17571 Mejlgaard N, Stares S (2010) Participation and competence as joint components in a cross-national analysis of scientific citizenship. Public Underst Sci 19(5):545–561 Moscovici S (1984) The phenomenon of social representations. In: Farr RM, Moscovici S (eds) Social representations. Cambridge University Press, Cambridge Moscovici S (2008) Psychoanalysis: its image and its public. Polity Moscovici S, Markova I (1998) Presenting social representations: a conversation. Cult Psychol 4(3):371–410 Moshabela M, Bukenya D, Darong G, Wamoyi J, McLean E, Skovdal M, Hosegood V et al (2017) Traditional healers, faith healers and medical practitioners: the contribution of medical pluralism to bottlenecks along the cascade of care for HIV/AIDS in eastern and southern Africa. Sexually Transmitted Infections 93(Suppl 3) Moshabela M, Pronyk P, Williams N, Schneider H, Lurie M (2011) Patterns and implications of medical pluralism among HIV/AIDS patients in rural South Africa. AIDS Behav 15(4):842–852 Nisbet M, Markowitz EM (2014) Understanding public opinion in debates over biomedical research: looking beyond political partisanship to focus on beliefs about science and society. PloS one 9(2):e88473 Paden JN (2005) Muslim civic cultures and conflict resolution: the challenge of democratic federalism in Nigeria. Brookings Institution Press, Washington DC Priego Hernández J (2011) Sexual and reproductive health among indigenous Mexican adolescents: a socio-representational perspective. Doctoral dissertation, London School of Economics and Political Science

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Ramohlale R (2019) Challenges of effective evaluation of science communication activities at the three science centres in Limpopo Province. Research assignment for MPhil in Science and Technology Studies, Stellenbosch University SAASTA (South African Agency for Science and Technology Advancement) (2015) Science engagement strategy. Department of Science and Technology. https://www.saasta.ac.za/saasta_ wp/wp-content/uploads/2018/10/2015-Science-Engagement-Strategy.pdf Schäfer MS, Füchslin T, Metag J, Kristiansen S, Rauchfleisch A (2018) The different audiences of science communication: a segmentation analysis of the Swiss population’s perceptions of science and their information and media use patterns. Public Underst Sci 27(7):836–856 Scheitle CP, Johnson DR, Ecklund EH (2018) Scientists and religious leaders compete for cultural authority of science. Public Underst Sci 27(1):59–75 Sturgis P, Allum N (2004) Science in society: re-evaluating the deficit model of public attitudes. Public Underst Sci 13:55–74 Tabi MM, Powell M, Hodnicki D (2006) Use of traditional healers and modern medicine in Ghana. Int Nurs Rev 53(1):52–58 Unsworth A (2019) Discourses on science and Islam: a view from Britain. In: Jones S, Kaden T, Catto R (eds) (2019) Science, belief and society: international perspectives on religion, modernity and the public understanding of science. Policy Press Van Binsbergen WM (2003) The translation of Southern African sangoma divination towards a global format, and the validity of the knowledge it produces. ‘World views, Science and Us’, symposium, Centre Leo Apostel, Brussels, June. Free University Brussels, Belgium 10:235–297 Wagner W (2007) Vernacular science knowledge: its role in everyday life communication. Public Underst Sci 16(1):7–22 Wagner W, Hansen K, Kronberger N (2014) Quantitative and qualitative research across cultures and languages: cultural metrics and their application. Integr Psychol Behav Sci 48(4):418–434 Wanyama JN, Tsui S, Kwok C, Wanyenze RK, Denison JA, Koole O, Colebunders R et al (2017) Persons living with HIV infection on antiretroviral therapy also consulting traditional healers: a study in three African countries. Int J STD AIDS 28(10):1018–1027 Wynne B (1982) Rationality and ritual: the Windscale inquiry and nuclear decisions in Britain. British Society for the History of Science, Chalfont St Giles

Bankole Adebayo Falade is a social psychologist and research fellow with the South African Research Chair in Science Communication, Centre for Research on Evaluation, Science and Technology (CREST), Stellenbosch University, South Africa and Visiting Fellow, Department of Psychological and Behavioural Sciences, London School of Economics and Political Science, United Kingdom. His research interests are in science and health communication; science and beliefs; and African studies of public understanding of science, health and disease. His current research is supported by the South African Research Chairs Initiative of the Department of Science and Technology (DST) and National Research Foundation (NRF) of South Africa grant number 93097. Refilwe Mary-Jane Ramohlale is a science communicator and coordinator at the Science Education Centre in the University of Limpopo, Limpopo Province, South Africa. Her interest is community-level science education. She develops, implements and facilitates science centre activities at the university; trains unemployed young graduates who are under the internship programme at the centre; and serves and motivates school learners, students, educators and the surrounding community at large. As an honours graduate of the University of Limpopo, Refilwe’s MPhil in science and technology studies at Stellenbosch University examined the challenges of effective evaluation of science communication activities at science centres in Limpopo Province.

Chapter 8

The Cultural Distance Model: Empirical Evidence from India Gauhar Raza and Surjit Singh

Abstract Public understanding of science (PUS) is an area of research using contributions from various areas of expertise but focusing on the borders between science and society. It is a recent but growing area of research with its own strengths and limitations. The first phase of its development involved attitudinal surveys in many countries to measure the public’s scientific knowledge and probe the public’s attitude towards science and scientists. In many countries, regular survey studies have underpinned the allocation of special budgetary provisions. Later, researchers refined their methodology and developed new analytical tools and techniques to gain deeper insights into PUS. In India, researchers from the National Institute of Science, Technology and Development Studies (a unit of the Council of Scientific and Industrial Research) have worked since 1989 on techniques for surveys suitable for developing countries. As a consequence of that research, the research group has proposed a culturally sensitive model for evaluating the data. This chapter describes the historical background of the development of PUS research, with special reference to that simple but effective ‘cultural distance’ model. The authors confirm that the method of measuring cultural distance can be applied to various datasets to draw meaningful conclusions. Keywords Science · Communication · Public understanding · Cultural distance · Survey studies

8.1 Introduction: Historical Backgrounds of Conceptual Models Aristotle (384–322 BCE) summed up what had been an ongoing, centuries-long debate about what communication is. Building on the work of others, including his G. Raza (B) Council of Scientific and Industrial Research (CSIR), New Delhi, India S. Singh Department of Zoology, Indira Gandhi University, New Delhi, India © China Science and Technology Press 2021 B. Schiele et al. (eds.), Science Cultures in a Diverse World: Knowing, Sharing, Caring, https://doi.org/10.1007/978-981-16-5379-7_8

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teacher, Plato, he identified five elements of public debate: speaker, speech, occasion, audience and effect (Dow 2014). For centuries, that conceptual model went without any serious challenge or modification (Campbell 1963). Philosophers tell us that during the following few centuries the emphasis in communication shifted from helping citizens to make good publicly deliberated judgements to the ‘importance of language in communicating ideas to understanding systems of discourse that implicitly structure societies’ and then to ‘the process and product of a human symbolic interaction’ (Zalta 2010). A major turning point in the history of conceptual models of communication came when mathematician and engineer Claude Shannon published ‘A mathematical theory of communication’ in two parts (Shannon 1948a, 1948b). His major concern was to understand some of the fundamental properties of general systems for the transmission of intelligence, including telephones, radio, television and telegraphy. He stated that ‘the fundamental problem of communication is that of reproducing at one point either exactly or approximately a message selected at another point. Frequently the messages have meaning … These semantic aspects of communication are irrelevant to the engineering problem’. In short, Shannon developed a mathematical model to solve a practical problem in the emerging, highly technical subdiscipline of ‘communication and control theory’ in electrical engineering. The model soon became quite popular among social scientists, who were interested in mass communication, which was also an emerging phenomenon at that time. They thought that it could help them to understand social processes, as well. Shannon’s elegant, simple and now famous block diagram attracted their attention. Scholars soon realized the limitations of that mechanistic model, which efficiently explained various components of electronic circuitry but did not take into account the social, political, economic, cultural or religious contexts in which messages are constructed, sent or received (Petersons and Khalimzoda 2016). In the post-Shannon era, many scholars suggested new or modified conceptual frameworks for communication, but a universally accepted model was yet to emerge. However, Marshal Mc Luhan made the most significant scholarly contributions to our understanding of mass communication during this period (Aslam 2012). World War II and its aftermath profoundly affected all aspects of mass communication, including academic discourse and the efforts that philosophers, historians, scientists, educationists and social scientists made to understand the processes involved in mass communication (Miller 2010). The war and the postwar period brought many rapid changes. The Manhattan Project led to ‘big science’, for which publicly mobilized funds were now necessary. The bombing of Hiroshima and Nagasaki led to public debate and divided scholars into pro- and anti-science camps. The Cold War triggered cut-throat technological competition, the launch of Sputnik 2 (which carried a living animal into orbit) led to the restructuring of the science education system in the Western world, and the emphasis on science communication to the public increased greatly (Hughes 2003; Chin 2019; Haugsbakk 2013; Rossiter 1985). The effort to popularize science through the education system, media channels, public campaigns and dedicated science museums required substantial investments of both human and material resources.

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By the 1980s, the ‘need to know’ and the impact of those efforts to popularize science led to the formation of a new area of research that was initially called ‘scientific literacy’. Over the years, many other names for that work were suggested, and new peer-reviewed research journals were launched. Subsequently, scholars also proposed new conceptual frameworks to measure scientific information, attitudes, perceptions, knowledge and ‘temper’ among the public. There has been a lively and enriching debate about science communication in the 40 years since the 1980s.

8.2 Science Communication and Public Understanding of Science The percolation and propagation of scientific ideas, laws and methods among common citizens is a slow process. An idea or a method generated by the specialists in mental and physical workshops through intellectual labour can take years to reach the masses after its acceptance within the scientific community. Often, scientific ideas are processed through ‘social networks, information ecologies, and other macro-level variables that provide important social context’ and encounter filters of prevalent misinformation (Scheufele and Krause 2019). Simple scientific information, such as the fact that the Earth rotates, which today most people consider to be common sense, took a few hundred years to be widely accepted. As the pace of scientific development and the spread, efficacy and efficiency of communication channels increased, the speed of the flow of scientific information and the acceptance of new technologies among the masses have also increased (Stamm et al. 2000), but still varies greatly. Remarkably, that assertion has been proved correct during the recent COVID-19 pandemic (Raza et al. 2020).

8.3 Culture as a Determinant of Science Propagation While the recognition of the divide between science and its public understanding is as old as the entry of science into public discourse, the institutionalized area of investigation that has come to be known as the ‘public understanding of science’ (PUS) remains ill-defined (Wynne 1995; Huxster et al. 2018). In the early stages of that discourse, scholars realized that the science–public divide, besides being caused by a natural lag in knowledge generation, validation and dissemination, also has cultural causes. Although CP Snow had acknowledged the heterogeneity that exists among the various subgroups of scientists, for him the hallmarks of scientific culture were the common attitudes, common standards and patterns of behaviour, common approaches and assumptions prevalent among scientists. He concluded that ‘the scientific culture is really a culture, not only in an intellectual but also in an anthropological sense’ (Snow 1959: 9).

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The debate that followed Snow’s lectures questioned almost all the building blocks on which his argument rested, yet the conclusion that ‘science as a social activity and scientists as agents of knowledge generation have a distinctive culture’ remains the focus of that debate (Levis 1962). The problem is twofold. On the one hand, it is difficult to arrive at a universal agreement on what constitutes scientific knowledge or, for that matter, what constitutes ‘the scientific method’. Taking the debate further, John Durant pointed out that during their investigations scientists use ‘a great variety of exploratory stratagems’ to produce results that can first be accepted by the community of experts and then pass into the ‘corpus of existing knowledge’ and eventually be assimilated into the common citizen’s world view (Durant 1993). On the other hand, ‘the ambiguity of the concept of culture is notorious’ (Sardar and Loon 1997). Anthropologists attempted to define culture in many ways, but none of those definitions is universally accepted. One end of the definition-spectrum is occupied by statements such as that culture is ‘that whole complex which includes knowledge, belief, arts, morals, law, customs, and other capabilities and habits acquired by man as a member of society’ (Tylor 1924). On the other end, cultural anthropologists define ‘culture’ as merely a mental construct or an ensemble of stories we tell ourselves about ourselves. Clifford Geertz noted that ‘not only is it [culture] an essentially contested concept, like democracy, religion, simplicity, or social justice, it is a multiply defined one, multiply employed, ineradicably imprecise’ (Geertz 1999). The notion of the gap between science and the public and also the notion of the public have undergone radical changes over the past three centuries (BensaudeVincent 2001). In the eighteenth century, the wedge was positioned in the ‘style of argumentation’; later, with the ‘formalisation and mathematization of science it became [a] linguistic one’; in the mid-twentieth century, ‘scientists and ordinary people live[d] in two different worlds’. Bensaude-Vincent notes that, during the first two phases of the discourse, the public was not presupposed to be just a mass consumer of science; the notion of an ignorant public emerged only in the midtwentieth century.

8.4 The Deficit Model As is discussed above, it was widely recognized by scholars that there is a gap between peoples’ scientific knowledge and the knowledge generated by the community of scientists. Consequently, what came to be known as the ‘deficit model’ was proposed for measuring the gap between science and various segments of common citizens. Indicators for measuring the level of scientific literacy were developed, and large-scale surveys were administered, first in the United States and then in Europe and elsewhere (Miller 2001:116; Zhongliang 1991: 314). Without explicitly stating it, the conceptual framework pronounced a large segment of the population to be scientifically illiterate. Serious doubts about the purpose and intent of that approach finally brought the ‘end of the deficit model’, at least in the United Kingdom, if not

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in other parts of the academic world, among those engaged in large-scale survey studies. However, Steve Miller pointed out that the demise of the deficit model ‘does not mean there is no knowledge deficit’ among laypeople (Miller 2001). Those criticisms played a crucial role in the emergence of a more realistic perspective, usually termed as a ‘contextual approach’. Godin and Gingras, while analysing the evolutionary trajectory of various approaches, suggested that the generation of scientific knowledge and its appropriation are essentially a form of social organization of culture (Godin and Gingras 2000). It is crucial to point out here that the ‘contextual model’ suggested by them needs further refinement (Godin and Gingras 2000: 53). The model places the scientific community at the centre of a broad set of culture. There is a need to recognize that the large universal set of human culture consists of smaller subsets, each of which is protected by a boundary. Although the membranes between the subsets are permeable, they offer variable resistance to the transfer or even appreciation of knowledge, attitudes and perceptions from or by one cultural subset to the others. It is also important to note that those boundaries often cut across each other and must be defined in terms of the multidimensional socialization processes prevalent in a given society. For example, social determinants such as linguistic barriers (Lee et al. 1995) or caste differentiation or a combination of both could influence the permeability of the boundaries to a significant extent and consequently increase cultural distance.

8.5 Yet Another Fuzzy Definition of Culture Godin and Gingras suggested that ‘it is perhaps best to leave the notion of scientific culture to intuition rather than try to circumscribe it within a strict definition’ and thereby desist from any attempt to measure the gap between ‘science’ and the ‘public’. In the late 1980s and early 1990s, defying that warning, we proposed a conceptual model known today as the ‘cultural distance’ model. In the early 1980s, when we started working on indicators for a survey of PUS in India, the realization dawned that the indicators proposed by scholars in the United States and Europe would yield erroneous results in Indian conditions. Most of the indicators were likely to deem the Indian public to be ‘scientifically illiterate’. The reason for the obvious mismatch was not that scientific information had not reached the lay public, but the Indian public’s cultural, social and economic needs were different. The issues that were debated were quite diverse in a highly complex, multilingual and multicultural society. The realization that the problem was deeper and that changing a few indicators would not solve it led us to focus on the conceptual framework. The name ‘deficit model’ for what Jon Miller had proposed had not yet emerged, but it was quite evident that framework could not be used in Indian conditions.

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8.6 The Cultural Distance Model In this chapter, we have tried to sum up the debate about the cultural distance model and its application. As we have discussed, new ideas generated in a set of subculture (science, religion, literature, economics, politics and so on) take time to be disseminated and absorbed into the universal set of culture. The intracultural and intercultural fertilization of ideas also go through the same process, with a few more complex dimensions added to it. We have also discussed how permeable boundaries of cultures and subcultures allow the propagation of new ideas to varying degrees and with varying intensity. Thus, the process of generation, dissemination and absorption of ideas could be understood in terms of the distance that the idea travels to become part of a cognitive structure located in a given culture. Thus, cultural distance can be defined as the distance that a world view, attitude, perception or idea, generated within one cultural context, travels on a timescale before it is democratized within the thought structures of other cultural groups. Having proposed a working definition of cultural distance, we now make an attempt to test the hypothesis that various ideas generated within the scientific realm of thought can be placed at varying cultural distances from the day-to-day life and concerns of a set of common citizens. We have identified a few social determinants of the permeability of cultural membranes, but they are not the focus of the argument. We have observed that, as the inherent mathematical and conceptual complexity needed to explain a phenomenon increases, the pace of the propagation of knowledge about it slows progressively (Raza et al. 1996). An ordinary citizen who has not been exposed to higher levels of mathematics and abstract scientific ideas is likely to invoke intuitive, cultural or even religious explanations when confronted with a complex natural phenomenon (Raza et al. 1991), but such explanations cannot be construed as a measure of people’s scientific illiteracy or irrationality (Durant and Bauer 1992). Non-experts, including the illiterate segments of society, rely to a high degree on scientific explanations and have often expressed confidence in the scientific community, as was observed during a survey conducted in Delhi among plague-affected citizens (Raza et al. 1997).

8.7 An Empirical Method for Measuring Cultural Distance We propose a simple method for determining the cultural distance of a given explanation from the quotidian life of a common person, measured in years of socialization in modern education. We propose a dichotomous response variable in which the first category is constituted by valid scientific responses and all scientifically invalid responses are added together to form the second category. The percentage response variable is plotted on a scale constituted by years of formal schooling that a respondent has received. For convenience, let us call it the education variable and plot it

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on an x-axis. The y-axis characterizes the dichotomous percentage response variable and is represented by two curves: scientifically valid and scientifically invalid responses offered by interviewees. Because the response variable is dichotomous, the two curves will always intersect at a point where 50% of those interviewed offer valid scientific explanations. The perpendicular drawn from that point on the x-axis will show the education level required for the concept, idea or information to become part of the cognitive structure of 50% of the population under discussion. Let this point be termed the index of democratization (id) of the concept. An incremental increase in the level of education would mean that more than 50% of the population subscribes to the valid scientific explanation. Conversely, a concept, idea or information has to travel on the education scale for x years in order to achieve the threshold level id (or point of democratization) at a given point of economic and socio-cultural development. The idea here is not to establish that socialization in modern education is the only determinant that influences the world view of a common citizen and that a change in educational level will bring about an identical change in that person’s world view, irrespective of other factors. It has been shown repeatedly that a whole host of factors external to the nature of scientific information, such as gender, occupation, access to non-formal channels of information, economic status, predisposition to cultural and religious activities and age, have a bearing on the world view of cultural groups and subgroups (Raza et al. 1991). We propose to develop a scale on which the comparative cultural distances of various scientific concepts and information from the day-to-day lives of people can be mapped. The method proposed above helps to measure the distance of the index of democratization (id) from the origin on the x-axis. In most survey studies, respondents’ years of schooling are recorded as one control variable, followed by answers to questions related to indicators of PUS. Using curve-fitting techniques, any empirical dataset collected from the field can be used to determine the id and the distance (Xi) for each question (Ci) posed. The curve plotted on the two-dimensional graph (that is, the response variable versus education) can now be reduced to one-dimensional plot without the loss of any information. On the education scale, we could plot id for each concept at a corresponding cultural distance X, and also measure the distance of the concept from the quotidian life of those people who have been interviewed. The larger the distance Xi for a given natural phenomenon or concept, in the first quadrant, the further would be the phenomenon from the daily lives of those surveyed. Once the distances for a set of questions posed to citizens are determined, they could be plotted as bars arranged in ascending or descending order representing the absolute and comparative cultural distance of each concept from the thought complex of the sampled population.

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8.8 Testing the Method For the first time, in order to test the efficacy of the method explained above, we scrutinized data collected in a survey at the Kumbh Mela site in Allahabad (now renamed as Prayagraj) in Uttar Pradesh. Kumbh Mela is a religio-cultural festival (Bhattacharya 1983) held every 12 years at Sangam, at the confluence of two large rivers. Since the occasion attracts large numbers of pilgrims from all over India, especially northern parts of the country, it lends itself to many large-scale surveybased studies that would otherwise require much funding and time. In 1989, a research team administered the first survey of a representative sample of the northern Indian population during the festival. In all, 3,404 respondents were interviewed by trained enumerators. The schedule prepared for conducting interviews contained 26 questions in four areas of scientific inquiry: astronomy and cosmology; geography and climate; agriculture; and health and hygiene. The demographic data of each respondent was also recorded. Respondents were asked to complete an open-ended questionnaire in the form of simple statements. Each question was read out in precisely the same language, and each response was recorded in one of four categories: ‘scientifically correct’, ‘scientifically incorrect’, ‘extra-scientific’ and ‘don’t know’. While the enumerators were extensively trained in categorizing responses, they were instructed to record each one verbatim, in case of any ambiguity. The responses were later categorized by the research team. Each of the categories was assigned a code. Later, for the purpose of analysis. a dichotomous response variable was constructed by clubbing all the scientifically invalid explanations together. Since 1989, we have conducted five more rounds of survey studies using the same methodology at Kumbh Mela festivals, with gaps of six years between the Kumbh (Full) and Ardh (Half) Kumbh Melas.

8.9 Scale of Cultural Distance As mentioned above, we constructed a bivariate response variable in order to perform statistical tests. Scientifically valid responses were assigned a value of 1, and all other responses were grouped and assigned a value of 0. For the purpose of our analysis, out of all the independent variables, only the age and education level recorded for each respondent could be used as continuous variables. Therefore, those two were the only strong candidates for a proxy scale of cultural distance. It was observed (and has been reported in the past) that education has a strong association with all the other independent variables and that the influence of other demographic factors is reflected through socialization in modern schooling. The response versus education and response versus age graphs plotted repeatedly confirmed that hypothesis. Thus, education level was selected as a better choice for the proxy scale.

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The databases constructed and the dichotomous percentage responses plotted were used for testing the validity of the conceptual framework and the method for computing the cultural distances of various scientific concepts. The unit of analysis was a question posed to the respondent. The dichotomous percentage response variable was plotted on an 18-point education scale. Each point represented one year of socialization in modern education that the respondent had undergone. Ironically, opinion survey research in third world countries has benefited from the illiteracy that is prevalent in those societies. Universal and compulsory education is a dream that is yet to take material shape in Indian society. At every stage of schooling, individuals drop out of the formal system of education, so in the sample, there were many respondents at all the discrete points of the scale. We used curve-fitting techniques to determine the id and the distance Xi for each question ci posed in the surveys. The quadratic curve estimation facility available in SPSS enabled us to plot curves and obtain values of quadratic constants at 50%. Since the response variable was bivariate, it always intersected at Y = 50, so it was easy to compute the value of X using the quadratic equation solver. The value of X for a scientific idea was its cultural distance from the quotidian life of the Indian populace. The curves plotted on two-dimensional graphs (the response variable versus education) could now be reduced to one-dimensional plots. On the education scale, we could now plot id for each concept at a corresponding cultural distance Xi and also measure its comparative distance from the daily life of the respondents. The larger the distance Xi for a given natural phenomenon or concept in the first quadrant, the further would be the phenomenon from the quotidian life of the population segment under scrutiny. Once the cultural distances for a set of questions posed to the respondents were determined, they could be plotted as bars arranged in ascending or descending order, representing the absolute and comparative cultural distances of each concept from the thought complex of the sampled population. In order to compute the average cultural distance of a knowledge area, such as ‘astronomy’, the cultural distances of all questions related to astronomical phenomena were added. We divided that result by the total number of questions in the area of ‘astronomy’. The average cultural distance for each area was used for comparative analysis. This method led us to the conclusion that the area of ‘astronomy and cosmology’ could be put on the farthest end and that the area of ‘health and hygiene’ was closest to the peoples’ thought structures. Results over the past 30 years have shown that, although the positions of knowledge areas shifted on the scale and the magnitude reduced, the relative positions of areas did not change. In other words, the average cultural distance of all the areas has decreased and overall PUS has increased, but factors intrinsic to scientific knowledge continue to place far thicker resistive filters against the permeation of notions related to ‘astronomy and cosmology’ compared to ‘health and hygiene’. The following equation illustrates the shift in cultural distances over the years: Xci =



Xcit2 −



Xcit1

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where Xci t2 t1

denotes the shift in cultural distance of a specific scientific concept ci. is the latest point of observation on the timescale. is the earliest point of observation on the timescale.

Curiously, for some notions, such as the roundness of the Earth, cultural distances showed negative polarity. On the plot, the point of intersection of the response variable (id, the index of democratization) lay in the fourth quadrant. Apparently, it shows negative education. However, it proved our hypothesis that the education scale when applied in this empirical method operates as a dummy variable. Empirically, the cultural distance could lie anywhere between minus infinity to plus infinity. When the computed cultural distance for a phenomenon lies in the fourth quadrant (with negative education value), that shows that more than 50% of even those who have never been through any formal education (illiterates) understand the scientific explanation. It is evident that this segment of society, which has never been to school, received the scientific explanation through social educative processes. Conversely, for all those scientific phenomena that show the negative polarity of cultural distance, society has taken charge of educating common citizens and does not need the intervention of formal schooling to propagate the scientific explanations for such natural phenomena. On the other end of the scale, we also found that the magnitude of cultural distance for some concepts that lay in the first quadrant was far more than 18 years. This was the highest level of recorded formal education. Evidently, this also validates our suggested empirical methodology. Based on values of cultural distance higher than 18 years, some scientific concepts could be categorized as ones that do not get absorbed into the cultural thought structures of citizens even after those citizens go through modern educational training.

8.10 The Versatile Nature of the Cultural Distance Model We live in a highly segmented society even in developed countries; however, cultural, social, educational, economic and geographical divergence is quite pronounced in developing countries. The suggested method helped us to map the population in many different ways. For example, we categorized the sampled population based on people’s reported geographical locations. Subsequently, cultural distances between each set of provincial population and all scientific phenomenon were computed. Once the values were obtained, two types of maps could be prepared. First, the province was located in the centre and scientific phenomena were placed at their relative cultural distances. Second, the phenomena were placed in the centre and all the provinces were placed at their respective cultural distances. The method helped us to identify areas of effective intervention at both the micro and macro levels of categorization of cultural groups. It also helped in the cultural-distance-wise categorization of discrete

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scientific explanations and areas of scientific investigation, which may need relatively more intense efforts to communicate them to a specific set of common citizens.

8.11 Conclusions The research team introduced the conceptual framework called the ‘cultural distance’ model in 1989. As opposed to the notion of scientific literacy, or what has now come to be known as the deficit model of PUS, we introduced the analytical framework of cultural distance between the structures of thinking prevalent among the public and the scientific knowledge system. We identified four factors, intrinsic to the nature of scientific knowledge, that influence cultural distance: • • • •

the complexity involved in explaining a scientific phenomenon the control that an individual or a group can exercise in altering its life cycle the duration of that life cycle the likely impact that the phenomenon can have on human existence.

Let us call these factors ‘CCDI’. We have shown that we can observe comparative distances between the areas of scientific knowledge and between issues within a given area. It was repeatedly found that the area of ‘astronomy and cosmology’ occupied the farthest end of the cultural distance scale and that ‘health and hygiene’ could be placed closest to the cultural life of common citizens. Over the past 30 years, the application of the cultural distance model has shown that scientific ideas generated in laboratories can be placed at different levels of cultural distance. Depending upon factors extrinsic (demographic) and intrinsic (CCDI) to science, each scientific notion must overcome a variable distance in order to become part of the cognitive structure of common citizens. In other words, cultural groups or subgroups will respond to an idea depending upon how far it is from their sociocultural thought complexes. We have demonstrated that this methodology could help in: • mapping the cultural distance of various scientific phenomena from peoples’ dayto-day lives, which are determined by their cultures • computing the aggregate cultural distance of a scientific discipline or subdiscipline in order to shape public discourse • developing communication strategies suitable for particular groups, since the cultural distance of a phenomenon or a scientific discipline is likely to vary among cultural groups and a uniform strategy might not work.

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References Aslam M (2012) A diagramatic study of different models of mass-communication. Global Journal of Human Social Science, Arts & Humanities 12(13). https://globaljournals.org/GJHSS_Volume12/ 4-A-Diagramatic-Study-of-Different.pdf Bensaude-Vincent B (2001) A genealogy of the increasing gap between science and the public. Public Underst Sci 10:99–113 Bhattacharya N (1983) The cultural heritage of India: vol. IV: The religions. The Ramakrishna Mission, Institute of Culture, Calcutta Campbell G (1963) The philosophy of rhetoric. Bitzer LF (ed). Southern Illinois University Press, Carbondale Chin W (2019) Technology, war and the state: past, present and future. International Affairs, July, 95(4):765–783 Dow JPG (2014) Proof-reading Aristotle’s Rhetoric. Archiv Für Geschichte Der Philosophie 96(1):1–37 Durant J (1993) What is scientific literacy? In: Durant J, Gregory J (eds) Science and culture in Europe. Science Museum, London, 129–137 Durant J, Bauer M (1992) British public perception of astrology: an approach from the sociology of knowledge. Paper presented at annual meeting of the American Association for the Advancement of Science, Chicago. Geertz C (1999) A life of learning. Charles Homer Haskins Lecture for 1999, occasional paper no. 45, American Council of Learned Societies Godin B, Gingras Y (2000) What is scientific technological culture and how is it measured? A multidimensional model. Public Underst Sci 9:43–58 Haugsbakk G (2013) From Sputnik to PISA shock—new technology and educational reform in Norway and Sweden. Education Inquiry 4(4). https://www.tandfonline.com/author/Haugsbakk% 2C+Geir Hughes J (2003) The Manhattan Project: big science and the atom bomb. Columbia University Press Huxster JK, Slater MH, Leddington J, LoPiccolo V, Bergman J, Jones M, McGlynn C, Diaz N, Aspinall N, Bresticker J, Hopkins M (2018) Understanding ‘understanding’ in public understanding of science. Public Underst Sci 27(7):756–771 Lee O, Fradd SH, Sutman FX (1995) Science knowledge and cognitive strategy use among culturally and linguistically diverse students. Journal of Research in Teaching 32(8):797–816 Levis FR (1962) Two cultures? The significance of CP Snow. Chatto and Windus, London Miller E (2010) Linguistic politics: creating a communication canon post World War II. McNair Journal, 6. https://scholarworks.boisestate.edu/mcnair_journal/vol6/iss1/11/ Miller S (2001) Public understanding of science at the crossroads. Public Underst Sci 10:115–120 Petersons A, Khalimzoda LI (2016) Communication models and common basis for multicultural communication in Latvia. Proceedings of the International Scientific Conference: Society. Integration. Education, 27–28 May, IV:423–433 Raza G, Singh S, Dutt B, Chander J (1996) Confluence of science and people’s knowledge at the Sangam. Ishtihaar, New Delhi Raza G, Singh S, Dutt B, Wahid A (1991) Prototypes of the forms of scientific cognition: a survey of cultural attitude to natural phenomena. NISTADS reports I and II Raza G, Singh S, Kumar PVS, Dabiru L (2020) Pulse of the pandemic: a sudden surge in scientific attitude during Covid-19 crisis. Anhad and PMB Foundation Raza G, Dutt B, Singh S (1997) Kaleidoscoping public understanding of science on hygiene, health and plague: a survey in the aftermath of a plague epidemic in India. Public Underst Sci 6:247–267 Rossiter MW (1985) Science and public policy since World War II, Osiris, Historical Writing on American. Science 1:273–294 Sardar Z, Loon BV (1997) Introducing cultural studies. Totem Books, New York

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Scheufele DA, Krause NM (2019) Science audiences, misinformation, and fake news. Proceedings of the National Academy of Sciences of the USA, 16 April, 116(16):7662–7669. https://www. ncbi.nlm.nih.gov/pmc/ articles/PMC6475373/citedby/ Shannon CE (1948a) A mathematical theory of communication, Bell System Technical Journal, July, 27(3):379–423 Shannon CE (1948b) A mathematical theory of communication. Bell System Technical Journal, October, 27 (4):623–666 Snow CP ([1959] 1993) The two cultures. Cambridge University Press, Cambridge Stamm KR, Clark F, Eblacas PR (2000) Mass communication and public understanding of environmental problems: the case of global warming. Public Underst Sci 9:219–237 Tylor B ([1871] 1924) Primitive culture, 7th edition. Brentano’s, New York Wynne B (1995) Public understanding of science. In: Jasanoff S, Markle GE, Peterson JC, Pinch T (eds) Handbook of science and technology studies. Sage, London, 361–388 Zalta EN (ed.) (2010) The Stanford encyclopedia of philosophy, Spring edition. https://plato.sta nford.edu/ Zhongliang Z (1991) People and science: public attitude in China toward science and technology. Science and Public Opinion, October, 18:311–317

Gauhar Raza is a former scientist at CSIR (Council of Scientific and Industrial Research), India, and involved in large-scale survey studies on public understanding of science. He is also involved in science film making for science communication. Surjit Singh has superannuated from CSIR (Council of Scientific and Industrial Research), India, and is now in the teaching profession. He has been involved in survey studies on the public understanding of science, including HIV/AIDS awareness programmes.

Chapter 9

Science Culture: A Critical and International Outlook Michel Claessens

Abstract The chapter reviews the importance of science culture and puts it in an international context. Although a consensual definition of science culture is still missing, it is widely considered as a major factor that supports research and innovation and the values attached to them (such as respect for evidence and analysis and trust in scientific expertise). The evidence shows that the public’s science culture does scale with understanding of science and economic development. Formal education, as well as informal outreach, are critical in this respect. There is also a lack of an international and consistent approach to science culture, although it could benefit a lot from international exchanges on its definition, measurement and good practices. The chapter introduces the WISE (World Investigation of Science Culture) project, which aims to bring together organizations and countries to join forces in an informal alliance to define, measure and promote science culture globally. Keywords Science culture · Science literacy · Opinion surveys · International · Eurobarometers

9.1 Introduction Does science culture genuinely exist as a property that can be measured? If it exists, how do we define it? How does it differ from science literacy or the public understanding of science? The debate about the origin, the history and the very existence of science culture is ongoing. Some scientists argue that science does not deserve any specific territory within people’s culture because it is silently flourishing and permeating that culture (Lévy-Leblond 2020). However, there is also evidence that, in recent decades, the average understanding of science, which includes the understanding of scientific methods and scientific values, is underdeveloped and therefore requires specific remedial actions. In the United States, for example, various stakeholders are claiming

M. Claessens (B) European Commission and Free University of Brussels, Brussels, Belgium © China Science and Technology Press 2021 B. Schiele et al. (eds.), Science Cultures in a Diverse World: Knowing, Sharing, Caring, https://doi.org/10.1007/978-981-16-5379-7_9

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that what they perceived to be a decrease in Americans’ science literacy can be interpreted as a disengagement from science or, at best, an ambivalent relationship with science (Snow and Dibner 2016). Conversely, Kahan et al. (2012) explored the effects of science literacy and numeracy on attitudes to climate change and found that both scientific knowledge and numeracy were associated with decreased risk perceptions regarding the dangers of climate change. As a result, science literacy and even science culture1 are now seen as important issues that are receiving growing and widespread attention and recognition in recent years, even at the highest political levels. It is accepted that nations should not only increase funding for science but also promote science literacy and science culture, and, more generally, an environment supportive to science and technology in order to develop scientific research and celebrate science values such as respect for evidence and analysis and trust in scientific expertise. However, there are more than a thousand science museums and science centres around the world, so it is fair to say that, to some extent, humankind celebrates science and technology as much as we celebrate the arts and humanities.

9.2 What is Science Culture? From a scientific point of view, the notion of ‘science culture’ is a conceptual as well as an empirical challenge for scholars and social researchers. Science culture is both a social fact to be measured and a concept to be clarified. There is no clear consensus about the precise definition of science culture, which is likely to involve a range of different components, including public discourse and debates about scientific issues, scientific knowledge, evaluative beliefs about the risks and benefits of science, the trustworthiness of experts, norms for science and individual self-efficacy. Overall affect and discrete emotions and how people frame scientific issues are also likely to prove to be important components of science culture. According to recent research, science culture appears to dynamic, as its various components may be more or less important depending on the context. Although science culture is usually seen as the responsibility of individuals, individual science culture also thrives thanks to the more general cultural contexts in which people live (Snow et al. 2016). Taking into account the fact that science and innovation culture depends on individual differences as well as on local, cultural, social and political contexts, Bauer et al. (2016) describe science culture not as an aggregation of a set of variables but as a structural pattern of relations between those variables. It is therefore relevant to distinguish scientific culture from science culture (Bauer et al. 2016). The former relates to science and technology as a ‘system’ and more specifically to the conditions of and the performance of science and innovations in inputs, process and outputs. The latter describes the general environment (society) in 1

For the purposes of constructing indicators of science culture, literacy is not the target variable, but one of the elements to consider (Bauer et al. 2016).

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which science and technology develop while being supported and considered as social values. This obviously depends on subjective and cultural factors. Culture is often understood as general patterns of behaviour, thinking and striving that characterize a community (sectoral or local). While science is a global activity, science culture may be influenced by local factors. Depending on each country’s conditions, individual opinions on science are disseminated by social structures and influence to some extent the governance of scientific matters. Despite the lack of a universal definition, supporting the development of science culture is considered to create a positive environment that will benefit both basic research and innovation. It is widely accepted that science culture is important, as it provides the public with adequate knowledge about science and technology to understand, question and operate in a technoscientific society such as ours. Also, promoting scientific culture supports a shared belief that scientific expertise can be trusted and will let the public know about what is scientifically plausible and possible, and what is not. A recent study conducted in Africa (NAS 2020) concludes that ‘science advice should seek to provide leaders at all levels of society with the most relevant and current evidence available to help guide their decision-making process. Ultimately, all of these various strategies are ways to shift the overall science culture so that science can play a more prominent role in development.’ Last but not least, the environment promoted by science culture contributes to the innovation potential of a social group, and hence to economic expansion. From a large-scale sample of statistical data collected in Europe and India, it has been shown that people’s knowledge of science does scale with economic development (Shukla and Bauer 2009). Formal education, as well as informal outreach, are critical in achieving this goal. Thus, several countries and organizations—including the United States, the European Union, China and Switzerland—are regularly conducting public opinion surveys to assess national averages and trends in the public’s science literacy/culture. For example, China’s President, Xi Jinping, declared on 17 September 2018 at the opening of the World Conference on Science Literacy in Beijing that China will work with other countries to promote scientific education and literacy domestically and abroad, leading to more innovations that can benefit national and social sustainable development (Zhihao 2018). In fact, that objective is embedded in China’s National Action Plan for Scientific Literacy 2006–2020, which aims to improve national scientific literacy by investing in education across China and popularizing knowledge of science and technology. However, as pointed out in a recent report of the committee on science literacy and public perception of science of the US National Academies of Sciences, Engineering and Medicine (Snow et al. 2016), there is still a lack of an international and consistent approach to science culture, which would benefit from national comparisons and allow one to make robust inferences about the relationship between average scores on common measures of science literacy and the putative consequences of enhanced science literacy. Furthermore, despite the fact that science and technology concepts and applications are omnipresent in our daily lives, there is a widely shared concern that

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science culture may be underdeveloped and even underdeveloping. Indeed, some recent trends, such as the expansion of anti-science movements at the highest societal and political levels (for example, growing opposition to vaccination, climate sceptic theories, denial of the natural origin of SARS-CoV-2 and antiviral drugs recommended without any scientific evidence), seem to show that the influence of science and scientific expertise could be at stake. A recent study carried out for the European Parliament found that increased access to information and communication technology, the development of artificial intelligence and a growing mistrust of traditional sources of information are creating a favourable context for the spread of misinformation and disinformation on science-related issues. Hence, the authors conclude that ‘fostering scientific literacy among the population has never been more essential’ (Siarova et al. 2019). But this will also require a shift in scholars’ approach to science culture. As pointed out by Le Marec and Schiele (2018), that approach is still too passive and often limited to the observation that the sciences are at the heart of ‘modernity’, as they modify values just as they modify social modes of organization. As shown by Bauer and Suerdem (2016), science, progress and modernity are closely connected. However, attention should be paid to not reducing the role of science and technology in the process of modernization to merely providing productive power and fuelling economic growth for well-being. Recent narratives about ‘biosociety’, the ‘information age’ and the ‘nuclear society’ tend to position science and technology as the mere productive force of a ‘scientific–technological civilization’. There is a need for a more proactive approach to science culture that explicitly recognizes ‘science’ as the primary objective.

9.3 A Tradition Being Reconstructed Promoting the wider diffusion of scientific knowledge is probably an activity as old as science itself.2 In France, for example, science cabinets were established in the eighteenth century. As science became increasingly institutionalized, scientists were actively involved in sharing with the public the results of research and the progress of knowledge. At the end of the nineteenth century, the dissemination of scientific knowledge was accelerated and amplified by the introduction of obligatory school education and a long-standing practice of popularizing the major scientific advances. In the past century, well-known scientists such as Carl Sagan, Stephen Hawking, Freeman Dyson, Hubert Reeves and Stephen Jay Gould were celebrated also for their talent in science popularization. Along with the professionalization of scientific research, countries with a strong science tradition established institutional structures to disseminate scientific results with the aim of developing science culture overall by bridging science and society and integrating scientific knowledge into the layman’s culture. France, in particular, 2

This section is adapted from M Claessens (2018).

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became a major player in the promotion of science culture by participating in the evolution of those practices. Landmarks included the establishment of the Museum of Natural History and the Conservatoire National des Arts et Métiers (inaugurated in 1793 and in 1794, respectively), the Palais de la Découverte (1937), the first Centre for Scientific, Technical and Industrial Culture (La Casemate) in Grenoble (1979), the Association of Museums and Centres for the Development of Scientific, Technical and Industrial Culture (1982) and the City of Science and Industry (1986). That is a long string of accomplishments, as measured by the volume and level of activities, both practical (events, training, media coverage) and academic (specialized journals, doctoral theses and so on). As a result, there is today a very large diversity of initiatives, practices and experiments aiming to develop science culture and covering a continuum of objectives and publics (see Fig. 9.1). Some scientists, however, do not depart from the idea that developing the culture of science and enriching the culture with science are close to une mission impossible. Despite significant achievements, the situation has become somewhat confused, both in terms of the means to be used and the objectives to be achieved. As far as the means are concerned, reflection on the practices and the statutes of science communication and science culture continues. After several years of promoting the public understanding of science and addressing the weaknesses pointed out by the well-established deficit model (Schiele 2018), the focus is now on communication, dialogue and ‘public engagement’ (Table 9.1). Key actors of science culture include the so-called mediators of science. They contributed to the professionalization of this field by integrating communication techniques, interactivity, multimedia, games and so on into their approach. However,

Fig. 9.1 Actions aiming to promote science culture cover a large variety of target publics, methods and objectives

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Table 9.1 A brief history of activities aimed at developing science culture in Europe 1799

Foundation of the Royal Institution—the first British public laboratory. Public lectures are an immediate feature of its work

Popularization

19th–21st C Books written by scientists (Flammarion, Sagan, Greene etc.) 1945

BBC starts science programmes on its Home Service radio

1959

CP Snow, The Two Cultures (sciences and humanities)

1972

First public opinion survey about science (France)

1985

UK Royal Society publishes The Public Understanding of Science (the Bodmer report). Scientists must ‘consider it their duty’ to communicate with the public about their work

1989

First Eurobarometer on science and technology

2002

European Union launches Science in Society programme (FP6),

2002

Participants in EU-funded R&D projects have a contractual obligation to communicate their results to the public

End 20th C

Two-way communication (opposition to GMOs, etc.), Dialogue but not only the public should be expected to listen and change their views

21st C

Science is a social activity and should involve the public as well

Engage with the public

Social dimension

despite the wealth of activities across the world, a quick look at the results immediately raises some concern: for example, almost one in three Europeans still believes that the Sun is orbiting the Earth (European Commission 2005). There is also a lot of confusion as far as the objectives are concerned. What is the priority? What do ‘we’ want to achieve? Across the world, a number of studies have shown that young people’s interest in science and technology declines with school years, along with their intention to pursue studies or careers in scientific and engineering disciplines (Potvin and Hasni 2014). Therefore, supporting science culture has emerged as an essential activity to make science more attractive and restore confidence in science. Genetically modified organisms, nanotechnologies and subatomic factories: are these controversial scientific and technical advances only the most visible part of a public opinion that seems now less supportive, in part because laypeople do not master the basic concepts and the scientific method? Showing a sense of modesty, museum and science centre managers, video producers and bloggers seem to converge as far as the end result of their activity is concerned: the aim is less to spread knowledge and raise interest in science than to spend a nice moment in a point of space–time dedicated to popularization.

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To add more to the general confusion, it also likely that, in order to obtain additional financial resources, scientists and stakeholders are now describing scientific culture as a political action and consider it as a toolbox enabling citizens to get involved in decision-making. But the circumstances have also called for some realism: consensus conferences, for example, which organize an explicit confrontation between skills and incompetence, do not lead to any rejection of technoscience. By recognizing people’s right to judge technoscientific subjects ‘in total ignorance’, society drove a radical U-turn compared to what Philippe Roqueplo wrote in 1974: ‘People living in a society like ours should have a minimal technoscientific background to understand its evolution and take part in decisions in a constructive way.’ To make things even more complicated, a large number of researchers, who overwhelmingly support science communication and the dissemination of scientific information, recognize that the need to spend more time on research is stopping them from engaging with the public (Royal Society 2006). In the same study, researchers stressed that public engagement might have a negative impact on their careers and considered that it should be carried out by those who are ‘not good enough’ for an academic career. Today, it is fair to say that supporting scientific culture, which can be considered in this historical perspective as a pedagogical dissemination of scientific knowledge in its broadest sense, seeking to make it (possibly together with its limits and uncertainties) accessible to non-experts, is still necessary and important, but the reasons for that commitment today have changed somewhat—or expanded. As citizens are now considered to be full players in research and innovation, this implies that the walls between scientists and citizens no longer make sense, as they are all contributing to research advances and societal choices. However, that commitment also has its own limits: the solutions to the current major challenges are not only technological but also require social, political and economic choices. Today, the so-called technosciences are fully part of our daily lives and of our modernity, although the public has some difficulty in following the transformations of our increasingly technological and rapidly changing world. Considering that the bulk of research and its applications are still discussed and decided without them, citizens feel ‘left behind’, and scientists also feel that they are not always heard or even listened to (as the recent COVID-19 pandemic has abundantly demonstrated). Many countries, with obvious success, are supporting activities related to communication, scientific mediation and engagement with democratic debate on collective issues in order to promote science culture while rebuilding trust and strengthening the links between science, technology and society. That work is incomplete, as shown by compelling evidence. The risk is that, by targeting several publics and several objectives at the same time, the action is diluted and becomes less meaningful. Finally, progress is still needed to recognize that raising the public understanding of science and promoting science culture is an integral part of the work of scientists and, as such, deserves to be recognized and valued throughout their careers.

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The century-old tradition of science culture is currently being reconstructed in almost every country. However, that should not allow us to conclude that populations are scientifically illiterate or even ignorant. Results and analyses from Eurobarometer surveys over the past decades confirm that science and technology are important values for Europeans. As discussed in the next pages, the European surveys may support the idea that scientific knowledge and even science culture are progressing, at least in Europe, and at least during a limited period of time. Other results show that Europeans are ‘better educated’ in science than they think and underestimate their own level in this field (Claessens 2010). Many science festivals attract several million visitors each year, and some popular science books, films, videos and blogs capture impressive audiences. These results can be seen as positive repercussions of initiatives taken by more and more numerous actors, and even as a plebiscite in favour of scientific culture.

9.4 The Failed Concept of EU Science Culture There is a long tradition of promoting science culture, particularly in European countries, but, in contrast, very few initiatives have been taken at the European level. Could this mean that a transnational approach is not suitable for addressing science culture, which is deeply rooted in its local environment? It was only in 1993, under the European Union’s Third Framework Programme (1990–1994) that the European Week for Scientific Culture was launched by the European Commission, following the personal commitment of the then Commissioner for Research, Antonio Ruberti. As explained below, the success and the impact of that initiative were rather limited. The reason is, at least in part, that culture in general and science culture in particular are not seen and perceived as an international top-down endeavour but rather as a local bottom-up activity. The aim of the European Week for Scientific Culture, which ran until 2010, was twofold: first, to support awareness-raising activities on the European dimension of science; second, to develop Europe-wide public understanding activities already going on in the EU member states. The initiative was based on the general assumptions that scientific knowledge is considered to be part of science culture and even general culture, and that popularizing and disseminating that knowledge is of paramount importance. Existing research also provides compelling support for the idea that communities can possess and use science literacy to achieve their goals and may contribute to new science knowledge in doing so. Thus, for more than 10 years, the European Commission has been supporting a range of projects that have involved, in particular, young people from different member states. These cooperative ventures aimed at showing—rather than telling— (young) Europeans, through transnational and coordinated projects, how science and technology affects them, from the simplest gadgets to the most sophisticated satellite technology. As a result, the week provided a framework for demonstrating to

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the public the existence of a ‘European science’ through a diverse range of EUfunded activities, such as competitions, exhibitions, interactive internet debates, school projects and videos. In the course of 1997 and 1998, it was decided that the week would become formally part of the European Union’s Fifth Framework Programme (1998–2002) and it was grouped with three new activities (networks, round tables and information services) aimed at raising public awareness of science and technology under the action line ‘Promoting Scientific and Technological Excellence’ of the Human Potential programme. At the same time, the week became the European Week for Scientific and Technological Culture so as to highlight the fact that many projects were not just about ‘blue sky’ research but also about concrete and technological applications. This change, which explicitly placed the week as part of the big EU funding machinery, did not meet those expectations. The underlying association of science culture with other activities such as networks and information services obviously raised more questions than it provided answers. In fact, the European Commission was at that time trying to relaunch the week and give it another impetus, as the scale of activity remained very modest and the impact marginal. In order to increase the participation base, introduce competition between ideas for projects and ensure that projects were selected on the basis of equality of treatment and transparency criteria, it was decided that proposals would be solicited through calls for proposals published annually. The European Week for Scientific and Technological Culture continued until 2007 (with projects running until 2010), and on average a dozen proposals were funded each year for a total budget which, by EU standards, remained very modest (typically e1–2 million). Following an external assessment of these activities, the European Commission decided to interrupt the week in 2007. The main reason was that the week funded lots of very small local activities with a limited added value and a marginal impact on the research community and the public. Most of the projects proposed and funded by the week were not perceived as being part of a larger challenge, despite the fact that, at their individual levels, they ‘delivered the goods’. Clearly, the EU budget was too low to fund a critical mass of substantial projects. In consequence, the European Commission abandoned the week and sought to fund activities that would introduce a European dimension into national science weeks but, again, success was limited. Then, the commission tried to coordinate science weeks across Europe, hoping that that would have a bigger impact and create a genuine European dimension. The underlying objective (which did not receive wide support across the scientific community) was to have one single event—a kind of giant ‘European’ science week across the whole continent—on the assumption that this would generate great visibility and awareness and have a huge impact on the public. To achieve that aim, the European Commission set up an ad hoc expert group, which met several times. But there were many good arguments against such coordination: the situation that prevailed so far gave more flexibility to national coordinators and allowed for exchanging some material and sharing some development costs. Despite several trials, the commission’s attempts to encourage the consolidation of national science weeks around one

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or two dates in the calendar clearly failed: member states’ science weeks remain uncoordinated and take place at different dates in the year. To a large extent, science culture in Europe remains a national endeavour.

9.5 Assessing the Scientific Knowledge of Europeans Since 1974, the European Commission has conducted ‘Eurobarometers’, which are regular public opinion surveys on a wide variety of topical issues across all EU member states. Eurobarometers are managed by the European Commission’s Directorate-General of Communication, and the reports and data are publicly available.3 As a result, the commission maintains one of the world’s largest databases of public opinion surveys. Aside from the ‘general’ Eurobarometers, which are designed to compare and gauge trends within EU member states, the commission conducts supplementary surveys on special topics such as agriculture, biotechnology, consumer behaviour, elderly people, energy, the environment, science and technology, urban traffic, working conditions, youth and so on. One of the Eurobarometer’s strong points is that it allows us to conduct at the same time face-to-face interviews in all the EU member states, plus possibly additional countries such as associated states. It also allows us to build up time series that can provide insights into the evolution of public opinion, provided that the questions used by the successive surveys are kept identical across a significant time span. Against that background, the European Commission has used the Eurobarometer instrument to try to evaluate the attitudes of Europeans towards, and public understanding of, science and technology in 1977, 1989, 1992, 2001, 2005, 2007, 2010, 2015. The most recent Eurobarometer results were published in December 2014 (European Commission 2014). A new Eurobarometer on science and technology should be published in 2021. According to these surveys, European citizens appear to have a clear and positive opinion about science and technology (Claessens 2008). However, they have a less clear insight into the work of the scientist, what a scientist actually does or the structure of the scientific community. Europeans also want political decisions to rely more on experts’ advice. Interest in science and technology is high: 70–80% of European citizens are very or moderately interested in new scientific discoveries, although that proportion has decreased somewhat since 1992. The proportion of people who are ‘very interested’ in science and technology issues also seems to have decreased since then. Until 2005, science and technology Eurobarometers typically included a dozen questions on science and technology issues (see Table 9.2). Unfortunately, the commission then discontinued this ‘quiz’ approach to science knowledge.

3

European Commission, ‘Public opinion’, https://ec.europa.eu/commfrontoffice/publicopinion/ind ex.cfm.

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Table 9.2 Questions on science and technology included in Eurobarometer no. 224 (2005) ‘For each of the following statements, please tell me if it is true or false. If you don’t know, say so, and we will go on to the next one’ Average number of answers (32 countries) Quiz statements (T = true; F = false)

True (%)

False (%)

Don’t know/no answer (%)

The Sun goes around the Earth (F)

29

66

4

The centre of the Earth is very hot (T)

86

7

7

The oxygen we breathe comes from plants (T)

82

14

4

Radioactive milk can be made safe by boiling it (F)

10

75

15

Electrons are smaller than atoms (T)

46

29

25

The continents on which we 87 live have been moving for millions of years and will continue to move in the future (T)

6

8

It is the mother’s genes that 20 decide whether the baby is a boy or a girl (F)

64

16

The earliest humans lived at 23 the same time as the dinosaurs (F)

66

11

Antibiotics kill viruses as well as bacteria (F)

43

46

11

Lasers work by focusing sound waves (F)

26

47

28

All radioactivity is man-made (F)

27

59

14

Human beings, as we know 70 them today, developed from earlier species of animals (T)

20

10

It takes one month for the Earth to go around the Sun (F)

66

16

17

Source EuropeanCommission (2005)

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These questions do not pretend to measure the level of ‘science culture’ of Europeans; nevertheless, they provide interesting information on (some form of) the public’s scientific knowledge and its evolution over time, at least between 1992 and 2005. The results of this knowledge quiz show that, for all statements, the majority of people interviewed answered correctly. The average proportion of correct answers reached 66%, while that of wrong answers was quite low at 21%. However, one should not conclude from this that Europeans have a fairly good knowledge of scientific topics, as answering the quiz at random would give an average proportion of correct answers of close to 50%. More interestingly, national averages show that there has been a clear rise in the number of correct answers to the quiz since 1992 (Fig. 9.2). That is the case in practically all countries surveyed. Average correct quiz answers rose significantly between 1992 and 2005 in countries such as Luxembourg (+19%), Belgium (+18%), Greece (+17%), the Netherlands (+16%), and Germany (+15%). Although these results date back a number of years, the increase in correct answers is undoubtedly a stunning development related to science in Europe. Since the previous surveys in 1992 and 2001, scientific knowledge, as measured by the Eurobarometers, had increased substantially in 2005 in several European countries. Further analysis of the Eurobarometer data confirms the overall trend towards higher scientific literacy in all European countries. There is obviously an apparent contradiction here. Although Europeans were showing a declining interest in science and technology and claiming to be poorly 20 18 16 14 12

10 8 6 4 2 0 LU

BE

EL

NL

DE

PT

DK

IT

IE

FR

ES

UK

Fig. 9.2 Improvement in the percentage of correct answers to the Eurobarometer scientific quiz in 12 European countries, 1992–2005

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informed on the subject between 1992 and 2005, their answers to the basic scientific knowledge test paradoxically improved. However, the reason for that apparent increase in scientific knowledge is far from obvious. A possible contribution may have come from the topics highlighted by the news and media coverage during the period from 1992 to 2005. After the Indian Ocean tsunami in December 2004, the percentage of people who understand the movement of continents and tectonic plates seems to have risen by 20%. Analysing the slight improvement in Japanese people’s understanding of science between 1991 and 2001, Shimizu (2007) argues that the 1995 Kobe earthquake contributed to the public understanding of plate tectonics, but more so among non-college-educated people than among the college educated. Similarly, one may argue that media coverage of crises and controversies that happened in the 1900s and 2000s in Europe (such as Chernobyl, mad cow disease, contaminated blood, avian flu, SARS, nuclear energy and GMOs) has brought many scientific and technological concepts and issues onto the public radar and has subsequently raised overall public understanding of science in the EU countries. Along the same lines, the ongoing COVID-19 pandemic may improve public knowledge about viruses and infectious diseases. This analysis, although dating back a number of years, provides encouraging information and openings regarding the development of scientific knowledge and possibly science culture.

9.6 An International Approach to Science Culture Despite the fact that the number of countries administering national public opinion surveys to measure the public’s attitudes towards science and general knowledge of science has grown significantly since the 1970s, very few initiatives are tackling science knowledge, let alone science culture, in an international framework (see Table 9.3). Most surveys target adult populations using a small set of quiz-like questions to measure the public’s knowledge of science/technology and in some cases of scientific method. Most of these surveys share similar if not identical questions. However, as pointed out by Shukla and Bauer (2009), little progress has been made in explicitly combining science–technology–society (STS) performance indicators and public understanding of science (PUS) indicators in a composite index of ‘science culture’. There is no publication that compiles and integrates results from all of these surveys. The main problem is the lack of methodology harmonization and time coordination. There are also language and cultural differences that affect the formulations of the questions and their responses (which have nevertheless been taken into account in the Eurobarometers). Therefore, although it is possible to aggregate responses to identical or similar questions regarding science knowledge, attitudes towards science, or both, the conclusions that can be drawn are very limited, as their scientific robustness cannot be established.

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Table 9.3 National and international surveys of public knowledge of science Country

Sponsors, survey titles and years administered

Argentina

Red Iberoamericana de Indicadores de Ciencia y Tecnología

Brazil

Brazilian National Research Foundation, Research Foundation of the State of Sao Paulo, Brazil

Bulgaria

Bulgarian Academy of Science, Institute of Sociology, Sofia

2003

1987, 2003, 2006, 2008, 2019 1992, 1996 Canada

Ministry of Science and Technology; Public Survey of Science Culture in Canada

China

China Association for Science and Technology, Chinese National Survey of Public Scientific Literacy; China Research Institute for Science Popularization

1989, 2013

1991, 1995, 1997, 2001, 2003, 2007, 2010, 2015, 2018, 2020 European Union

European Commission, Eurobarometers on Europeans, science and technology 1977, 1989, 1992, 2001, 2005, 2007, 2010, 2013, 2020

France

Centre for the Study of Political Life, SciencePo, Paris

Germany

Wissenschaft im Dialog

1972, 1982, 1989, 1994, 2000, 2007, 2011, 2020 2014, 2015, 2016, 2017, 2018, 2019 Tecknikradar 2018, 2020 India

National Council of Applied Economic Research

Japan

National Institute of Science and Technology Policy, Survey of Scientific Literacy

2004

1991, 2001, 2011 Korea

Korea Foundation for the Advancement of Science and Creativity, Survey of Public Attitudes Toward and Understanding of Science and Technology

Malaysia

Science and Technology Information Center, Survey of the Public’s Awareness of Science and Technology

New Zealand

Ministry of Science and Technology

Russia

National Research University Higher School of Economics, Monitoring Survey of Innovative Behaviour of the Population

2002, 2004, 2006, 2008, 2010, 2012, 2014, 2016, 2018

2000, 2014 1997

(continued)

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Table 9.3 (continued) Country

Sponsors, survey titles and years administered 1995–1999, 2001, 2003, 2006–2016, 2018

United Kingdom

Economic and Social Research Council; MORI (British public opinion research company); Office of Science and Technology, London 1986, 1988, 1996, 2000, 2004 (also included in Eurobarometer survey), 2011, 2014

United States

National Science Foundation, Public Attitudes Toward and Understanding of Science and Technology, General Social Survey (GSS), GSS Science and Technology Module 1979, 1983, 1985, 1988, 1990, 1992, 1995, 1997, 1999, 2006, 2008, 2010, 2012, 2014, 2016, 2018, 2020

International surveys Sponsors BBVA Foundation

International Study on Scientific Culture, 15 countries, including the United States

World Values Survey Association

World Values Survey, 50 + countries

2011

Since 1981 Wellcome Trust

Wellcome Trust Monitor, 140 + countries Since 2005

Source Adapted from Snow et al. (2016)

Nevertheless, there are three international studies to be mentioned here (in addition to the Eurobarometers, which also provide international surveys). The first survey was carried out in 2011 by the BBVA Foundation in 10 European countries and the United States using a set of 22 knowledge questions that are different from those traditionally asked.4 The second one, the Wellcome Global Monitor, has surveyed more than 140 countries and 140,000 people since 2005 on science and health issues. The third one, the World Values Survey, explores people’s values and beliefs, and how they change over time, but does not address science and technology. From this short overview of public opinion surveys on science and technology, it can be concluded that there is currently no attempt to approach science literacy in a genuinely international way. However, such an approach would allow us to:

4

The recent State of the Science Index survey carried out by 3 M covered 14 countries (Brazil, Canada, China, Germany, India, Japan, Mexico, Poland, Singapore, South Africa, South Korea, Spain, the UK, the US). The survey focused on the impact of science and did not address science culture. See State of Science Index: 2019 global findings, 3 M Company, https://multimedia.3m. com/mws/media/1665444O/3m-sosi-2019-global-findings.pdf.

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• enrich science culture concepts and approaches through international cooperation and cultural diversity • possibly agree on a joint working definition of science culture and its measurement • set up harmonized questionnaires and methodologies, make direct comparisons and build up time series • set up expert working groups to tackle science culture issues internationally • allow participating countries to share and access statistical data • possibly address other topics with an international perspective and through coordinated surveys.

9.7 A WISE Approach to Science Culture During a meeting held in Beijing on 2 November 2019, 12 scientists from 11 countries agreed to join forces in an informal alliance, called WISE (World Investigation of Science Culture), to define, measure, promote, support and connect science culture globally.5 Participants signed a memorandum of understanding in order to express a convergence of approaches and signal their intention to move forward. The signatories agreed, in particular: • to work towards an international approach to science culture, including its characterization, using a variety of methodologies in a coordinated way to allow comparative detailed analysis and monitoring • to exchange ideas and information about public perception surveys, results and methodologies and best practices to measure science culture through curating current efforts, developing an item bank and cultivating competencies for comparative analysis. The aim of this international network is to integrate the best international expertise through ongoing informal exchanges with non-European countries very active in this field, such as China, Russia, the United States, India and Korea. This should increase the efficiency and effectiveness of the participating research teams on science culture and enhance the global impact of their results by achieving a common understanding and agreeing on precise methodologies. More importantly, the benefits of such an approach would be to enrich science culture concepts and approaches through international cooperation and cultural diversity and allow participating countries to share experiences and access each other’s data. By providing robust scientific grounds for science culture and sharing data and good practices, WISE would enhance the global impact of the lessons and the messages provided to decision-makers about science culture. It would also reinforce and provide worldwide support for the work of scientists, science educators and science mediators, all of whom aim to promote and improve science culture. 5

WISE Alliance, http://www.wise-alliance.org/.

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References Bauer MW, Falade B (2014) Public understanding of science: survey research around the world. In: Bucchi M, Trench B (eds) Routledge handbook of public communication of science and technology, 2nd edn. Routledge, New York, pp 140–159 Bauer MW, Suerdem A (2016) Relating ‘science culture’ and innovation. In: OECD Blue Sky Forum on Science and Innovation Indicators 2016, 19–21 September 2016, Ghent, Belgium. http://epr ints.lse.ac.uk/67933/ Claessens M (2008) European trends in science communication. In: Cheng D, Claessens M, Gascoigne T, Metcalfe J, Schiele B, Shi S (eds) Communicating science in social contexts, Springer, New York, 27–38 Claessens M (2010) Allo la science? Analyse critique de la médiascience, Hermann, Paris, 2011 Claessens M (2018) Reality of theories and realism of practices. In: Le Marec J, Schiele B (eds) Cultures of science. Association Canadienne Française pour l’avancement des sciences, Quebec. https://www.acfas.ca/sites/default/files/documents_utiles/CULTURES-OF-SCIENCE.pdf European Commission (2005) Europeans, science and technology. European Commission, Brussels. https://ec.europa.eu/commfrontoffice/publicopinion/archives/ebs/ebs_224_report_en.pdf European Commission (2014) Public perceptions of science, research and innovation, European Commission, Brussels. https://ec.europa.eu/commfrontoffice/publicopinion/archives/ebs/ ebs_419_en.pdf Kahan DM, Peters E, Wittlin M, Slovic P, Larrimore Ouellette L, Braman D, Mandel G (2012) The polarizing impact of science literacy and numeracy on perceived climate change risks. Nature Climate Change 2(10):732–735 Le Marec J, Schiele B (2018) Cultures of science. Association Canadienne Française pour l’avancement des sciences, Quebec, https://www.acfas.ca/sites/default/files/documents_utiles/ CULTURES-OF-SCIENCE.pdf Lévy-Leblond J-M (2020) Le Tube à essais. Le Seuil, Paris NAS (Nigerian Academy of Science) (2020) The evolving science advisory landscape in Africa. University of Lagos, Lagos Potvin P, Hasni A (2014) Analysis of the decline in interest towards school science and technology from grades 5 through 11. J Sci Educ Technol 23:784–802 Roqueplo P (1974) Le partage du savoir. Science, culture, vulgarisation. Le Seuil, Paris Royal Society (2006) Survey of factors affecting science communication by scientists and engineers. The Royal Society, London Schiele B (2018) Participation and engagement. In: Le Marec J, Schiele B (2018) Cultures of science. Association Canadienne Française pour l’avancement des sciences, Quebec, 31–38 Shimizu K (2007) Japanese survey of the public understanding of science and technology: review of results, impact and recent secondary analysis. In: Communication at the international indicators of science and the public meeting organized by the royal society, 5–6 Nov 2007, London Shukla R, Bauer MW (2009) Construction and validation of ‘Science Culture Index’. Results from comparative analysis of engagement, knowledge and attitudes to science: India and Europe, NCAER working paper 100, National Council of Applied Economic Research. https://ideas. repec.org/p/nca/ncaerw/100.html Siarova H, Sternadel D, Sz˝onyi E (2019) Science and scientific literacy as an educational challenge. European Parliament, Policy Department for Structural and Cohesion Policies, Brussels. https://www.europarl.europa.eu/ RegData/etudes/STUD/2019/629188/IPOL_STU(2019)629188_EN.pdf Snow CE, Dibner KA (eds) (2016) Science literacy: concepts, contexts, and consequences. National Academies Press, USA. https://www.ncbi.nlm.nih.gov/books/NBK396088/ Zhihao Z (2018) Xi urges enhancing scientific literacy. China Daily, 18 September. http://www.chi nadaily.com.cn/a/201809/18/WS5ba040b7a31033b4f4656900_1.html

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Michel Claessens is a civil servant at the European Commission and a professor at the Université Libre de Bruxelles. He has a Ph.D. in physical chemistry and has been a researcher and science journalist. In the European Commission, he was in charge of the Science and Society programme and has been head of the communication unit, editor-in-chief of the research*eu magazine, coordinator of the Eurobarometer public opinion surveys on science and technology and spokesperson for the European Commissioner in charge of research. He currently works for the ITER project, the experimental and international nuclear fusion reactor that is under construction in Saint-Paullez-Durance near Marseille (France). He has published a dozen books, including ITER, the giant fusion reactor (Springer, 2020).

Part III

Public Attitudes

Chapter 10

Cultural Differences in Media Framing of AI Ahmet Suerdem and Serhat Akkilic

Abstract Media frames are especially important in understanding how the public makes sense of hi-tech artefacts that are either poorly or indirectly experienced in everyday life. Since the algorithms behind artificial intelligence (AI) are almost a ‘black box’ to most people, despite its pervasive presence in everyday life, AI keeps its fetish-like representation in the public imagination. Differing from certain science topics, such as space technologies, by having little direct presence in everyday life, AI presents an important case for understanding the cultural functions of hi-tech artefacts. Despite its importance, the way media framing of AI differs in different cultural contexts remains a gap in the literature. The limited number of studies analysing AI in the media rely mostly on content analysis of single cases, rather than cross-cultural comparisons. Media framing is closely related to context, and analysing media across countries can accentuate different media framings. Through automated text analysis of approximately 5000 news items, this study provides some evidence supporting the proposition that media in different countries represent AI in ways that reflect the cultural, societal and political context in which they are embedded. Keywords Artificial intelligence · Media frames · Topic modelling · Representation of emergent technologies · Automatized text analysis

10.1 Introduction The term ‘artificial intelligence’ (AI) has recently had much use in academic, business and media circles, in which there is increasing hype about its expected economic, social and existential effects (Fast and Horvitz 2017). That buzz not only attracts attention to the current tangible impacts of the technology, but also connotes a rich cultural imaginary. Representing it as a timeless novelty, the discourse on AI stirs the public imagination about how technology will reshape the organization of social life.

A. Suerdem (B) · S. Akkilic Istanbul Bilgi University, Istanbul, Turkey e-mail: [email protected] © China Science and Technology Press 2021 B. Schiele et al. (eds.), Science Cultures in a Diverse World: Knowing, Sharing, Caring, https://doi.org/10.1007/978-981-16-5379-7_10

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While AI technologies’ immediate impacts on people’s lives are directly experienced, public discourse about them usually semantically innovates the fictions of the future. However, the dominance of imagination in the hype about AI does not necessarily mean that it is futile or deceptive. On the contrary, imagination is ‘productive’ in generating insights about new ideas, new values and new ways of being-in-theworld. Hype can contribute to science specifically by encouraging reflection about science and technology (Robertson 2020). A specific version of science culture that has been dominant in the modern world depicts reality as still pictures of empirically experienced external facts. That version confuses the unreal with the absent. What produces the image of reality might be absent but might have been real in the past or could be real in the future. Imagination makes sense of the reality even in the absence of direct experience of it (Ricoeur 1991). It produces not models of taken-for-granted reality but models of emerging reality; that is, heuristic fictions for redefining reality. ‘Reality’ is a product of disciplined imagination, shaped and guided by conventions for selecting, organizing and testing experience against agreed-upon criteria. In that sense, establishing a hypothesis, a plan or a strategy, writing a poem or telling a story are all fictional, as they challenge our prejudices about what we accept as reality (Ricoeur 1991: 46). The principal function of such fiction is to challenge the dominant vision of reality by exploring alternative accounts of all possible worlds without having to experience them. Fiction both discovers and invents the reality. In modern societies, the media provide an important fictional repository for understanding how a society organizes its cultural imaginary for making sense of the possible impacts of new technologies. Science communication literature abounds with examples of how the media organize new and vaguely understood technoscientific concepts into heuristic storylines in a way that makes them more understandable by the non-expert public. Those storylines mediate between experts and non-experts by providing them with shared scripts for framing scientific issues such as global warming (Boykoff and Rajan 2007), bioenergy (Skjølsvold 2012), biotechnology (Marks et al. 2007) and nanotechnology (Lee et al. 2005). They help the audience to relate their everyday knowledge and experiences to the potential impacts of a given technology. Hence, analysing media stories will give us important clues for understanding the formation of public imagination about the potential risks and benefits of new technologies (Brossard and Shanahan 2003; Hornig 1990). Media stories do not only reflect the public imagination but also shape it. The stories are not produced in a vacuum but implicitly or explicitly state a ‘moral of the story’, implying a coda or a normative stance. The scripts for producing media stories operate through a complex web of professional roles, institutional constraints, political beliefs and broad cultural assumptions dominant in a society (Rachlin 1998; Chang et al. 1998). They are authored by a network of actors to persuade the public why certain forms of social order are imperative. The way in which science and technology issues are discussed in the public sphere is economically, culturally and politically grounded (Felt 2000: 4), and not necessarily directly related to the specific advances under discussion. For example, decisions regarding the patenting of living cells, genetic material of different kinds or even biological processes are usually interwoven with vested interests, fuelling political and ethical controversies. Each

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time a new technology is introduced, the controversies around it revive a discursive arena that mobilizes and responds to relevant actors. In that arena, while powerful actors try to shape public opinion according to their own agenda, they also attract resistance that challenges their arguments (Bauer 2015; Stilgoe 2015). The benefits of a new technology are usually exaggerated by those actors who have vested interests in it and are challenged by those who have concerns about its societal impacts. The media exploit those vibrant debates to attract the attention of the audience, often by creating hype about the controversies (Groboljsek and Franc 2012). While the hype might appear to be a futile repetition of older controversies, it is a functional necessity. It is a way to control uncertainty by organizing intellectual, social and financial resources serving a particular idea of the future (Van Lente et al. 2013; Borup et al. 2006). Hence, a critical study of the discursive hype about AI is a crucial element in understanding alternative visions of how emerging technologies will shape the future fabric of a given society.

10.2 Background While the way scientific and technological issues relate to societal and political contexts is a well-covered area, the study of public opinion about AI is at an early stage (Zhang and Dafoe 2019). The origin of the term goes back to the 1950s, when several researchers gathered to clarify and develop ideas about ‘thinking machines’ that might overcome cognitive deficiencies in human decision-making (McCarthy et al. 2006). For a long time, this ‘electronic brain’ metaphor remained a fanciful concept perceived either in the domain of complex expert knowledge or in science fiction. The few news items about AI represented it as a surrogate for human intelligence that would produce flawless solutions in all domains of social life or as a malign entity with an intention to subordinate humans. However, with the pervasive penetration of digital technologies into everyday life, media coverage of AI has begun to increase sharply, and its nature has changed. The overall framing of the stories has changed from science fiction to governance concerns about AI’s future impacts (Elish and Boyd 2018). That resulted in a diversification of the tone of the discourse according to different domains of social life. According to a study by Fast and Horvitz (2017), while representations of AI in the US media were optimistic in the contexts of health care and education, they were more pessimistic about possible surveillance, alienation and a loss of human autonomy. Brennen and Nielsen (2018) have shown that the AI discourse in the British media has been far from being value free and has implicitly or explicitly reflected vested interests or ideological positions. The general tone of the UK media has been more biased towards private-sector interests and has narrowly framed AI as ‘a relevant and competent solution to a range of public problems’ (Brennen and Nielsen 2018: 1). Brennen and Nielsen also found that the discourse was highly politicized: while rightleaning media highlighted business and national security issues, left-leaning media emphasized concerns about ethics, discrimination, algorithmic bias and privacy.

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Suerdem et al. (2018) have used neural network language models for detecting semantic regularities to show how the words embedded in a lexicon representing the language of AI change in the word vector space over the years. They found that the terms appearing in the same context as AI have changed from philosophical– speculative terms, such as ‘killer robots’ and ‘transhumanism’ into terms pointing to tangible technologies, such as ‘internet of things’, ‘machine learning’ and ‘big data analytics’. They also discovered that the language of AI began to stabilize after 2016, reflecting a more positive tone and business applications. Despite the positive and business-oriented framing of AI in the media, opinion polls show that the public typically expresses conditional support for AI, expecting it to be more carefully governed (European Commission 2017; Zhang and Dafoe 2019). The few studies on this issue that have been completed have been limited to single countries; cross-cultural studies into how the publics relate AI to society remain a gap in the literature. Our study aims to address that gap by investigating the media framing of AI in different countries and discovering patterns, nuances, similarities or overlaps in those representations.

10.3 Operationalizing Media Framing There is little agreement on the operational definition of media frames and methods for observing them. There has even been debate about whether an adequate systematization of frame analysis would be feasible (Gamson 1975: 605). A common approach for detecting frames is through a qualitative–inductive process in which the frames emerge from the textual material (see, for example, McCaffrey and Keys 2000; Triandafyllidou 2002). However, that approach has been criticized because of its subjective nature and difficulties in replicating and generalizing the results (Tankard 2001; Hertog and McLeod 2001). To ensure objective measurement and rigorous hypothesis testing, some researchers have proposed the deductive preparation of concise, defined content analysis coding frames tested for reliability and validity (Tankard et al. 1991; Maher 1994; Cappella and Jamieson 1997). However, the abstractness and complexity of the concept makes it hard to develop categories with well-defined boundaries for identifying and annotating relevant text segments (Matthes and Kohring 2008: 258). Because frames involve both individual cognitive and cultural elements of meaning generation, it is harder to treat them as content units with definite denotations (see Livingstone 2013). For frame analysis, content units only make sense within the context in which the words are embedded in different configurations each time. It is not possible to treat textual units as information containers transmitting mutually exclusive and exhaustive events, since texts operate within an encoded symbol system requiring semiotic decoding. Although this premise does not mean that frame analysis is not interested in the content, we cannot analyse frames from a purely content-free structuralist semiotic view either. Frames operate through bringing the form and content together according to certain

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systematic rules motivated by cultural codes. It is not possible to understand the content without analysing the form, which gives us clues about how a code system configures the selection of signs for articulating the message. The content is not in the message per se, but instigates cognitive heuristics helping the receiver to decode the message (Van Dijk 1988). Understanding how this decoding process occurs requires methods that can handle the complexity in how cognitive and cultural elements of sense-making come together. Methods gathered under the umbrella term ‘conceptual mapping’ aim to address that complexity by observing how individual cognitive and cultural mentality forms interact with each other. Those methods are based on the theory that meaning does not occur as the processing of the information in isolated messages, but that people perceive, conceptualize and make sense of the messages by framing them according to a mental model (Edwards and Mercer 1986: 642; Stubbs 1983; Axelrod 1976; Bonham et al. 1976). From a multi-method, multi-level perspective, conceptual mapping aims at eliciting the relationships between a set of concepts and visually presenting those relationships to investigate how people in different contexts organize their ideas to conceptualize an issue (Axelrod 1976). The analysis starts with inductive coding of qualitative material such as interviews, focus groups, policy proposals or other documents (Axelrod 1976; Young and Schafer 1998; Hodgkinson and Clarkson 2005). The coded material is then mapped into a visual form using either qualitative thematic analysis methods or multivariate statistical techniques. Those visual forms are then used to study the belief structures of individuals, groups or organizations. By mixing the strengths of automatic and manual coding-based content-analysis techniques and integrating them with the use of multivariate statistical methods, conceptual mapping offers great potential for representing how the sense-making process is framed. Its ability to represent diversity and dimensionality in that process through the analysis of the entire corpus can help to reveal subgroup differences in mental models (Trochim 2006). Because the conceptual mapping method is based on the analysis of discourse, it is possible to extract abstract and complex ideational forms that are otherwise not observable using classical data collection methods, such as surveys. That property makes it an impeccable instrument for understanding the complex relationship between mental and cultural structures. Language mediates between thought and action, and our conceptual categories shape how we perceive the world and, in turn, are shaped by the environmental context we live in (Vygotsky 1962). Through the analysis of discourse, we can have access to intangible and complex ideational forms bringing together both individual and social aspects of human thinking. This gives us an opportunity to observe and represent how ideas are framed within different contexts. Hence, conceptual mapping converges with media framing, as they are both concerned with how abstract ideational frames are linguistically embodied in everyday life. Although there is no agreement on the definition of media frames, the way language shapes and is shaped by the environment in different contexts is an underlying aspect of the existing definitions. That makes conceptual mapping an ideal candidate method for operationalizing and observing media frames.

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Framing research has already benefited from methods inspired by conceptual mapping that bring computer-assisted text analysis tools together with multivariate classificatory techniques (such as clustering, multidimensional scaling/network analysis and correspondence analysis). For example, one of the pioneering efforts in ‘frame mapping’ (Miller 1997) built upon Entman’s (1993: 53) premises that frames can be observed and discovered by the presence or absence of certain keywords. Regularities in occurrence and co-occurrences can be the manifestations of thematically reinforcing clusters that represent how everyday events are discursively organized. If we assume that an author has an internal conceptual map representing the relationship between different concepts, then he or she would frame the words within the constraint that the elements of the map appear surrounded by similar sets of words. (Lowe 2004: 12, fn. 12). Frame mapping operationalizes those axioms according to the vector space model, assuming that detecting co-occurrences of words in similar contexts can help us to represent documents as word occurrences. The resulting similarity matrices can then be used to reduce the dimensionality of the semantic space through multivariate statistical techniques for projecting the terms, documents, or both, into an interpretable visual map. The popular multivariate methods for automatically extracting frame maps are usually built into packaged text-analysis software (Koella 2001; Miller 1997; Miller and Riechert 2001; Koenig 2004a, 2004b). Such automatic procedures can cause some problems. To reduce the burden of computation, the software automatically selects the keywords with the help of built-in stop word lists, by automatically limiting the words to a minimum–maximum range, or by both methods. However, according to the operational definition, keywords are the building blocks of the frames (Entman 1993: 53; Triandafyllidou and Fotiou 1998; Miller and Riechert 2001). Getting meaningful patterns from the data depends upon the selection of the keywords according to their theoretical relevance to the intended analysis. For that reason, the common route among frame researchers is to identify the relevant keywords through hermeneutic reading. However, hermeneutic methods are designed for an in-depth analysis of a small volume of texts and cannot handle the ‘big data’ produced by today’s online media. Although that can be managed by a meticulous purposive sampling design, hermeneutic methods require being immersed in the textual material. To avoid that extra or in some cases impractical burden, a common shortcut is either ad hoc purposive selection of the keywords or leaving it to automatic selection. Making arbitrary decisions for qualitative analysis or naively using default parameters for automatic text analysis can misguide the further analytical process. Drawing the external boundaries of the vocabulary of a corpus and delineating internal boundaries demarcating different categories within it is the hardest part of frame mapping. Although using predefined content-analysis dictionaries seems to be a feasible solution to that problem, selecting dictionary categories and keywords in an ad hoc manner can be problematic (Shapiro and Markoff 1997). Advances in computational linguistics and access to libraries of functions and methods that allow us to run complex algorithms are now providing accessible tools for addressing these problems. Supervised machine-learning algorithms that can automatically extract word vectors that demarcate one conceptual domain from

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another can help to automatically select the keywords classifying texts into categories. However, their success is largely dependent upon a training set assembled according to some ‘ground truth’, such as texts assumed to truly represent the issue at hand. The construction of such sets requires the leveraging of high-level domain knowledge and issue-specific knowledge from experts, annotating the texts for both positive and negative examples, and contextual metadata linked to the text. Noisy or incorrect annotation will produce biased and ineffective models. This requires extra effort in reaching a stable set of results compared to the traditional process of defining content-analysis dictionaries based on theoretical considerations. Computational linguistics experts usually lack social science domain expertise and resort to spontaneously tagged documents, such as the Reuters corpora, for the training sets. On the other hand, social scientists usually lack the coding expertise needed to run these algorithms. Discursive domains of interest to social science researchers require much more complex annotation of the texts than the news section tags. That makes using supervised learning for the social sciences elusive or costly for both social scientists and computational linguistics experts. Unsupervised learning algorithms can address these difficulties because they do not require training sets with explicit instructions. A corpus of texts collected by using a few keywords broadly defining the domain of interest would be enough. The algorithms then attempt to automatically find structure in the corpus by extracting useful keywords and analysing potential structures without any a priori definition. Topic modelling is a particularly interesting unsupervised learning method for extracting keywords from and elucidating the structure of large volumes of untagged text. In this context, a topic can be defined as a set of keywords tending to appear in similar contexts within a corpus, and each document is a combination of a fixed number of topics in different proportions (Steyvers and Griffiths 2007), overcoming the disadvantages of traditional multivariate methods that directly use bags of words (Madsen et al. 2005). Topic models can help us to discover the internal categories of a domain vocabulary and keywords belonging to them and discard the words not belonging to the domain. This brings an obvious advantage over other automatic keyword selection techniques. As topic modelling allows more user control through parameter tweaking and user-controlled iterative processes for vocabulary crafting, it can also help in the interpretive identification of the keywords and hermeneutically uncover frames. Through iterative improvement in its qualitative and quantitative stages, text analysis is becoming popular under the heading of ‘mixed methods’ (Bergman 2011). As suggested above, selecting the keywords represented as topics reflecting the contextual information through a multi-method perspective can help us to reduce the complexity of human interpretation with the help of computational linguistics tools. Topic modelling can therefore contribute to the difficult task of operationalizing frames when combined with qualitative methods. Brier et al. (2016) suggest that topic modelling and multivariate statistical analysis can be complementary for addressing the complexities in automated text analysis.

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10.4 Method 10.4.1 Corpus Corpus linguists commonly adhere to stratified random sampling for constructing a representative corpus. That process involves the identification of the external and internal criteria for delineating the contextual strata of the corpus (Biber 1993: 244). External criteria can be various non-textual context strata, such as the characteristics of a broadcaster and an audience identified according to the purpose of the research. For this study, those strata were identified as the English editions of major newspapers in selected countries. The assumption behind the choice of that criterion was that those outlets would reflect the general view in the country to the international audience in a way that would enable us to control for intra-country differences. Countries were selected to reflect the diversity of cultural contexts. Texts were collected by means of a crawler, which automatically searched Bing News for given keywords (‘AI’ and ‘artificial intelligence’) and newspaper domain URLs. The Bing algorithm retrieves 1000 news items most relevant to the keyword. Although the texts are not randomly selected from a population, the criteria used by the algorithm (D’Onfro 2018) can be considered as a valid selection procedure with certain limitations. In addition to usual noise, such as URLs, html tag remnants and non-ascii codes, words that are quite frequent but contain non-informative content, such as the names of newspapers, press agencies and reporters, were interactively cleaned. Then, hypernyms and synonyms of commonly occurring entities, such as presidents’ names and geolocations, were replaced by means of a dictionary. The detection of syntactically and semantically similar words as topics can create some noise that hinders the correct assignment of a coherent model. We managed that by detecting such topics and aggregating them with the hypernyms through iterative topic modelling. Finally, the corpus was annotated by the Spacy natural language processing library. Documents parsed by Spacy can be used for extracting key entities, such as n-grams, named entities, subject–verb–object triples, and many more. This is especially important for this research, since the quality of frame analysis is dependent on keyword selection. See Table 10.1 for the final state of the corpus (n = 5547).

10.4.2 Keyword Selection Keyword selection helps us to simplify the text-mining models to make them interpretable, to reduce training times, and to reduce the dimensionality and enhance generalization by decreasing overfitting. For that purpose, we selected a keyword set containing only nouns, proper nouns and adjectives, as those were found to be most effective for text categorization purposes (Chua 2008). Then we added bigrams and trigrams to the vocabulary. Since an active keyword selection is essential for frame analysis, the first 1000 most frequent words were browsed to detect and clean

10 Cultural Differences in Media Framing of AI Table 10.1 Source counts

193

Source

Country/region

Count

China Daily

China

884

Times

UK

751

Punch

Nigeria

573

France 24

France

532

Japan Times

Japan

502

New York Times

US

462

Deutsche Welle

Germany

405

Sputnik

Russia

404

Sabah

Turkey

329

Mail & Guardian

South Africa

269

Al-Jazeera

Qatar

239

Hurriyet

Turkey

103

Mercosur

Latin America

94

words signifying potential noise, such as newspapers’ and reporters’ names, or by adding further categories to synonym dictionaries. The final vocabulary was selected by trimming the words that did not occur in more than 90% of the documents or in fewer than 20 documents. That reduced the vocabulary size from 58,961 to 4433 key terms.

10.4.3 Model Selection and Evaluation Topic modelling algorithms are attractive because they bring structure to otherwise unstructured text data, but topics are not guaranteed to be easily interpretable and coherent (Chang et al. 2009). Deciding on the best model and getting good-quality topics is an iterative exercise requiring multiple interpretative steps dependent upon many criteria (Brier et al. 2016). Some decision tools are available, but selecting the model and number of topics is a craft rather than a technique. This study used two criteria for selecting the best model: • The objective criterion builds upon the coherence value (CV) scores produced by different algorithms. In topic modelling, coherence is a measure of whether the words in a topic tend to co-occur together (Newman et al. 2010). • The subjective criterion depends on the interpretability of the set of keywords making a topic when they are grounded in the larger context. For our case, after experimenting with various models, LDA Mallet largely outperformed others for both criteria. To decide on the final model, the CV scores for different numbers of topics produced by Mallet were calculated. CV improved together with the number of topics, but that improvement was not linear. After

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70 topics, incremental improvement in coherence slowed down and it remained almost constant at around 0.600.

10.4.4 Exploring the Model Topics Although systematic, these procedures still do not guarantee the best performing model. Performance is dependent upon several factors, such as the number of documents, document length, the number of topics, sparsity, the coherence of topics and, most importantly, the interpretability of the topics. Topics occurring in a very few documents, with extremely high or extremely low coherence, might need to be removed or merged with other topics (extremely high coherence might indicate synonyms). Topic modelling provides us only with the topic words and weights, which can give us an intuition about but not the meaning of the topic. Some topics might be artefacts resulting from the co-occurrence of words denoting clichés, such as ‘Subscribe to our digital edition to read more content.’ Reading the documents relevant to each topic is required not only for sensible labelling of the topics but also for identifying such artefacts. To ensure correct interpretation of the topics, we examined the headlines of the news articles dominated by each topic, together with the topic keywords. If that did not give a straightforward understanding of the topic, we then did a deep reading of the documents. Most of the 70 automatically discovered topics were either hypernyms or irrelevant to the discursive domain of AI. After removing and merging topics, the model was stabilized at 28 topics. The final model was extracted through guided LDA (Jagarlamudi et al. 2012) by providing the sets of seed words from each topic. Guided LDA is a semisupervised approach that uses those seeds to both improve topic–word distributions (by biasing topics to produce appropriate seed words) and to improve document– topic distributions (by biasing documents to select topics related to the seed words they contain). With further tweaking, 23 highly interpretable topics with coherence scores within a range of 0.462 (Space) to 0.767 (Health) remained. The average model coherence score was 0.601 (see Table 10.2 for the final list of the topics that were selected according to this procedure). Finally, to check whether we had well-segregated topics, we needed to visualize the clusters of documents in a reduced dimensional (2D or 3D) space. The t-SNE (t-distributed stochastic neighbour embedding) algorithm is particularly well suited for the visualization of high-dimensional datasets. The result of the analysis shows that topics were distributed in well-segregated clusters and positioned meaningfully in the two-dimensional space (see Fig. 10.2).

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Table 10.2 Topics, keywords and excerpts Topic (coherence)

Keywords

Excerpts

1. Big Tech (0.602)

Google company Amazon technology Microsoft research Silicon_Valley software project technology_giant

Google parent Alphabet on Monday reported a sharp drop in profits over the past quarter as it ramped up spending for a wide array of new gadgets and services

2. Space (0.582)

Space drone satellite Earth mission rocket project scientist system Mars

A ball shaped artificial intelligence robot nicknamed the ‘flying brain’ because it is trained to follow and interact with a German astronaut, blasted off June toward the International Space Station aboard SpaceX’s Dragon cargo ship

3. Surveillance (0.522)

Right law technology police facial_recognition authority report system surveillance protest

As India prepares to install a nationwide facial recognition system in an effort to catch criminals and find missing children, human rights and technology experts warn of the risks to privacy from increased surveillance

4. Chatbots (0.658)

Chatbot voice user Good grief: chatbots will let you talk to dead language bot app relatives conversation social_media Google device

5. Cybersecurity (0.492)

Technology company bank digital big_datum solution organization innovation security process

The Chartered Institute of Bankers of Nigeria has urged chief executive officers to get the essential cybersecurity knowledge that would ensure companies take appropriate actions to secure valuable information assets

6. Trade wars (0.653)

Trump economy economic trade official deal agreement cooperation foreign relation

Mnuchin said Monday that enforcement of any agreement, protection of USA intellectual property and an end to the forced joint venture policies as a condition of access to the China market were ‘three of the most important issues on the agenda’

7. Smart devices (0.633)

Huawei company device technology smartphone phone camera product Samsung chip

Huawei launches powerful AI processor Ascend 910

8. Misinformation (0.532)

Social_media company content user video platform medium account report news

Facebook said improved technology using artificial intelligence had helped it act on millions of posts containing graphic violence, nearly three times more than it had in the last quarter of 2017. Improved IT also helped Facebook take action against millions of posts containing terrorist propaganda, a percent increase (continued)

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Table 10.2 (continued) Topic (coherence)

Keywords

Excerpts

9. Education (0.677)

Education student university skill program knowledge school University research teacher

A delegation from the Southern University of Science and Technology of China (SUSTech) met with academics from a UK university for a week-long visit to discuss collaborating on research projects into artificial intelligence, among others

10. Automation (0.492)

Job percent work technology worker company economy report future automation

The public is broadly fearful that automation will lead to significant job losses, with many populations skeptical the technologies will boost economic efficiency, according to a survey of countries released Thursday

11. AV (0.677)

Car vehicle company technology driver Toyota autonomous_driving Tesla system future

Electric car maker Tesla has confirmed its ‘Autopilot’ feature was engaged during a fatal crash last week, a development set to exacerbate concerns over the safety of futuristic vehicles. The latest fatal Tesla crash came the same week a collision involving an autonomous Uber vehicle in Arizona killed a pedestrian and caused that company to temporarily halt its self-driving car program

12. Platforms (0.605)

Service big_datum company user app platform consumer technology online customer

If you share Netflix password with others, an AI could hunt you down. While the percent of people one can share their Netflix account with depends on their personal plan, casual credentials sharing has become too expensive for the streaming service to ignore, a company that can crack down on cheaters, has suggested

13. Robotics (0.484)

Robot robotic company technology machine able Sophia future head hand

The robot-dog weighs the same as a female labrador. Sensors dotted across its body feedback to artificial intelligence, helping it to navigate and perform tasks. It can also be controlled by its owner. The robot is all-electric, without hydraulics, and runs for about an hour and a half on one charge

14. Futurism (0.553)

Technology machine future scientist computer humanity robot intelligence Elon_Musk mind

We have entered a new technology era, it points out, the consequences of which could have grave implications. You don’t need to be HG Wells to see that synthetic biology, nanotechnology and, shudder, artificial intelligence could have unforeseen outcomes

15. Business (0.597)

Company percent market investment technology startup investor growth sale product

While SoftBank still holds an equity stake in Nvidia, it has constructed a so-called collar trade of about $1 billion., the people said, which allows investors … (continued)

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Table 10.2 (continued) Topic (coherence)

Keywords

Excerpts

16. Tech & development (0.594)

Technology development company innovation industry sector area application field investment

Political advisors discuss accelerating industrial Internet construction

17. Health (0.765)

Patient health doctor medical COVID hospital pandemic healthcare system disease

Deepmind: Computer could flag up kidney injury to doctors

18. Farming (0.638)

Food water farmer energy project area percent climate_change agriculture farm

The project, titled Holmene (the Islets), is the brainchild of Urban Power architecture and planning, who plan to reshape the Danish coastline with 3 million square meters of mixed-purposed islands used for commercial spaces, fossil-free energy production, flood barrier relief, and a massive public nature zone

19. Deep learning (0.556)

Big_datum system technology algorithm computer machine researcher research software program

Imagine that you give the machine a piece of input, a video clip, for example, and ask it to predict what happens next, scientist LeCun said in his office at NY University, decorated with stills from the film 2001: A Space Odyssey

20. Art & culture (0.569)

Work art film music artist story project character history image

Artificial intelligence is being used to trace the cultural history of Russia’s Bolshoi Theater. Thousands of volunteers have helped to digitize historic posters, programs and photographs from past productions going back further than the Bolshevik Revolution

21. Defence (0.681)

Military weapon system defense war attack force report drone missile

Artificial intelligence had already taken over defense targeting decisions on Aegis missile warships of the US Navy, Deputy Defense Secretary Bob Work told a conference at the Atlantic Council

22. Research (0.633)

Scientist research researcher brain University study cell method team science

In a first, US researchers have used artificial intelligence to identify a powerful new antibiotic capable of killing several drug-resistant bacteria

23. Games (0.619)

Game football player team Sony computer AlphaGo chess program winner

Visitors watch robots competing in boxing at the 20th National Robot and Artificial Intelligence football in Shunde District of Foshan, south China’s Guangdong Province, Oct. 24, 2018. The 20th National Robot and Artificial Intelligence football kicked off here on Wednesday. More teams from China colleges will take part in competitions under categories

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10.4.5 Mapping We then calculated the document–topic matrix, which represents the weight of each topic in each document. According to our operational definition, frames can be derived from the patterns in the co-occurrence of certain concepts within the same context. In our case, topics represented the conceptual domains making up the discursive space of AI in the news. Hence, the co-occurrence of the topics in the same news articles could be used as a proxy for the contextual similarities of each topic to others. We operationalized this as the topic-by-topic correlation matrix. This similarity matrix was used for mapping how the topics were framed in the discursive space of AI. Multidimensional scaling (MDS) is a set of statistical techniques used for the transformation of observed similarities (the correlation matrix, in our case) by estimating distances among a group of real or mental objects to project the patterns between them upon a low-dimensional space (Kruskal and Wish 1978: 23– 30). We used a special version of MDS-INDSCAL—which considered the individual country differences for frame mapping. While that technique considers a common space structure for all countries for the MDS, it assumes that the weights given to each dimension by each of those countries can vary. We used this technique to jointly map the topics and countries. Contrary to commonly (mis)used methods such as correspondence analysis, which maps in the form of joint plots of the incommensurate row and column points (Brier et al. 2016), INDSCAL does not map rows and columns together but presents the subject weighing of dimensions as a separate plot. Since the output produces a configuration for individual weights reflecting the salience of each dimension for the subjects, INDSCAL is an ideal tool for mapping individual differences in ‘structured conceptualizations’, such as media framing.

10.5 Findings Table 10.2 shows topic keywords, example extracts and coherence values for each topic (labelled by us after an interpretive reading of the documents dominated by the topic, as described above). Figure 10.1 shows the number of documents in which the topic was dominant. While ‘Tech & Development’ was dominant in most of the documents, ‘Space’ was the least frequent. Figure 10.2 shows the clusters of documents in a 2D space. There were relatively few overlaps in the clusters, as can be observed from the colours, so the topics were quite well segregated. To visualize the topic dominance by country, a heatmap was produced (Fig. 10.3). According to the heatmap, ‘Research’, ‘Defense’ and ‘Space’ topics were salient in the Russian media. That makes sense, since most AI-related research is publicly funded and targeted at the public sector, transport, defence and security).1 The 1

Artificial intelligence (AI) in Russia, Netherlands Enterprise Agency, https://www.rvo.nl/sites/def ault/files/2019/07/Artificial-intelligence-in-Russia.pdf.

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700 600 500 400 300 200 100 0

Fig. 10.1 Number of news items, according to topic dominance

Fig. 10.2 Document clusters, by topics

application of AI in the military is a strategic priority and traditionally strong in Russia.

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Fig. 10.3 Topics, by country

‘Tech and Development’ and ‘Health’ were dominant topics for China. That also makes sense, because, according to the China’s New Generation Artificial Intelligence Development Plan,2 making AI ‘the main driving force for China’s industrial upgrading and economic transformation’ is the top priority. China aims to be worldleading in the applications of AI in dealing with chronic and emerging challenges, such as improving the healthcare system. It is leading research and innovation to develop an integrated data platform for research into precision medicine (Zhang et al. 2018). In the US, the dominance of ‘Big tech’ and ‘Deep learning’ topics reflects the fact that the country is the home of big-tech companies such as Google, Apple and Microsoft, which are specialized in developing new technologies for learning from data. The news articles representing those topics highlighted issues such as removing 2

AI policy—China, Future of Life Institute, https://futureoflife.org/ai-policy-china/.

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barriers to innovation and discovery, prioritizing long-term R&D, building the AI workforce and fostering public trust. The implicit message from those articles is that AI requires long-term R&D and investment, which can only be afforded by the big-tech companies; therefore, their intellectual property needs to be protected in the American national interest. European countries such as France, Germany and the UK presented a critical view about the cultural, political and ethical challenges of AI. In particular, the media in those countries are concerned about the dominance of big-tech companies and the everyday problems that might arise from new AI technologies (France: ‘Big tech’, ‘Autonomous vehicles’ and ‘Smart devices’); robotics (Germany); and future challenges that AI might bring to humanity (UK). Japanese media highlighted the opportunities offered by AI-enabled job automation and start-ups for addressing the rapid decline in the country’s labour force and the limited influx of immigrants. ‘Cybersecurity’ was the dominant topic in the Nigerian media, which makes sense when we consider that Nigeria is one of the world’s most vulnerable countries to cyber attacks.3 ‘Farming’, ‘Education’, ‘Surveillance’ and ‘Applications’ were dominant topics in South America, South Africa, Qatar and Turkey, respectively. Another topic that concerned several developing countries was the ‘trade wars’ between the US and China, especially in the field of digital technologies. Global uncertainty because of that conflict has made emergent markets prohibitive for investment. We can group the countries into two clusters according to the similarities of topics discussed in their media. While the media in South America, Nigeria, China and South Africa media are more inclined to discuss more techno-industrial-focused topics, such as ‘Security and Development’, the US, the UK, Japan, Qatar, Turkey and Germany tended to focus more on sociocultural issues, such as ‘Games, ‘Futurism’ and ‘Art & Culture’. Russia was an outlier. Finally, when we check the patterns in the INDSCAL topic map (Fig. 10.4a), we can observe a clustering of economy-related topics such as the ‘Tech and Development’, ‘AV’, ‘Automation’, ‘Start-ups’ and ‘Trade wars’ group on the left-hand side of the first dimension. On the right-hand side, R&D-related topics such as ‘Research’, ‘Deep learning’, ‘Health’ and ‘Robotics’ are clustered. The upper end of the second dimension groups anticipated AI topics such as ‘Futurism’, ‘Defence’ and ‘Space’, while applied AI topics such as ‘Smart devices’, ‘Apps’, ‘Bigtech’, ‘Misinformation’ and ‘Cybersecurity’ are grouped on the lower end. A word of caution: the naming of these dimensions is subjective, so their interpretation needs to be grounded in the literature, which requires more theoretical and hermeneutical work. Check Table 10.1 for a deeper understanding of the topics. When we checked the configuration weights for the countries (Fig. 10.4b), we could see that the salience of each dimension was different for each country, implying differences in the ‘structural conceptualization’ or media framing of AI. China, Japan, Russia, Latin, and South Africa weighted the first dimension, meaning that AI debates 3

Nigeria’s cybersecurity problem, StearsBusiness, 20 March 2020, https://www.stearsng.com/art icle/nigerias-cybersecurity-problem.

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Fig. 10.4 a INDSCAL mapping of the topic space. b INDSCAL mapping of the country space

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in their media are mostly framed by the economy versus research dimension. This resonates with the heatmap findings, as that dimension seems to manifest the ‘development’ face of AI. On the other hand, Nigeria, Qatar, Turkey, the US and France weighted the second dimension, implying that the media discourse in those countries is framed by the anticipated AI versus applied AI dimension. This dimension seems to emphasize the concrete versus abstract face of AI. Media in the UK and Germany gave equal weights to both dimensions.

10.6 Conclusion The findings of this study show that media in different countries represent AI in a way that reflects the cultural, societal and political context in which they are embedded. Each country values different aspects of AI, as was reflected in the salience of the topics. Moreover, while the framing of the topics can be represented in a joint space, each country weights different dimensions. These findings have important implications, as they show that AI is not only a technological fact but also a cultural artefact embodying different concerns in different societies. While the media in some countries look at AI from a development and economic growth perspective, others look from the angle of concrete versus abstract problems and prospects. Moreover, media in each country prioritize different topics embedded in their socio-cultural, economic and political contexts. This study also shows the potential of text-mining tools for analysing and summarizing large amounts of textual data. That has important implications for science communication. When used together with interpretive analysis, automated, real-time text analysis can help to get a handle on a huge volume of textual media documents for a broad range of uses. That can maximize the efficiency of science journalists and reduce their burden of repetitive tasks, helping them to focus more on deeper analyses of specific issues. Moreover, real-time automatic monitoring of the news can help science communicators to draw insights without having to sort through millions of media and social media documents and survey responses. However, the potential of automated text analysis, as for other AI technologies, needs to be cheered cautiously. The findings of this research show that the impacts of emerging technologies make sense only contextually. If we do not understand what those technologies mean in local contexts, we cannot develop more reflective thinking about the possible forms of governance for a more democratic technology–human interaction. Science communicators should assume responsibility in this respect, as they are among the actors who play important roles in the discursive shaping of public opinion. According to Marcus and Davis (2019), our current understanding of AI as a technological support system is narrow. That understanding limits AI to learning from patterns in past data and accomplishing repetitive tasks, such as using a digital assistant to book a table in a restaurant. We need a broader view of intelligence if we want a safer, smarter or more reliable future.

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The problem here is the possibility of endowing machines with a deeper understanding of the world. However, that would be an impossible quest if we define understanding in the hermeneutic verstehen sense, as the ‘interpretive or participatory’ examination of social phenomena. We cannot interpret action based on analyses of the behavioural patterns in past data, but by understanding the meanings attributed by the actors to it. Meaning is a discursive construction that can be understood only by analysing the contexts giving rise to the specific challenges deliberated during that construction. How AI will shape the future cannot be left to the technologies alone; a broader intelligence for a safer society requires human understanding and intervention for governance. The way we establish AI today will affect the construction and management of our digital infrastructure and the way we design and distribute AI systems (Brundage et al. 2018). That will not only shape the technological infrastructure but will also shape the organization and formation of the social fabric. Sociotechnical imaginary in different contexts is informed by both fictions about how technology will shape our future and by our direct experiences with more familiar technologies, which form our attitudes (Lee et al. 2005). Technology forms differently in different national contexts; national cultures are not just about responses to or acceptance of technology, but fundamentally shape what that technology becomes in the real world.

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Madsen RE, Kauchak D, Elkan C (2005) Modeling word burstiness using the Dirichlet distribution. In: Proceedings of the 22nd international conference on machine learning. Association for Computing Machinery, New York, pp 545–552 Maher M (1994) How news media frame the population–environment connection. Paper delivered to the Media and the Environment Conference, Reno, Nevada. Association for Education in Journalism and Mass Communication, pp 13–14 Marcus G, Davis E (2019) Rebooting AI: building artificial intelligence we can trust. Pantheon Marks LA, Kalaitzandonakes N, Wilkins L, Zakharova L (2007) Mass media framing of biotechnology news. Public Underst Sci 16(2):183–203 Matthes J, Kohring M (2008) The content analysis of media frames: toward improving reliability and validity. J Commun 58(2):258–279 McCaffrey D, Keys J (2000) Competitive framing processes in the abortion debate: polarizationvilification, frame saving, and frame debunking. Sociol Q 41(1):41–61 McCarthy J, Minsky ML, Rochester N, Shannon CE (2006) A proposal for the Dartmouth summer research project on artificial intelligence, August 31, 1955. AI Kayesmagazine 27(4):12–12 Miller MM (1997) Frame mapping and analysis of news coverage of contentious issues. Soc Sci Comput Rev 15(4):367–378 Miller M, Riechert BP (2001) Frame mapping: a quantitative method for investigating issues in the public sphere. Prog Commun Sci 61–76 Newman D, Lau J, Grieser K, Baldwin T (2010) Automatic evaluation of topic coherence. In: Human language technologies: the 2010 annual conference of the North American chapter of the association for computational linguistics, pp 100–108 Rachlin A (1998) News as hegemonic reality: American political culture and the framing of news accounts. Praeger, New York Ricoeur P (1991) A Ricoeur reader in reflection and imagination. In: Valdes MJ (ed). University of Toronto Press Roberson TM (2020) Can hype be a force for good? Inviting unexpected engagement with science and technology futures. Public Underst Sci 29(5):544–552. https://doi.org/10.1177/096366252 0923109 Shapiro G, Markoff J (1997) A matter of definition. In: Text analysis for the social sciences: methods for drawing statistical inferences from texts and transcripts, vol 1, pp 9–34 Skjølsvold TM (2012) Curb your enthusiasm: on media communication of bioenergy and the role of the news media in technology diffusion. Environ Commun J Nat Cult 6(4):512–531 Steyvers M, Griffiths T (2007) Probabilistic topic models. In: Handbook of latent semantic analysis, vol 427(7), pp 424–440 Stilgoe J (2015) Experiment earth: responsible innovation in geoengineering. Routledge, London Stubbs M (1983) Discourse analysis: the sociolinguistic analysis of natural language, vol 4. University of Chicago Press Suerdem A, Yildiz T, Yildrim S (2018) Detection of change in the sense of AI in popular discourse. In: Paper presented at the 19th international conference, CICLing: international conference on computational linguistics and intelligent text processing, Ho Chi Minh City, Vietnam Tankard JW (2001) The empirical approach to the study of media framing. In: Reese SD, Gandy OH, Grant AE (eds) Framing public life: perspectives on media and our understanding of the social world. Lawrence Erlbaum, Mahwah, New Jersey, pp 95–106 Tankard J, Hendrickson L, Silbernab J, Bliss K, Ghanem S (1991) Media frames: approaches to conceptualization and measurement. In: Paper presented to the association for education in journalism and mass communication, Boston, MA Triandafyllidou A (2002) Negotiating nationhood in a changing Europe: views from the press, vol 28. Edwin Mellen Press Triandafyllidou A, Fotiou A (1998) Sustainability and modernity in the European Union: a frame theory approach to policy-making. Sociol Res Online 3(1):60–75 Trochim WM (2006) The research methods knowledge base, 2nd ed. http://www.socialresearchm ethods.net/kb

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Van Dijk TA (1988) News analysis: case studies of international and national news in the press. Lawrence, New Jersey Van Lente H, Spitters C, Peine A (2013) Comparing technological hype cycles: towards a theory. Technol Forecast Soc Chang 80(8):1615–1628 Vygotsky LS (1962) Thought and language (trans: Hanfmann E, Vakar G). MIT Press, Massachusetts Young MD, Schafer M (1998) Is there method in our madness? Ways of assessing cognition in international relations. Mershon Int Stud Rev 42(Supplement 1):63–96 Zhang B, Dafoe A (2019) Artificial intelligence: American attitudes and trends. SSRN, 19 January Zhang L, Wang H, Li Q, Zhao M-H, Zhan Q-M (2018) Big data and medical research in China. British Med J 2018(360). https://doi.org/10.1136/bmj.j5910

Ahmet Suerdem (PhD) is a professor in the Business Administration Faculty at Istanbul Bilgi University. He is also a Senior Academic Visitor at LSE’s Psychological and Behavioural Sciences Department. He received his doctorate from Paris 8 University on educational sciences and institutional analysis. He was a European Council post-doctoral fellow at Paris 5, Social Anthropology Department and Visiting Research Fellow at the UCLA and UCI marketing departments. He was involved in several international and national projects as a director and researcher. His areas of expertise include science in society, science culture, public understanding of science, text mining, content analysis, social network analysis, multivariate statistical analysis, bridging qualitative and quantitative research methods; consumer culture; and social aspects of system design. He is an expert in many statistical and qualitative data analysis software and coding and analytics tools such as R, Python and KNIME. Serhat Akkılıç has earned his PhD degree in Communication from Istanbul Bilgi University (2020), BSc degree from Istanbul Technical University (1992) and MBA from Koç University (1998). As a marketing communications professional, he co-founded one of Turkey’s leading digital communications companies in 1999 and he is currently leading HAVAS Creative and CX group companies. He taught an undergraduate Communication Design course and currently colectures MBA-level Digital Transformation courses at Istanbul Bilgi University. As an independent researcher, he focuses on technology–human relations and communication.

Chapter 11

Segmentation Disparities in Scientific Experts’ Knowledge of and Attitudes Towards GMOs in China Jianbin Jin, Xiaoxiao Cheng, and Zhaohui Li

Abstract Genetically modified organisms (GMOs) have been a unique topic of continuous controversy in the past decade in China and beyond. Although a vast body of literature has been devoted to polarized public opinions about GMOs, there remains a dearth of research exploring the views of scientific experts. The cognition-based dimension of attitudes—to be specific, the relationship between scientific knowledge and attitudes towards GMOs—has attracted extensive scholarly attention, yet no systematic and uniform conclusion can be drawn based on the observations of the lay public. This study attempts to offer a fresh understanding of the experts’ cognitionbased attitudes to GMOs by employing a segmentation strategy, through which the knowledge–attitudes association among presumably distinctive expert segments can be observed more clearly. Based on the latest large-scale national survey involving 11,538 valid cases of scientific experts in China, this study verifies the existence of segmentation disparities among Chinese experts regarding their knowledge levels and differentiated attitudes to GMOs, as characterized by their disciplinary fields, institutional affiliations and education levels. This study also contributes to the current academic debate over the relationship between knowledge and attitudes by revealing a relatively constant pattern of a positive knowledge–attitude association partially and substantially mediated by perceived benefit and perceived risk across various segments within science communities. Keywords Segmentation analysis · Deficit model · Attitudes towards GMOs · Scientists and experts · Perceived risk · Perceived benefit

J. Jin (B) · X. Cheng School of Journalism and Communication, Tsinghua University, Beijing, China e-mail: [email protected] X. Cheng e-mail: [email protected] Z. Li National Communication Center for Science and Technology, China Association for Science and Technology, Beijing, China e-mail: [email protected] © China Science and Technology Press 2021 B. Schiele et al. (eds.), Science Cultures in a Diverse World: Knowing, Sharing, Caring, https://doi.org/10.1007/978-981-16-5379-7_11

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Public understanding of and attitudes towards controversial scientific issues such as GMOs have been a prominent research focus in science communication over the past few decades. Vast numbers of conceptual tools and much empirical evidence have been developed and accumulated through efforts to fully unravel the complexities behind polarized opinions about GM technologies among the general public around the globe. Nevertheless, a critical area of inquiry into various experts’ perspectives is still far from complete. Although there have been several studies that address the prevalence of perceptional and attitudinal gaps between experts and the public in the food domain in general (Siegrist et al. 2018) and in GMOs in particular (Hartmann et al. 2018; Kato-Nitta et al. 2019; Savadori et al. 2004), topics such as experts’ conceptualizations and perceptions of GMOs remain largely underexplored (Huang et al. 2017). This issue is of great importance not only because scientific experts usually play crucial roles in policymaking in contemporary governance, but also because of their explicit and implicit influence on media coverage and public perceptions of emerging technologies (Beaudrie et al. 2014; Bertoldo et al. 2016; Goldberg et al. 2019; Ho et al. 2011; Kim et al. 2012; Su et al. 2016; van Dijk et al. 2017). To some extent, it is proper to view experts as the opinion leaders of the general public. As for the situation in China, over the years, the so-called ‘manufactured scientific controversy’ (Ceccarelli 2011, 2013) surrounding GMOs has moved further away from science per se (Cui and Shoemaker 2018) and is increasingly chaotic in the public sphere, while ‘China has reached a decision point as to whether it should accept, reject, or go slow with the use of GM technology’ (Cui and Shoemaker 2018:1). It is in this theoretical and social context that we discuss experts’ views about GMOs in China.

11.1 Literature Review 11.1.1 The Cognition-Based Dimension of Attitude Among Expert Segments The cognition-based dimension of attitude offers a starting point for our discussion. As a dominant theoretical underpinning, the association between scientific knowledge and the public’s attitudes to GMOs and other controversial scientific issues has been studied extensively. The underlying assumption of this research orientation is that the formation of attitudes to GMOs among the general public basically follows a bottom-up approach, through which individuals form their attitudes based on what they know about the technology and its features (Costa-Font et al. 2008; Zhu and Xie 2015). That assumption, however, faces some theoretical and empirical challenges. One major exogenous challenge is associated with the criticism that attitude is embedded in a system of value beliefs that preserve the evaluative tendency of the

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higher-order attitudes (Costa-Font et al. 2008; Rose et al. 2019; Zhu and Xie 2015), and that, therefore, the formation of attitude is subject to perceptual filters such as motivated reasoning, heuristic devices, mental shortcuts and the like (Delshad and Raymond 2013; Hart and Nisbet 2012; Mielby et al. 2013). While there is ample evidence supporting such a psychographic claim among the general public, its applicability cannot be automatically extended to expert groups. It is generally acknowledged that the way experts make judgements tends to be more evidence- or knowledge-based and is systematically distinct from the methods used by relatively ill-informed laypeople, who are more subject to psychological factors and several qualitative characteristics (Hartmann et al. 2018; Urquhart et al. 2017). For instance, one study has found that scientists rely less upon their value predispositions than does the public when forming their regulatory attitudes towards nanotechnology (Su et al. 2016). In GMO-related research, a number of studies lend support to the argument for the cognition-based dimension of attitude among scientifically literate populations (Mielby et al. 2013; Sturgis et al. 2005; Zhu and Xie 2015). For example, Mielby et al. (2013) found that scientifically knowledgeable people are more likely to condition their acceptance of a GM application on its purpose and utility rather than on an obsession with naturalness. Those findings suggest that scientific backgrounds function as a lens through which experts cognitively approach the issue (Bertoldo et al. 2016) and therefore base their attitudes to GMOs on a cognitive foundation (Zhu and Xie 2015). In the light of this, our study mainly investigated the cognition-based dimension of experts’ attitudes to GMOs. The biggest endogenous challenge of the deficit model of science communication lies in the deterministic and oversimplified way in which attitude formation is explained (Kato-Nitta et al. 2019). While multiple studies have lent support to the linear and positive relationship between scientific literacy and individuals’ attitudes to GMOs, huge disparities remain regarding the form of association (for example, Christoph et al. 2008; Fernbach et al. 2019; Francisco et al. 2019) as well as the direction and magnitude of effects on the knowledge–attitude nexus (for example, Lee and Kim 2018; Rose et al. 2019). As noted by Rose et al. (2019), the relationship between scientific knowledge and attitudes is by no means definitive but varies in direction and across issues and possibly social segments. On the issue of cognition-based understanding of attitude formation, we argue that the so-called ‘expert’ is by no means a monolithic but rather a plural and variable entity (we discuss this in the following section). A nuanced analytical approach embracing the heterogeneity of segments of experts is therefore a reasonable strategy to elaborate the connection between experts’ knowledge of and attitudes towards GMOs. Drawing on previous studies (for example, Besley 2018; Guenther et al. 2018; Runge et al. 2018), we employ a segmentation strategy to explore the knowledge–attitude relationships among expert segments.

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11.1.2 Selecting Variables for Expert Segmentation Generally, segmentation aims to divide the target population into relatively homogeneous but mutually exclusive subgroups (Guenther et al. 2018; Schäfer et al. 2018). We argue that such an approach could, as noted by Beaudrie et al. (2014:12), yield ‘insight into the complexity of risk perceptions, opinions, and regulatory attitudes that can be expected from experts in each group’. The key to conducting segmentation is to select proper grouping identifiers. As we illustrate below, based on the choices of previous researchers, as well as a preliminary examination of stratifying effects of different demographics (Metag and Schäfer 2018), we decided to do the segmentation based on three inherently knowledgerelevant factors: disciplinary field, institutional affiliation and education level. The extant scholarship has observed the existence of variations among experts in their perceptions of and views on controversial issues such as GMOs (for example, Huang et al. 2017) and nanotechnology (for example, Larsson et al. 2019). Overall, studies have overwhelmingly emphasized the significance of the experts’ disciplinary fields and institutional affiliations (two somewhat interrelated constructs) to understand their views about emerging technologies (Beaudrie et al. 2014; Gupta et al. 2012; Powell 2007; van Dijk et al. 2017). The mindset and mentality, as well as the knowledge structure and world views, of experts with different disciplinary training are somehow shaped by specific scientific traditions and research paradigms unique to those fields (Bertoldo et al. 2016; Kato-Nitta et al. 2019; Larsson et al. 2019; Patterson and Williams 2005). For instance, one study found that ‘hard’ scientists from physics, chemistry and engineering fields tend to perceive nanotechnologies more in terms of opportunities than of risks, whereas ‘soft’ scientists, such as those from environmental science, life science and social science, are apt to be more aware of the accompanying risk while acknowledging the benefits (Bertoldo et al. 2016). Beaudrie et al. (2014) have made a similar observation. Institutional affiliation is another important explanatory variable for expert group distinctions (Gupta et al. 2012; Huang et al. 2017; Larsson et al. 2017; Urquhart et al. 2017). The importance of institutional affiliation lies in the societal roles and responsibilities of organizations of various types (Larsson et al. 2017, 2019). Van Dijk et al. (2017) and Larsson et al. (2019) argue that experts affiliated with governmental organizations are more aware of their responsibilities for risk assessment to ensure public health and safety than those working in industries whose concerns are more related to the promotion and commercialization of technologies. For that reason, technocrats are more liable than other groups of experts to be concerned about risks and support the regulation of controversial technologies. Similarly, one study conducted in China (Huang et al. 2017) found that scientists from national research institutions (the Chinese Academy of Sciences and the Chinese Academy of Agricultural Sciences) are more supportive of developing GM technology than their counterparts in universities. Some studies have investigated the effect of education level on expert group distinctions. For instance, Potter et al. (2017) compared the differences in conceptions

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of GMOs among individuals with varying levels of biology expertise (undergraduate, entering and advanced biology majors and biology faculty) and found that biology faculties exhibited evidence of expert thinking by using organismal rationales in understanding GMOs. In contrast, novices in biology (undergraduate students) used essentialist reasoning, thereby leading to misconceptions about GMOs.

11.1.3 Knowledge of, Perceptions of and Attitudes Towards GMOs The knowledge–attitude nexus in science communication is increasingly chaotic, as documented in the extant literature (Lee and Kim 2018). One major factor assumed to be related to the inconsistencies, as has been previously discussed, is the heterogeneity of informants on which different studies based data collection. Another cause, however, might lie in the different specifications for the way through which knowledge is associated with attitude. Some researchers argue that the nature and magnitude of the knowledge–attitude nexus are not so self-evident and straightforward; rather, they are dependent upon various working mechanisms (Allum et al. 2008; Larsson et al. 2019; Lee and Kim 2018). The inconsistency might not be able to be ruled out without specifying the mediators that link knowledge to attitudes (Lee and Kim 2018). One systematic review of multidisciplinary research on public acceptance of GMOs has revealed that consumers’ perceptions of risk and benefit not only play key roles in affecting their attitudes towards GM food but also function as mediators between attitude and other factors, such as knowledge (Costa-Font et al. 2008). More recent empirical observations (Lee and Kim 2018) have lent support to that finding. For instance, Zhu and Xie (2015) performed a survey of 561 graduate students in mainland China and found that risk and benefit perceptions serve as two distinct mechanisms that mediate and co-shape the relationship between knowledge and attitudes towards GMOs. It is noteworthy that very few studies have been devoted to the investigation of indirect correlations between knowledge and attitude (Brossard et al. 2009; Lee and Kim 2018), even though perceived risk and benefit together explain a significant portion of the variance in individuals’ attitudes towards nanotechnology (Larsson et al. 2019) and GMOs (Zhu and Xie 2015). To the best of our knowledge, there have been only very limited studies examining the mediating effect of perception between knowledge and attitude. In this stream of research, a general finding is that lower levels of perceived risk and higher levels of perceived benefit are associated with more favourable views of emerging technologies (for example, Brossard et al. 2009; Corley et al. 2009). However, the empirical evidence is somewhat inconsistent when it comes to the relationship between knowledge and perception: while most studies revealed lower perceived risk and higher perceived benefit as the individual’s level of knowledge increased (for example, Ho

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et al. 2011), some found that knowledge is correlated with perceived benefit but not with perceived risk (for example, Larsson et al. 2017). Taken together, our study tends to address these gaps in the literature by providing a better understanding of the perceptual mechanisms on which the knowledge–attitude nexus relies among expert segments.

11.2 Research Questions The overarching aim of this study was to investigate the segmentation disparities among experts’ cognition-based attitudes towards GMOs, as well as the mechanisms by which knowledge affects attitudes. Since experts are a group of people whose scientific decision-making is typically facts-based and more rational than the decision-making of ill-informed laypeople, we assume that experts’ attitudes are proportionally dependent on their levels of knowledge about GMOs. Furthermore, it seems reasonable to expect that experts with varied disciplinary fields, institutional affiliations and education levels will demonstrate different levels of knowledge of GMOs. The question, however, is ‘In what way are they different?’ We therefore posit the first research question (RQ): RQ1: What are the patterns of disparities among expert segments defined by three specified factors in terms of their knowledge of and attitudes towards GMOs? Our second and third research questions concern the knowledge–attitude relationship and the possible mediating mechanisms of perception (that is, perceived risk and perceived benefit). It is noteworthy that, since the relationship between scientific knowledge and attitudes towards GMOs is dependent upon the level of domainspecific knowledge (Kato-Nitta et al. 2019) among the expert group, as indicated by the three factors in RQ1, the knowledge–attitude relationship and the mechanisms behind it might be conditional, rather than consistent. Following this line of reasoning, we propose our second and third research questions as follows: RQ2: How is scientific knowledge correlated with attitudes towards GMOs among different expert segments? Are there any distinctions between various expert segments in the pattern as well as the magnitude of the association? RQ3: Do the levels of perceived risk and perceived benefit mediate the association between scientific knowledge and attitudes towards GMOs among different expert segments? If so, are there any distinctions between various expert segments in the pattern as well as the magnitude of the knowledge-perception (perceived risk versus perceived benefit)-attitude relationship?

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11.3 Research Design 11.3.1 Sampling The data for this study was collected based on a large-scale national survey organized by the China Association for Science and Technology (CAST1 ), ‘the largest nongovernmental organization of scientific and technological professionals in China’, in the summer of 2019. This is a biennial survey of multi-stage probability sampling of China’s science and technology community, which is composed of 210 national member societies and local branches all over the country. In the latest survey, conducted from 18 to 31 July 2019, a total of 13,532 valid cases were successfully visited through CAST’s national branches and networks of science and technology promotion. The subjects of this survey are so-called scientific and technological professionals. This is a concept with Chinese characteristics and mainly refers to those professionals whose work is related to the research, development, dissemination, promotion and management of science and technologies. Under this definition, they mainly come from eight categories of institutions: scientific research institutes; universities; enterprises and corporations; healthcare institutions; middle schools; science parks; county-level science and technology promotion sites; and CAST’s branches across the country. After being selected and reached based on the sampling procedure mentioned above, those scientific and technological professionals were then directed to an online survey platform to complete a questionnaire in which the main measurement items of this study were included. Since the primary concern of this study was about scientists or broadly defined experts, we excluded three types of cases that were included in CAST’s initial sampling frame: technology-promoting personnel, middle school teachers and those labelled as ‘others’ in the ‘occupation’ options. Ultimately, we derived a final sample of 11,538 valid cases for the purpose of this study. Approximately 58.2% of the respondents were male, and the average age of the whole sample was 37.05 years (SD = 8.08). Among the surveyed sample, 1099 (9.5%) and 3,061 (26.5%) were at the level of professor or associate professor in professional rank, 4296 (37.2%) were at intermediate professional rank, and 3082 (26.7%) were ranked in the primary professional ranks or below.

1

CAST: http://english.cast.org.cn/col/col471/index.html.

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11.3.2 Measurement 11.3.2.1

Scientific Knowledge About GMOs

We differentiated and measured two types of knowledge about GMOs: subjective knowledge and factual knowledge (Ladwig et al. 2012; Rose et al. 2019; Zhang and Liu 2015). To measure subjective knowledge, the respondents were asked to rate their understanding of and/or levels of perceived familiarity with three constructs or terms (hybrid breeding technology, genetically modified food, bio-agricultural technologies) using a 5-point scale in which 1 represented ‘poor’ and 5 ‘excellent’. The level of subjective knowledge was then obtained by averaging the scores for the three items. To measure factual knowledge, based on previous studies, we employed a list of true/false questions about GMOs. There were nine statements described as follows (a to i), and the respondents needed to give their judgement about the correctness of them; a respondent’s level of factual knowledge (M = 2.88, SD = 1.37, KR-20 = 0.82) was then obtained by first summing up the total scores (0 ~ 9) and then converting them to a scaling range from 0 to 5 to make it directly comparable with that of subjective knowledge (M = 3.04, SD = 0.75, α = 0.86). (a) (b) (c) (d) (e) (f) (g) (h) (i)

Ordinary tomatoes do not carry genes, but genetically modified tomatoes do. (F) One’s genes could change after eating genetically modified food. (F) It’s impossible to insert a clip of animal gene into the genome of plants. (F) Genetically modified tomatoes with fish genes taste like fish. (F) The genome of humans and that of gorillas are 98% the same. (T) All living things are made up of cells. (T) Transgenic technology is the introduction of known good genes into the genome of an organism. (T) Food from authorized GM crops is no riskier than that from conventionally bred crops. (T) Genetically modified crops and traditional hybrid crops are both bred through genetic changes. (T)

11.3.2.2

Attitude Towards GMOs

We measured attitude to GMOs by asking respondents how much they opposed or supported: (a) (b) (c)

research and development of GMOs commercializing GMOs applying genetic engineering technologies in the biomedical field.

A rating of 1 represented ‘strongly oppose’ and 5 represented ‘strongly support’. The value of attitude was then calculated by averaging the score for the three items (M = 3.13, SD = 0.92, α = 0.82).

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Perceived Benefit and Perceived Risk

We measured the perceived benefit of GMOs by asking respondents’ opinions about the following three statements: (a) (b) (c)

Transgenic technology can reduce the use of pesticides. Transgenic technology can increase the nutrition of crops. Transgenic technology can improve crop yields.

A rating of 1 represented ‘strongly disbelieve’ and 5 represented ‘strongly believe’. We measured the perceived risk of GMOs by asking respondents for their opinions about the following two statements, using the same scaling as for perceived benefit: (a) (b)

Authorized genetically modified food may contain harmful substances. Authorized genetic engineering technologies may harm biodiversity.

The measures for perceived benefit and risk exhibited acceptable internal consistency and thus were combined into two single indexes ranging from 1 to 5, in which higher scores indicated greater levels of perceived benefit (M = 3.32, SD = 0.81, α = 0.78) and perceived risk (M = 3.22, SD = 0.82, α = 0.74) of GMOs, respectively.

11.3.3 Demographics and Grouping Identifiers As justified above based on our review of previous studies on emerging technologies, due to the complexity and diversity of risk perception and attitude formation among experts, it is necessary to elaborate our understanding of the association between the knowledge and attitudes of experts on issues such as GMOs through segmentation. In this study, as illustrated, we stratified experts based on three scientific background characteristics as the grouping identifiers; that is, disciplinary field or major, education level, and occupation (a proxy measure of institutional affiliation). For the disciplinary field or major, while there were 12 specific options in our initial questionnaire for this variable, based on our preliminary observations plus their inherent associations with different disciplines, we recoded the options into four categories: • Bio-Agriculture (biology and agriculture) • Chemi-Medicine (chemistry and medicine) • Sci-Engineering (other science and engineering disciplines excepting BioAgriculture and Chemi-Medicine, including physics, mathematics, geography, astronomy, engineering and materials science and information science) • S-H-A (social sciences, humanities and arts). Education level was categorized into three levels: bachelor or below, master, and doctorate (PhD).

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For occupation, we recoded the initial options into four categories: engineers and technicians; scientists and researchers; university faculty; and administrative staff. It should be noted that the occupational categories are much broader in China than in the West; we used occupation as a surrogate measure of institutional affiliation, given that the occupation-based strata are known to be predictive of social stratification in general and among Chinese knowledge workers in particular (Wang 2016), among whom the available capital, especially the organizational capital, is incorporated into this occupation-based measurement.

11.4 Findings 11.4.1 Disparities of Knowledge and Attitude Among Expert Segments We first examined the stratifying effectiveness of three demographic factors based on experts’ knowledge of and attitudes towards GMOs. For that purpose, we presented the disparities through two approaches, one of which was descriptive and the other inferential. The knowledge levels of expert segments defined by disciplinary field, education level and institutional affiliation or occupation are reported in Table 11.1. For both factual knowledge and subjective knowledge, the expert segments in Bio-Agriculture scored the highest, followed by those in Chemi-Medicine, SciEngineering and S-H-A, in that order. On a scale from 0 to 5 for factual knowledge, for Bio-Agriculture segments, mean knowledge scores of those with doctor, master or bachelor degrees were 3.78, 3.55 and 3.12, respectively. For Chemi-Medicine segments, the scores were 3.24 for doctor, 2.99 for master and 2.74 for bachelor. For the S-H-A segments, the results were 2.51 for doctor, 2.47 for master and 2.42 for bachelor or below. For disparities of knowledge level in each segment with the same disciplinary field and education level, the scientists and researchers sub-segment typically scored highest, followed by the sub-segment of engineers and technicians and university faculty, while the sub-segment of administrative staff typically had the lowest score. This disparity pattern was basically the same for subjective knowledge, as shown in Table 11.1. A clearer illustration of this disparity pattern can be seen in Fig. 11.1, which shows the discrepancies in factual knowledge levels between segments defined by the three grouping identifiers. Significant gaps or divides can be observed between segments with different disciplinary fields (gaps among the lines) and education levels (points within the same line). Figure 11.2 shows the disparities in subjective knowledge among expert segments. Compared to the disparities in factual knowledge, the disparities in subjective knowledge between the Bio-Agriculture segments and the other three disciplinary segments were even bigger, while the differences among the latter three segments shrank, indicating that relatively more knowledgeable experts

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Table 11.1 GMO knowledge of segments defined by disciplinary field, education level, and occupation Variables

Factual knowledge Subjective knowledge

N

Disciplinary field

Education Occupation level

Mean (SD)

Bio-Agriculture

Bachelor Engineers and or below technicians (N = 484) Scientists and researchers

3.04 (1.22) 3.12 3.33 (0.73) 3.52 103 (1.24) (0.76) 3.37 (1.13)

3.72 (0.70)

145

3.00 (1.43)

3.55 (0.87)

33

Administrative 3.00 (1.27) staff

3.47 (0.78)

203

University faculty

Master (N Engineers and = 765) technicians

3.41 (1.23) 3.55 3.55 (0.78) 3.71 129 (1.14) (0.80)

Scientists and researchers

3.70(1.08)

3.86 (0.76)

293

University faculty

3.33 (1.21)

3.6 (0.84)

94

3.66 (0.82)

249

Administrative 3.53 (1.12) staff Doctor (N Engineers and = 725) technicians

3.21 (1.34) 3.78 3.72 (0.77) 3.96 13 (1.12) (0.82)

Scientists and researchers

3.95 (1.03)

4.06 (0.80)

344

University faculty

3.62 (1.17)

3.90 (0.82)

290

Administrative 3.72 (1.16) staff

3.78 (0.84)

78

Chemi-Medicine Bachelor Engineers and or below technicians (N = 749) Scientists and researchers

2.75 (1.38) 2.74 2.87 (0.64) 2.89 538 (1.39) (0.64) 2.89 (1.47)

3.01 (0.68)

25

2.64 (1.47)

3.08 (0.76)

20

Administrative 2.69 (1.40) staff

2.91 (0.63)

166

University faculty

Master (n = 1063)

Mean (SD)

Engineers and technicians

2.97 (1.35) 2.99 2.84 (0.60) 2.86 773 (1.34) (0.61)

Scientists and researchers

3.29 (1.27)

3.05 (0.68)

59

University faculty

2.79 (1.37)

2.89 (0.59)

70

Administrative 3.04 (1.30) staff

2.91 (0.62)

161 (continued)

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Table 11.1 (continued) Variables Disciplinary field

Sci-Engineering

Factual knowledge Subjective knowledge Education Occupation level

Mean (SD)

Doctor (n = 752)

Engineers and technicians

3.30 (1.27) 3.24 3.05 (0.70) 3.08 278 (1.26) (0.69)

Scientists and researchers

3.50 (1.21)

3.17 (0.73)

118

University faculty

3.07 (1.25)

3.05 (0.67)

295

Administrative 3.25 (1.19) staff

3.17 (0.72)

61

Bachelor or below (n = 1871)

Master (n = 1562)

Doctor (n = 1262)

S-H-A

N

Mean (SD)

Engineers and technicians

2.62 (1.31) 2.58 2.82 (0.64) 2.81 1350 (1.33) (0.63)

Scientists and researchers

2.58 (1.45)

3.09 (0.66)

34

University faculty

2.57 (1.12)

2.94 (0.67)

86

Administrative 2.45 (1.41) staff

2.75 (0.57)

401

Engineers and technicians

2.85 (1.25) 2.80 2.90 (0.62) 2.89 898 (1.29) (0.60)

Scientists and researchers

3.11 (1.32)

3.01 (0.59)

103

University faculty

2.61 (1.33)

2.87 (0.59)

293

Administrative 2.70 (1.31) staff

2.89 (0.60)

268

Engineers and technicians

2.80 (1.33) 2.86 2.88 (0.63) 2.98 138 (1.33) (0.65)

Scientists and researchers

3.03 (1.40)

3.04 (0.67)

128

University faculty

2.86 (1.31)

2.98 (0.65)

911

Administrative 2.67 (1.46) staff

3.01 (0.63)

85

Bachelor Engineers and or below technicians (n = 591) Scientists and researchers

2.39 (1.32) 2.42 2.74 (0.59) 2.86 64 (1.43) (0.62) 2.54 (1.66)

3.00 (0.88)

7

2.09 (1.34)

2.82 (0.55)

71

Administrative 2.47 (1.45) staff

2.88 (0.63)

449

University faculty

(continued)

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Table 11.1 (continued) Variables Disciplinary field

Factual knowledge Subjective knowledge

N

Education Occupation level

Mean (SD)

Master (n = 475)

Engineers and technicians

2.76 (1.23) 2.47 3.02 (0.63) 2.84 29 (1.43) (0.60)

Scientists and researchers

2.75 (1.32)

2.83(0.52)

20

University faculty

2.31 (1.43)

2.84 (0.60)

224

Administrative 2.59 (1.45) staff

2.81 (0.61)

202

Doctor (n = 215)

Mean (SD)

Engineers and technicians

3.33 (1.67) 2.51 2.89 (0.51) 2.94 3 (1.36) (0.70)

Scientists and researchers

3.23 (1.25)

3.31 (0.83)

16

University faculty

2.44 (1.36)

2.90 (0.69)

183

Administrative 2.44 (1.29) staff

3.03 (0.69)

13

S-H-A = social sciences, humanities and arts 3.65 3.45 3.25 3.05 2.91

2.85 2.65

2.45 2.25 Bachelor or below

M aster

Bio- Agriculture

C hem i- M edicine

S- H - A

Observed grand m ean

P hD Sci- Engineering

Fig. 11.1 Estimated marginal means of factual knowledge about GMOs among expert segments

majored Bio-Agriculture were apt to overestimate their levels of factual knowledge, even though they did know more about the topic. Figure 11.3 shows disparities in attitudes to GMOs among segments, visualized in the same way.

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3.06

2.95 2.75 Bachelor or below

M aster

Bio- Agriculture

C hem i- M edicine

S- H - A

Observed grand m ean

P hD Sci- Engineering

Fig. 11.2 Estimated marginal means of subjective knowledge about GMOs among expert segments 3.70 3.50 3.30

3.14

3.10 2.90 2.70 Bachelor or below

M aster

Bio- Agriculture

C hem i- M edicine

S- H - A

Observed grand m ean

P hD Sci- Engineering

Fig. 11.3 Estimated marginal means of attitudes towards GMOs among expert segments

The general pattern of disparities in attitudes to GMOs among expert segments remained the same: that is, the attitude of the segment majored in Bio-Agriculture was most positive, followed by the segments majored in Chemi-Medicine, SciEngineering and S–H-A, in that sequence. For the differentiating effect of education level, generally speaking, the higher education levels corresponded with a more positive attitude towards GMOs, with an exception in the case of the segment with S-H-A expertise, in which those with master’s degrees were, in fact, the most positive towards GMOs. After descriptive illustrations of the disparities of knowledge and attitude, we also conducted inferential analyses to test the between-subject effects of disciplinary

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field, education level and occupation on knowledge and attitudes via general linear modelling. The results are presented in Table 11.2. Consistent with our descriptive analyses illustrated through charts, in our fullfactorial modelling, basically only the main effects of three grouping identifiers were significant, the only exception being for subjective knowledge, where the interaction between the disciplinary field and education level was significant at the 95% confidence level. Of the discriminating effects, disciplinary field accounted for the largest part, followed by education level and occupation, and the latter two had basically the same level of effect size. Based on the coefficient of determination (R-square) of each model, we can conclude that disciplinary field, education level and occupation collectively provide the best explanation for subjective knowledge in terms of the disparities among expert segments, followed by that of factual knowledge and attitude.

11.4.2 The Association of Knowledge and Attitudes We independently conducted bivariate correlation analyses for segments with differing disciplinary fields between knowledge (including factual knowledge and subjective knowledge) and attitudes. The results are reported in Table 11.3. On the one hand, whether for factual knowledge or subjective knowledge, experts’ knowledge levels were all significantly related to attitudes across different segments defined by the disciplinary field. On the other hand, we also found a certain pattern in correlation strength across expert segments, roughly in alignment with the knowledge level of each segment; that is, the correlation for the Bio-Agriculture segment was the highest (0.443 for factual knowledge and 0.422 for subjective knowledge), followed by the Chemi-Medicine, Sci-Engineering and S–H-A segments, in that sequence. In fact, the discrepancy in the association between knowledge and attitude across segments was very prominent, considering the huge sample size for each segment. This result also echoes the findings, disclosed in previous studies, that the associations and relationships between knowledge and attitude might be different and uncertain for people with different characteristics.

11.4.3 The Mediating Effects of Perceived Benefit and Perceived Risk Between Knowledge and Attitudes We examined the mediating effects of perceived benefit and perceived risk to elaborate on the connections between knowledge and attitude. The analytical tool we employed for that purpose was PROCESS Procedure for SPSS V3.3 developed by Andrew F Hayes (Hayes 2017). The modelling framework and the results are summarized in Table 11.4. Once again, we conducted the analyses for discipline-based

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Table 11.2 Between-subjects effects of disciplinary field, education level and occupation on the knowledge–attitude relationship Source

Dependent variable

Type III sum of squares

df

Mean square

F

Corrected model

Factual knowledge

1644.908a

47

34.998

20.635***

Subjective knowledge

1340.436b

47

28.520

64.415***

Attitude

470.256c

47

10.005

12.243***

Factual knowledge

270.739

3

90.246

53.209***

Subjective knowledge

338.877

3

112.959

255.128***

Disciplinary field

Education

Occupation

Disciplinary field* education

Disciplinary field* occupation

Education* occupation

Disciplinary field* education *occupation

Attitude

100.009

3

33.336

40.791***

Factual knowledge

62.964

2

31.482

18.562***

Subjective knowledge

9.596

2

4.798

10.837***

Attitude

12.729

2

6.365

7.788***

Factual knowledge

41.238

3

13.746

8.105***

Subjective knowledge

9.144

3

3.048

6.884***

Attitude

5.302

3

1.767

2.163

Factual knowledge

12.895

6

2.149

1.267

Subjective knowledge

7.557

6

1.260

2.845*

Attitude

4.595

6

0.766

0.937

Factual knowledge

18.311

9

2.035

1.200

Subjective knowledge

4.129

9

0.459

1.036

Attitude

8.110

9

0.901

1.103

Factual knowledge

4.321

6

0.720

0.425

Subjective knowledge

3.560

6

0.593

1.340

Attitude

6.146

6

1.024

1.253

Factual knowledge

18.832

18

1.046

0.617

Subjective knowledge

9.029

18

0.502

1.133

Attitude

15.035

18

0.835

1.022 (continued)

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Table 11.2 (continued) Source

Dependent variable

Type III sum of squares

df

Mean square

Error

Factual knowledge

17,751.269

10,466

1.696

Subjective knowledge

4633.868

10,466

0.443

Attitude

8553.424

10,466

0.817

Factual knowledge

108,312.346

10,514

Subjective knowledge

104,305.889

10,514

Attitude

112,560.111

10,514

Factual knowledge

19,396.177

10,513

Subjective knowledge

5974.304

10,513

Attitude

9023.680

10,513

Total

Corrected total

F

Notes *P < 0.05, ** P < 0.01, *** P < 0.001 a adjusted R2 = 0.081 b adjusted R2 = 0.221 c adjusted R2 = 0.048 Table 11.3 Correlations between knowledge of and attitude towards GMOs

Disciplinary field Bio-Agriculture

Chemi-Medicine

Sci-Engineering

S–H-A

Dependent variable

Attitudes towards GMOs Correlation (r)

N

Factual knowledge

0.443**

1975

Subjective knowledge

0.422**

Factual knowledge

0.312**

Subjective knowledge

0.227**

Factual knowledge

0.284**

Subjective knowledge

0.160**

Factual knowledge

0.226**

Subjective knowledge

0.134**

S-H-A = social sciences, humanities, and arts *P < 0.05, **P < 0.01, ***P < 0.001

2567

4698

1283

0.200***

Subjective knowledge

M2→Y

0.424***

0.412***

0.439***

0.412***

0.413***

0.391***

0.455***

0.029

– 0.107***

0.035*

– 0.081***

– 0.029

– 0.124***

– 0.191***

– 0.026***

– 0.218***

– 0.264***

– 0.249***

– 0.238***

– 0.225***

– 0.249***

– 0.249***

0.066** (49.3%)

0.077** (34.1%)

0.082 ***(50.9%)

0.122*** (43.0%)

0.097*** (42.8%)

0.132*** (42.3%)

0.188*** (44.5%)

0.172*** (38.9%)

0.134***

0.226***

0.160***

0.284***

0.227***

0.312***

0.422***

0.443***

Total effect

0.018

0.051

0.026

0.081

0.051

0.097

0.178

0.196

R2

S-H-A = social sciences, humanities and arts; X represents knowledge; M1 represents perceived benefit; M2 represents perceived risk; Y represents attitude. *P < 0.05, **P < 0.01, ***P < 0.001

0.175***

0.306***

0.344***

Factual knowledge

0.297***

Subjective knowledge

0.410*** 0.389***

Subjective knowledge

X→M2 – 0.214***

X→Y

M1→Y 0.449***

X→M1 0.484***

Direct effect (% of the total)

Indirect effect

Coefficients (standardized)

Factual knowledge

S-H-A (n = 1,283) Factual knowledge

Sci-Engineering (n = 4,698)

Chemi-Medicine (n = 2,567)

Subjective knowledge

Bio-Agriculture (n Factual knowledge = 1,975)

Segments. by disciplinary field

Table 11.4 The impact of GMO knowledge on attitude towards GMO mediated by perceived benefit and perceived risk

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segments separately, and we examined the mediating effect of perceived benefit and risk for both factual knowledge and subjective knowledge in terms of the paths and magnitudes of their effects on attitudes. First, in accordance with the results of RQ2, in terms of the total effects of knowledge on attitudes, the pattern of effect size disparity was quite similar to that of the correlation analyses as shown in Table 11.3. For both factual knowledge and subjective knowledge, the total effects of knowledge on attitude are in their nature the same as those of the correlation coefficients shown in Table 11.3, which decrease from the Bio-Agriculture segment to the Chemi-Medicine, Sci-Engineering and SH-A segments, in that sequence, and the square of total effects is the corresponding model’s R2 value. Second—and this may be the most important finding of this analysis—perceived benefit and perceived risk do partially mediate the effect of knowledge on attitude. As indicated in the column showing ‘Direct effect’, besides the direct effect of knowledge on attitudes, we also calculated the percentage of direct effect in total effect. Quite consistently across the expert segments, indirect effect accounted for more effect than direct effect; the only exception was in the case of subjective knowledge on attitude for the Sci-Engineering segment, in which the percentage was almost half. On the other hand, the direct effect remained significant, accounting for one-third to one-half of the total effect. Another noticeable finding was that direct effects accounted for a higher percentage for subjective knowledge than that of factual knowledge across all the segments. In other words, compared to subjective knowledge, factual knowledge is more greatly mediated by perceived benefit and perceived risk.

11.5 Conclusions and Discussion We begin our discussion by emphasizing that GMOs continue to be a prominent and controversial issue in Chinese society, and justify the rationale of this study by highlighting the dearth of research exploring the formation of scientific experts’ attitudes to GMOs. We have attempted to offer a fresh understanding of those attitudes as well as the drivers and mechanisms behind them through the data obtained in the latest large-scale national survey of Chinese scientific professionals, or experts. The first and foremost conclusion that can be drawn from our study is that significant segmentation disparities among experts in their knowledge of and attitudes towards GMOs do exist (RQ1). Among three stratifying demographic variables, the respondent’s disciplinary field proved to be the most influential factor in differentiating experts’ knowledge and attitudes, followed by education level and institutional affiliation or occupation. In short, the closer one’s disciplinary field is to bio-agricultural technologies, the higher one’s education level is, the more one’s occupation is research-oriented, the higher one’s GMO knowledge level is, and the more positive one’s attitude towards GMOs is. Noticeably, the pattern of such disparities remains basically stable for

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both factual knowledge and subjective knowledge. Such cross-validation has both theoretical and practical significance, given that the two types of knowledge could function differently in shaping attitudes to GMOs (Fernbach et al. 2019; Ladwig et al. 2012; Lee and Kim 2018; Rose et al. 2019; Zhang and Liu 2015). The findings of this study not only confirm the effectiveness of our segmentation tools, but also verify the proposition that those regarded as experts are indeed arranged in segments with diverse knowledge levels and views, rather than forming a monolithic whole. Evidence on the knowledge–attitude association exhibits positive and statistically significant direct effects of knowledge among the expert segments (see Table 11.3), suggesting that a scientist’s knowledge of GMOs is positively correlated with his or her attitude towards GMOs in China (RQ2). Notably, such a connection pattern holds true across the expert segments, as indicated by the four disciplinary fields, notwithstanding variations in magnitude. Taking factual knowledge as an example, the highest correlation was observed among those with Bio-Agriculture expertise, followed by experts with chemistry or medicine backgrounds. Those from social sciences, humanities and arts showed the smallest knowledge–attitude correlation, and those from Sci-Engineering fields had the second lowest correlation. Our findings echo what Huang et al. (2017) have revealed; that is, while a positive relationship exists between factual knowledge about GMOs and attitudes to them among scientists in all disciplinary fields in China, experts in social sciences are less supportive of developing GM technology than those from the physical sciences and technology. As we have discussed, some studies have reported negative (for example, Lee and Kim 2018) or even non-significant (for example, Rose et al. 2019) influence of scientific knowledge on individuals’ attitudes to GMOs. Those studies were typically based on data collected from the general public, and we argue that the heterogeneity of the so-called public is one of the causes for such inconsistency regarding the knowledge–attitude relationship. To some extent, this verifies the necessity and importance of the segmentation strategy we advocate in elaborating our understanding of the nature and mechanism of the knowledge–attitude association. When the research objects are clearly defined, as is the case in our study, some clearly explainable patterns emerge across segments, as shown in Figs. 11.1, 11.2 and 11.3. As we have noted, more knowledgeable people tend to form their attitudes more on a cognitive rather than a perceptual base or mentality (Bertoldo et al. 2016; Su et al. 2016). One empirical observation (Aleksejeva 2014) on European Union (EU), the most conservative region regarding cultivation of GM plants, favours this argument, indicating that the experts make decisions based on knowledge, experience and safety of a particular GMO and are supportive towards use of GMO in food and feed; more important, the experts’ attitude is not extreme as that of the average EU consumer. Our findings convincingly verify that proposition by comparing the evolution of knowledge levels and attitudes, as well as the strong correlation between knowledge and attitude across expert segments. Another primary goal of this study was to elaborate our understanding of how knowledge affects attitude on issues such as GMOs. Based on the literature review and theoretical discussion, we introduced perceived risk and perceived benefit as the mediators of knowledge in its effect on attitude (RQ3). The findings of our study

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show that the effect of knowledge is indeed partially and substantially mediated by perceived benefit and perceived risk across all the expert segments. Also, based on a 5,000-bootstrap resampling technique, we found that all the estimated biascorrected bootstrap confidence intervals did not cover zero, indicating the robustness of the mediating role of perceived risk and perceived benefit in the knowledge–attitude relationship (Costa-Font et al. 2008; Zhu and Xie 2015) among Chinese expert segments. It is also important to note that the estimated indirect effect accounted for the majority of total effects for experts with different disciplinary backgrounds, indicating the prominence of the perceptual mediating mechanisms on which the knowledge–attitude association is based across Chinese expert segments. Last but not least, we found that perceived benefit and perceived risk function differently in exerting influence on the knowledge–attitude relationship. As expected, levels of perceived benefit co-vary with experts’ knowledge levels, which is then translated to more positive attitudes towards GMOs (Zhu and Xie 2015). Conversely, experts’ factual knowledge level leads to perceptions of reduced perceived risk, which in turn translates to more favourable attitudes towards GMOs (Lee and Kim 2018). Notably, we found that the patterns disclosed above held constant, while the magnitudes varied across segments: large variations were observed in the magnitudes of knowledge–mediator correlations across segments. These results echo a similar divergence found elsewhere in nanotechnology research between ‘hard’ and ‘soft’ (Bertoldo et al. 2016; Besley et al. 2008) and/or ‘upstream’ and ‘downstream’ scientists (Larsson et al. 2019; Powell 2007), in which the latter tend to be more concerned about underlying negative social consequences (Beaudrie et al. 2014; Bertoldo et al. 2016; Larsson et al. 2019; van Dijk et al. 2017). In sum, we found that there do exist segmentation disparities in experts’ knowledge of and attitudes to GMOs, and that the association between them is substantially mediated by perceived benefit and risk. Our study contributes to the current academic debate about the seemingly confusing relationship between knowledge and attitude by identifying the underlying causes and presenting a segmentation strategy to clarify the patterns of knowledge– attitude association. That said, we acknowledge that, in our sample, the perceptions of and attitudes to GMOs among expert segments are subject to the respondents’ inherent and unobservable biases, which are hard to detect and measure by using self-reporting instruments. Future studies should explore the possibility of alternative measures of both knowledge and attitudes and conduct some cross-validation to test the stability and robustness of the relationships found here. Acknowledgements This research is financed by China’s State Major Research Projects on Breeding New Varieties of Genetically Modified Organisms under grant number 2016ZX08015002.

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Kato-Nitta N, Maeda T, Inagaki Y, Tachikawa M (2019) Expert and public perceptions of gene-edited crops: attitude changes in relation to scientific knowledge. Palgrave Commun 5(1):1–14 Kim Y, Corley EA, Scheufele DA (2012) Classifying US nano-scientists: of cautious innovators, regulators, and technology optimists. Sci Public Policy 39(1):30–38 Ladwig P, Dalrymple KE, Brossard D, Scheufele DA, Corley EA (2012) Perceived familiarity or factual knowledge? Comparing operationalizations of scientific understanding. Sci Public Policy 39(6):761–774 Larsson S, Boholm Å, Magnus J (2017) Attitudes towards nanomaterials and nanotechnology among Swedish expert stakeholders: risk, benefit and regulation. Gothenburg Res Inst Larsson S, Jansson M, Boholm Å (2019) Expert stakeholders’ perception of nanotechnology: risk, benefit, knowledge, and regulation. J Nanopart Res 21(3):57 Lee S, Kim S-H (2018) Scientific knowledge and attitudes toward science in South Korea: does knowledge lead to favorable attitudes? Sci Commun 40(2):147–172 Metag J, Schäfer MS (2018) Audience segments in environmental and science communication: recent findings and future perspectives. Environ Commun 12(8):995–1004 Mielby H, Sandøe P, Lassen J (2013) The role of scientific knowledge in shaping public attitudes to GM technologies. Public Underst Sci 22(2):155–168 Patterson ME, Williams DR (2005) Maintaining research traditions on place: diversity of thought and scientific progress. J Environ Psychol 25(4):361–380 Potter LM, Bissonnette SA, Knight JD, Tanner KD (2017) Investigating novice and expert conceptions of genetically modified organisms. CBE—Life Sci Educ 16(3):ar52 Powell MC (2007) New risk or old risk, high risk or no risk? How scientists’ standpoints shape their nanotechnology risk frames. Health Risk Soc 9(2):173–190 Rose KM, Howell EL, Su LY-F, Xenos MA, Brossard D, Scheufele DA (2019) Distinguishing scientific knowledge: the impact of different measures of knowledge on genetically modified food attitudes. Public Underst Sci 28(4):449–467 Runge KK, Brossard D, Xenos MA (2018) Protective progressives to distrustful traditionalists: a post hoc segmentation method for science communication. Environ Commun 12(8):1023–1045 Savadori L, Savio S, Nicotra E, Rumiati R, Finucane M, Slovic P (2004) Expert and public perception of risk from biotechnology. Risk Anal Int J 24(5):1289–1299 Schäfer MS, Füchslin T, Metag J, Kristiansen S, Rauchfleisch A (2018) The different audiences of science communication: a segmentation analysis of the Swiss population’s perceptions of science and their information and media use patterns. Public Underst Sci 27(7):836–856 Siegrist M, Hübner P, Hartmann C (2018) Risk prioritization in the food domain using deliberative and survey methods: differences between experts and laypeople. Risk Anal 38(3):504–524 Sturgis P, Cooper H, Fife-Schaw C (2005) Attitudes to biotechnology: estimating the opinions of a better-informed public. New Genet Soc 24(1):31–56 Su LY-F, Cacciatore MA, Brossard D, Corley EA, Scheufele DA, Xenos MA (2016) Attitudinal gaps: how experts and lay audiences form policy attitudes toward controversial science. Sci Public Policy 43(2):196–206 Urquhart J, Potter C, Barnett J, Fellenor J, Mumford J, Quine CP (2017) Expert risk perceptions and the social amplification of risk: a case study in invasive tree pests and diseases. Environ Sci Policy 77:172–178 van Dijk H, Fischer AR, Marvin HJ, van Trijp HC (2017) Determinants of stakeholders’ attitudes towards a new technology: nanotechnology applications for food, water, energy and medicine. J Risk Res 20(2):277–298 Wang C (2016) The subtle logics of knowledge conflicts in China’s foreign enterprises. Springer, New York Zhang M, Liu GL (2015) The effects of consumers’ subjective and objective knowledge on perceptions and attitude towards genetically modified foods: objective knowledge as a determinant. Int J Food Sci Technol 50(5):1198–1205 Zhu X, Xie X (2015) Effects of knowledge on attitude formation and change toward genetically modified foods. Risk Anal 35(5):790–881

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Jianbin Jin is a professor at Tsinghua University. He earned his BE degree in 1991 from the Department of Material Science and Engineering, his BA degree in 1992 from the Department of Chinese Language and Literature, and his ME degree in 1997 from the School of Economics and Management, Tsinghua University. He obtained his PhD degree in 2002 from the School of Communication, Hong Kong Baptist University. His research interests lie in empirical studies of media adoption, uses and effects, and science and risk communication. He has published more than 100 papers and book chapters in academic journals and books. Currently, he serves as a vice president of the Chinese Association of Science and Technology Communication and as a council member of the China Communication Association. He is a member of the Academic Committee of Tsinghua University and the director of the Academic Committee of Tsinghua School of Journalism and Communication. Xiaoxiao Cheng is a PhD. candidate in the School of Journalism and Communication at Tsinghua University, China. His research interests lie in SHER (science, health, environmental and risk) communication, computational communication and political communication. His academic works have been published in the International Journal of Communication, among other outlets. He has presented a number of papers at the annual conferences of ICA and AEJMC. He won the Top Student Paper Award in the 2018 ICA Environmental Communication Division and 2019 McCombs Shaw Award for Best Student Paper in the AEJMC Political Communication Interest Group. His PhD dissertation is currently investigating the collaboration and diffusion of public expressions related to genetically modified organisms (GMOs) risks on Chinese social networking sites. He takes a multidisciplinary approach that encompasses the fields of communication studies, sociology, network science and information science. Zhaohui Li is an associate professor at the National Communication Center for Science and Technology, CAST. His research interests are in theoretical and practical studies on science communication and technology diffusion. He was the co-author and co-editor of a series of books titled Blue Books: development report of science popularization infrastructure in China (2009, 2010, 2011, 2012–2013). He has participated in the continuous construction of the China Communication Center for Science and Technology since 2014 and is interested in theoretical and practical studies on promoting the transformation of scientific and technological achievements in China since 2015.

Chapter 12

Responsible Research and Innovation in China and the Risks in Innovation Yandong Zhao and Miao Liao

Abstract Innovation is a risky process; it entails both the risk of failure and economic, political, social and ethical risks due to unexpected consequences. Failure to control innovation risks can lead to many detrimental consequences. As an endeavour to reduce and control risk in innovation, responsible research and innovation (RRI) has recently become a hotly discussed concept in science and technology policy research and policymaking in developed countries. Rapid social transition in China has led to a series of changes in attitudes towards and behaviour related to responsibility for innovation among various stakeholders, including the public, the scientific community, enterprises and government. Those changes provide an ideal environment for RRI in China as well as for reducing the risks of innovation and guiding innovation to meet people’s needs for better lives. Keywords Innovation · Risk · Governance · Responsible research and innovation · Science and technology policy

12.1 Introduction Today, as China’s economic and social development enters a new era, innovation has become the main theme of the times. In this connection, both the Communist Party of China and the Chinese Government have launched a host of policy goals, including driving development through innovation, building an innovative country and promoting mass entrepreneurship and innovation. Innovation is also changing people’s daily lives at an unprecedented pace. On the other hand, it is a complex and risky process, and the risks of innovation and its governance must not be overlooked when discussing it. In order to control innovation risks and promote sustainable and Y. Zhao (B) Department of Sociology, Renmin University of China, Beijing, China e-mail: [email protected] M. Liao Changsha University of Science and Technology, Changsha, China e-mail: [email protected] © China Science and Technology Press 2021 B. Schiele et al. (eds.), Science Cultures in a Diverse World: Knowing, Sharing, Caring, https://doi.org/10.1007/978-981-16-5379-7_12

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responsible innovation, the concept of responsible research and innovation (RRI) should be strongly advocated. In recent years, rapid social transformation has taken place in China, and various RRI stakeholders are emerging rapidly, which provides a positive social environment for RRI development in the country. At the same time, the process involves numerous difficulties and challenges. Defusing innovation risks by promoting responsible innovation is an issue that requires more exploration, both in theory and in practice.

12.2 Innovation is a Highly Risky Process Innovation used to be a broad concept encompassing change in all areas of politics, economies, social systems and so on. As societies have modernized, the scope for innovation has gradually narrowed, and it now focuses mainly on scientific research, technological development and commercial applications. The risks of innovation have also been a concern for researchers in this field. Joseph Schumpeter, the founder of modern innovation theory, argued that one of the three defining features of innovation is its fundamental and inherent uncertainty (Fagerburg 2009). The risks of innovation can be divided into two main categories. One is the risk of innovation failure; that is, the possibility that the innovation activity fails to achieve the desired goal or deviates from that goal. The main manifestations include the termination or withdrawal of the innovation activity, failure to achieve the original purpose and failure of business operations (Yuan and Wang 2002). The other type of risk is risk resulting from the side effects or unintended consequences of innovation, and is more complicated. Sociologists have pointed out that intentional social actions taken by human beings may often lead to outcomes that are beyond the original purpose. In particular, in modern society, due to the rapid advance of science and technology (S&T) and the increasing complexity of society, innovation has caused more unforeseeable consequences with wider impact and become a major source of risk (Beck 2004). The main risks include political, economic, social and ethical risks.

12.2.1 Political Risks Science, technology and innovation present new opportunities for and challenges to the existing model of government administration and the functioning of politics. They have fundamentally changed the relationship between the government and the market and between the state and society. In today’s society, new technologies such as the internet and big data continue to create new political spaces, which has made the management of society more difficult and weakened governments’ administrative capacity. The emergence of large new technology companies in recent years has reshaped the model of government regulation, the delivery of public services and the

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operation of state power. They are no longer content to provide services and advice to governments but are more actively involved in the process of government management and seek to influence its decision-making (Fan 2018). Those factors bring new and unpredictable risks to the political governance of any country, including China.

12.2.2 Economic Risks While technological innovation continues to disrupt existing market structures and combine factors of production into new productive functions, it naturally creates potential risks in the economic field. Take employment as an example. Innovation has involved a constant cycle of creating new jobs while destroying the old ones. In recent years, the rapid advance of big data, cloud computing, intelligent devices and other technologies has given rise to new forms of business, such as e-commerce, the sharing economy and internet finance. They have created new value and provided new jobs, but also taken a heavy toll on traditional industries and increased the risk of massive unemployment. Despite differences in the data produced by various agencies, there is a nearly unanimous view in the research community that a substantial number of routine and operational jobs will be performed by robots or intelligent systems in the near future. In 2016, Citibank and the University of Oxford published a joint report stating that 47% of the current jobs in the US, 57% in OECD countries, 69% in India and 77% in China are at risk of being replaced by automated technology in the coming 10–20 years (Citi GPS 2016). When large numbers of ordinary workers become ‘structurally unemployed’ and run into structural ceilings in employment and income growth due to the progress of technology, that could seriously jeopardize the stability of the entire socio-economic system.

12.2.3 Social Risks Every major technological innovation and industrial revolution in human history is followed by major adjustments in social structures. Take changes in class structure as an example. The first industrial revolution, resulting from the invention of the steam engine, turned peasants into industrial workers. In the transition to so-called ‘post-industrial’ society, the white-collar class overtook the blue-collar class in many developed countries. Over recent decades, however, the rapid advance of technologies has led to dramatic changes in organizational structures, wiping out a large number of white-collar jobs, including lower and middle-level management positions in factories and administrative positions in offices, resulting in the so-called ‘decline of the middle class’. In the wake of the 2008 global financial crisis, the US and European countries, driven mainly by technological innovation and monetary policy, entered a period of ‘jobless recovery’. The middle-income group is shrinking due to falling incomes, and the high-income and low-income groups are expanding,

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bringing about profound changes in the social structure. At the same time, driven by a new round of the technological revolution, the logic of capital appreciation will go through a fundamental shift, and the scope for ‘winner-takes-all’ outcomes will expand further. All this could make social inequality even worse. The latest research of the McKinsey Global Institute shows that companies, individuals and countries that have a head start on artificial intelligence (AI) technology are more likely to lead in the future competition and, at the national level, developed countries that are leaders in AI technology will gain an extra 20–25% in benefits in 2030 compared to today, while growth in emerging economies will be only 5–15% higher. In the future, the application of AI technology will further widen the ‘digital divide’ and social inequality (Bughin and Zeebroeck 2018).

12.2.4 Ethical Risks Developments in S&T are having a constant impact on the ethical norms and moral codes that regulate relationships between individual human beings and between humanity and nature. At present, the rapid advance and widespread application of new technologies such as information technology, AI and biotechnology have had strong impacts on social values concerning people’s ethics, safety, health and privacy that were developed under earlier technological conditions. For example, genetic editing technology has broad application in the treatment of major diseases and the eradication of certain genetic diseases, yet it has also caused a huge controversy about whether humans are at liberty to design the genomes of their offspring and treat infants as engineered products with the possibility of ‘customization’. All these are issues concerning the dignity and rights of human beings. The development of information technology, big data and AI has also raised questions about privacy, security and regulation. The prospect of resource depletion and ecological damage that may come as a result of S&T innovation, as well as environmental risks such as climate change, have caused concerns about the sustainability of the development of future generations.

12.3 Lack of Understanding of Innovation Risks Endangers the Sustainability of Innovation Failure to understand the risks of innovation and put them under effective governance can be detrimental to innovation and even make it unsustainable. The harms to innovation are manifested in the following ways.

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12.3.1 Lack of Tolerance for the Risk of Failure Discourages Innovation Since failure in the process of S&T innovation is a high-probability event, we should fully tolerate failure in order to encourage innovation. Tolerance of failure should be embodied in the management system of S&T innovation and in the culture of the whole society. However, it is undeniable that China is not doing very well in properly understanding the risk of innovation failure and building a system and culture that tolerate failure. Those problems, to some extent, are the causes of an impetuous culture in academic circles and the lack of motivation for innovation and entrepreneurship in society. Although China has come a long way in science, technology and innovation, the ongoing trade friction between China and the US has exposed the bottlenecks constraining China’s technological progress, including its weak capacity for original innovation and overdependence on core and critical technologies. When discussing the causes of those phenomena, people often put the blame on the prevailing impetuous culture in China’s scientific community. However, it should also be noted that the lack of a social and cultural atmosphere that tolerates innovation failure and protects innovators is a main reason behind that culture. According to the national surveys of S&T workers conducted by the China Association for Science and Technology in recent years, most S&T workers think that the lack of an ‘atmosphere of tolerance for failure’ is a weak link in China’s innovation environment. In the 2008 survey, 48% of the respondents rated the atmosphere as ‘average’ and 28% as ‘not good’. In the 2013 survey, the situation improved slightly, but the respondents who chose ‘average’ and ‘not good’ still reached 37 and 22%, respectively (CRPD-CDRC 2015). Many researchers said that the current research evaluation system overemphasizes quantity and short-term results, not high quality and long-term impact, and that the S&T management system is too strict and gives no acknowledgement of or protection for innovation failure. Under such an evaluation and management system, researchers prefer to work on quick and easy projects that are more likely to succeed and often turn away from potentially disruptive and groundbreaking research projects.

12.3.2 Ignoring the Social Risks of Innovation Leads to Public Opposition to and Scepticism About Innovation There is no shortage of episodes in human history when the speed and magnitude of innovation caused concerns and even fears. Different versions of anti-innovation theories enter the public discourse in an almost cyclical pattern, and various pseudoscientific and superstitious ideologies emerge from time to time, such as the Luddite movement in England during the industrial revolution and the anti-Uber campaigns

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that have swept across the world in recent years. In particular, when innovators ignore the social risks that can result from innovation or fail to communicate the risks effectively to the public, people’s attitudes to innovation can be skewed towards scepticism and opposition. Genetic technology is a perfect case in point. According to a series of surveys in China, public acceptance of genetically modified (GM) food has been on a steady decline in recent years. The 2006 survey showed that 65% of Chinese urban consumers could accept GM food, yet, in the 2016 survey, only 25.7% of respondents expressly supported the promotion of GM rice cultivation in China, while 65.2% categorically rejected the notion; 18.9% of respondents clearly stated that they were OK with GM foods, while 72.8% made clear that they would not eat such foods (He et al. 2015). The analysis found that the perception of the risks of GM food is an important factor influencing the public attitude towards GM. Of all the respondents who thought that GM food was harmful to human health, 78.0% opposed the promotion of GM rice cultivation in China, and 91.8% refused to eat GM food; in contrast, of the respondents who believed that GM food would cause no harm to human health, only 50.0% opposed the promotion of GM rice cultivation, and only 52.7% refused to eat GM food. Jim Al-Khalili, president of the British Science Association, fears that AI technology in the future may face the same danger as GM technology today. He has argued that, without transparency and public engagement, the potential of AI may be stifled by a fear-dominated public response.1 If an innovative technology fails to gain sufficient acceptance in society and is questioned and boycotted by the public, it will be impossible to achieve its universal application and reach the goal of innovation, no matter how big a breakthrough is made at the technological level.

12.3.3 Ignoring the Social Risks of Innovation Leads to the Gradual Deterioration of the Social Environment for Innovation Failure to properly understand the unanticipated risks of innovation and develop an effective social consensus on innovation risks can also lead to public scepticism about the social institutions in favour of innovation, thus damaging the innovation environment and ultimately jeopardizing the sustainability of innovation. Scepticism about the benefit-distribution mechanism The market economy system has been working as an efficient system for stimulating innovation activity and distributing the benefits of innovation. However, the benefits of innovation, which is, in essence, a form of ‘creative destruction’, can never be equally distributed among social groups. Innovation is bound to disrupt the existing 1

Warning from British science leader: the threat of artificial intelligence bigger than terrorism, Can Kao Xiao Xi, 12 September 2018, 7.

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pattern of interests and generate winners and losers in relative terms. At the same time, people’s perceptions of the distribution of innovation benefits are deeply shaped by their social connections. When measuring the benefits of innovation, people might not compare them with what they had in the past, but more likely compare what they have gained with what people around them have gained. In many cases, people oppose innovation not because of their absolute losses but because they believe their share in the benefits is shrinking due to innovation. They think their relative weight is declining and therefore feel a strong sense of relative deprivation. Groups that are disadvantaged in either absolute or relative terms are unable to automatically absorb and adapt themselves to the shocks of innovation. Powerful interest groups may even seek to stop innovation from changing the existing pattern of interests by influencing government policies and reject the allocation of innovation benefits by the market. Scepticism about the administrative capacity of government The Chinese Government is both a funder and promoter of innovation and a market regulator. Because of such a dual role, it is impossible for the government to stay away from the controversy about new technologies, new products and new business forms. Its position and actions will directly affect the public’s attitude towards the government. For example, there is a somewhat dangerous trend in the GM debate, in which the controversy over the technology itself has shifted to questions about the administrative capacity of the government. Many GM opponents like to say, ‘I agree that the risks of GM are theoretically manageable, but what I don’t trust is the government’s ability to manage it well.’ As shown by the results of a 2016 survey conducted by the Chinese Academy of Science and Technology for Development on the public’s attitude to GM technology, such an argument has fairly large support in society. On the issue of genetically modified organisms (GMOs), only 33.1% of respondents said they trusted the information provided by government officials, and 66.6% believed that China’s institutional regulations on GMO management were still inadequate. In addition, 27.2% said they did not trust the ability of the government to manage public affairs, while only 39.1% expressed faith in the government (He et al. 2016). In the past decade or so, ‘not in my backyard’ (NIMBY) campaigns against the construction of PX (para-xylene) plants, waste incineration stations and other facilities have happened from time to time in China. While the specific causes are complex and varied, public mistrust of the government’s administrative capacity is a key factor. What has happened in recent years shows that the social risks posed by science, technology and innovation, if not properly managed, can have a considerable negative impact on the image of the government, undermine its credibility in the public’s eyes, and challenge public perceptions of the government’s overall administrative and management capacity. That, in turn, will erode the social foundation and environment for innovation.

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12.4 Promoting Responsible Innovation in China to Dissolve Risks New approaches and systems are constantly being explored to effectively address innovation risks and ensure the sustainability of innovation. One concept in this connection, RRI, has emerged in EU countries and spread around the world in recent years. It is more than just an academic concept; it is also a set of policy initiatives and a social movement. RRI requires ‘mutual feedback between social players and innovators’ in the course of innovation, ‘taking into full account the (ethical) acceptability, sustainability and social desirability of the innovation process and its market products and allowing scientific and technological development to be properly embedded in our society’ (von Schomberg 2012). The essential purpose is to identify the goals and values of science, technology and innovation through public consultation and to shape the direction and path of innovation accordingly in order to realize the goal of mitigating innovation risks and promoting the harmonization of S&T innovation and social development. To achieve responsible innovation in scientific research, it is important to implement the principle of ‘anticipate, reflect, negotiate and feedback’ and to fully anticipate and evaluate the possible consequences (including risks) of innovation activities. The participants in research and innovation activities must constantly reflect on their actions, goals and commitments, and all the stakeholders in innovation must get involved in the governance process, identify the risks and problems that may arise in innovation through dialogue, discussion and consultation, and then readjust and redefine the goals, directions and pathways of innovation through collective consultation (Stilgoe et al. 2013). With the rapid advance of science, technology and innovation in China, the concept of RRI is receiving growing attention from S&T regulators and innovation communities (Liu 2015). Due to accelerated development in the economy, the society and S&T, a series of social changes have taken place in China, bringing RRI and its associated concepts, including ‘responsible research’, ‘scientific ethics’ and ‘science, technology and society’, to the attention of researchers and policymakers. The emergence of a group of RRI activists has created favourable conditions for the recognition and growth of the RRI concept in China and created the possibility of mitigating innovation risks with the RRI concept. This will have different implications for the public, the scientific community, the business sector and the government.

12.4.1 The Public Rapid economic development over the past three decades of reform and opening up has significantly raised the living and education standards of the Chinese people. There has been a general increase in people’s incomes, and the gross enrolment rate of higher education institutions rose from 1.5% in 1978 to 30% in 2013 (Li 2014). With

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the rapid improvement in the public’s standard of living, people’s awareness of rights and safety has also notably increased, and a culture that stresses the pursuit of safety and the proper treatment of life is being formed. At the same time, with increased levels of education and media openness, the public is now better informed about the risks and negative consequences of S&T, resulting in growing public concerns about those risks and consequences and heightened risk awareness. As a result, the Chinese public has become increasingly concerned about the social impact of S&T and has raised higher demands for social responsibility and ethics in science, technology and innovation. Those changes are evident in the changing attitudes of the public towards S&T. For example, in public surveys conducted in recent years on the public image of scientists, when asked whether they agree with the idea that ‘scientists shall be responsible for the bad things committed by other people with their inventions’, the proportion of respondents giving an affirmative answer was 36% in 2007 and rose to 46% in 2010 (STPISTW 2009, 2011) (Fig. 12.1). To some extent, the results reflect the growing public concern over the social consequences of scientific and technological innovation and the higher requirement for responsibility for scientific research. The change in public awareness of the social responsibility for S&T is reflected not only in the changing public attitude, but also in a series of social campaigns. The 2007 public protest against a PX chemical plant project in Xiamen is a typical case, and similar protests have happened in other Chinese cities ever since. The NIMBY movement is gaining traction in China (Tao and Tong 2010). Another typical case is the ‘tobacco academician’ incident in 2011, when a researcher was elected as a member of the Chinese Academy of Engineering for his contribution to technology that reduces the tar content in cigarettes. The election of the academician Scientists shall be responsible for the bad things committed by other people with their inventions

2010

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0% Totally agree

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Fig. 12.1 Changing public attitudes towards the idea that ‘scientists shall be responsible for the bad things committed by other people with their inventions’ Source STPISTW (2009, 2011)

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sparked widespread controversy in society. Opponents argued that the technology was unethical and could create the illusion that smoking was ‘safe’, thereby inducing more people to smoke, and they demanded that the Chinese Academy of Engineering strip the scientist of the title of academician (Li 2013). This incident showed that the public no longer considers the evaluation of S&T innovation as an issue that stays within the scientific community and now demands a broader assessment of the social consequences of innovation. In particular, the rapid diffusion of internet technology has made information on S&T developments more readily available to the public and greatly facilitated public discussion on and participation in S&T issues. The growing public interest in and demand for social responsibility for S&T has added pressure to the development of S&T and created an important impetus for RRI development in China. The public is both a beneficiary of innovation and an undertaker of its risks. In the framework of RRI, the public is no longer an ‘outsider’ to innovation. People must play their part in fostering a public culture that tolerates and encourages innovation and actively participate in the formulation of innovation policies, the selection of innovation pathways, the allocation of innovation benefits and decision-making on the management of innovation risks.

12.4.2 The Scientific Community The Chinese scientific community has always paid close attention to the issue of responsible behaviour in scientific research. Earlier discussions focused mainly on the duty of researchers to uphold research ethics and integrity as members of the scientific community (Cao and Qiu 2008). In recent years, the discussion on responsibility in S&T has moved beyond the boundaries of the scientific community and started to address the possible social impacts and risks of innovation. More and more scientists are becoming aware of the socio-ethical issues involved in their research and work. For example, in the second National Survey of Science and Technology Workers, which was conducted in 2008, only 34.4% of respondents agreed with the proposition that ‘scientists care only about their scientific research and rarely consider the negative consequences of their findings’ (STGSSTW 2010). In a 2012 survey on research ethics conducted among applicants for the National Natural Science Foundation of China, only 18.7% of the applicants believed that their research did not involve the issue of ethics (Zhang et al. 2013). Discussion in the Chinese scientific community on the social ethics and responsibility for research and innovation activities has become increasingly heated. For example, in 2015, a research team at Sun Yat-sen University published a paper on the genetic modification of human embryos, which triggered heated debates on the social ethics of scientific research in Chinese and international academic circles. Natural and social scientists in China have expressed their opinions on the research. Some voiced their support for it, calling it a project conducive to the progress of S&T and the development of human health, while others took a more prudent attitude, calling

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on the researchers to pay more attention to ethical and social responsibility for new technologies (Wang 2015; Li Na 2015; Zhang 2015). Chinese researchers are becoming increasingly aware not only of the social implications of their R&D activities, but also of the importance of communication among stakeholders in the promotion of responsible research. They are taking a more active part in the public discussion on RRI and engaging in close dialogue with fellow researchers, social scientists, ethicists, the public and government, both at home and abroad. Many scientists at the frontiers of S&T have published articles in the media or given interviews to express their concerns about the safety, risks and uncertainties of S&T (Chen 2010; Xue 2010; Zhao 2010; Bai 2011). With the development of the internet and mobile communication technologies in recent years, researchers are also actively communicating with the public through new media channels. The scientific community’s interest in RRI is not limited just to communication and discussion, but also translates into concrete institution-building initiatives. Since 1997, with the promulgation of relevant regulations by the Ministry of Health, the Food and Drug Administration and other departments, many organizations involved in medical research have established ethics committees, paving the way for the launch of the ethical review system. Since 2005, the National Natural Science Foundation of China has explicitly stated in its guidelines that, for research projects involving ethics, the applicant should attach a certificate issued by the ethics committee of the employer or the higher authority (NSFC 2005). In April 2013, the Presidium of the Academic Divisions of the Chinese Academy of Sciences issued the Appeal for responsible practices in GM research, which proposed that scientists engaged in the development of transgenic technology should pay attention to the social impact of the technology’s applications, observe ethical norms, ensure safety, stay sensitive to the ethics of technologies, reflect on the ethical, social and legal issues that may arise from the development and deployment of technologies, and act in accordance with the principles, responsibilities and guidelines related to decision-making, consultation, science communication and ethics education (PADCAS 2013). The Chinese academic sector’s understanding and practice of RRI are largely influenced by China’s opening up to the world and exchanges with international peers. Chinese scholars have actively introduced the concepts, theories and practical experiences of RRI in their exchanges with the international academic community. Starting from 2012, the Research Alliance on the Ethics of Science and Technology, which was formed by five Chinese technology universities and is known as 5TU, and the Research Centre on the Ethics of Science and Technology, which was formed by three Dutch technology universities and is now known as 4TU,2 have jointly hosted international symposiums on RRI on an annual basis (Yu 2013; Yan 2014). Scholars have used the concept of RRI to explore and experiment with the model and governance of science, technology and innovation in China. The Chinese Academy of Science and Technology for Development and research institutes in Germany, the 2

Originally known as 3TU (Delft University of Technology, Eindhoven University of Technology and the University of Twente), it was renamed 4TU in 2016, when Wageningen University and Research Centre joined.

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UK, the Netherlands and India have jointly conducted the Global Ethics of Science and Technology project, with the aim of exploring ways to incorporate the issue of ethics and social responsibility for S&T into the policy process (Ladikas et al. 2015).

12.4.3 The Business Sector The business sector is the most important driving force for technological innovation in China today. In 2013, 76.6% of China’s total R&D expenditure came from the business sector, far exceeding that from government-backed research institutes (15%) and universities (7.2%) (NBS-MoS-MoF 2014). In recent years, Chinese enterprises have attached higher importance to innovation and paid closer attention to corporate social responsibility (CSR), which has provided strong impetus for further promoting RRI in China. Over the years, Chinese enterprises’ understanding of CSR has gradually evolved. In the era of the planned economy, state-owned enterprises mainly produced according to state plans and administrative instructions. They were also responsible for meeting the daily needs of their employees, providing a classic example of the ‘business-run society’ model. The burden of their social functions weakened their ability to operate as basic economic units. From the beginning of reform and opening up to the 1990s, enterprises, which were eager to break away from the traditional planning system, cared for nothing but maximum profits. Most companies in that period focused only on their responsibilities to shareholders, ignoring or even evading governmental, social and environmental responsibilities (Li 2015). Since the 1990s, the economic order in the Chinese market has been improving, and the domestic market is increasingly connected with the international market. The concept and practice of CSR have been gradually introduced by multinational corporations through their management chains. More and more Chinese enterprises have since begun to release CSR reports, from one or two in 2000 to about 30 in 2006, and to nearly 2000 in 2013 (Editing team 2014). This shows that Chinese enterprises have already developed a certain awareness of their responsibilities to society. CSR has also been included in a series of policy and legal documents. The amendment to the Company Law of the People’s Republic of China, which entered into force on 1st January 2006, clearly stipulates that: when engaging in business activities, companies must abide by the laws and administrative regulations, observe social and business ethics, maintain honesty and integrity, accept government and public oversight and undertake social responsibilities. In June 2015, the General Administration of Quality Supervision, Inspection and Quarantine and the Standardization Administration of China jointly issued three national CSR standards—the Social responsibility guidelines (GB/T 36,000–2015), the Guidelines for the preparation of social responsibility reports (GB/T 36,001– 2015) and the Guidelines for the classification of social responsibility performance

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(GB/T 36,002–2015)—which entered into force on 1st January 2016, building a framework of CSR policies, laws and standards. There is a strong affinity between the concepts of CSR and RRI. The key aspects of CSR, including concerns for society and the environment, transparent and ethical behaviour, stakeholder engagement and normative perspectives, all overlap with the notion of RRI, which provides the basis for promoting and practising RRI in the Chinese business sector. Survey statistics also suggest that there is a good foundation for the application of RRI in China. For example, in the second national survey of S&T workers, when asked whether they agreed with the idea that ‘scientists shall be responsible for the bad things committed by other people with their inventions’, 64% of respondents in the business sector gave an affirmative answer, which was significantly higher than in research institutes (33%) and universities (54%). On the question of whether ‘the government should set strict limitations on the research activities of scientists to prevent problems’, 71% of respondents in the business sector agreed, which was again far higher than in research institutes (32%) and universities (48%) (STGSSTW 2010). To a certain extent, those results prove that S&T workers in the business sector have a clearer understanding of social responsibility for research and innovation. With a growing awareness of social responsibility, the business sector will become a leading force in promoting RRI in China. Researchers and entrepreneurs have an important role to play in mitigating innovation risks with RRI. As the key players in innovation activities, they must fully consider the social and ethical consequences of innovation in order to minimize the possible negative results. To that end, researchers should consciously abide by the principles of research ethics, and entrepreneurs should fully fulfil their social responsibilities. At the same time, they should communicate fully with other stakeholders, including government officials and the public. They must give authoritative explanations to address the public’s misconceptions and questions about the risks of S&T, dispel rumours and encourage the public to form a correct understanding of the development of new technologies and new industries. They must also heed the views and concerns of stakeholders and incorporate them into the design of innovation pathways through consultation to ensure the social and ethical acceptability of innovation and reduce its social risks.

12.4.4 The Government Strong government leadership and intervention are one of the hallmarks of Chinese society and an important driving force that has enabled China’s rapid economic development. However, after more than three decades of rapid development, the Chinese Government is facing an increasing number of social challenges. In the face of a series of social problems, such as environmental pollution, resource shortages and social injustice, the Communist Party and the government are seeing the limits of a growth-based approach to development. In recent years, new concepts, such as the

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scientific outlook on development and harmonious society, have been put forward, all aimed at shifting towards a more sustainable and inclusive model of development. The emphasis on social responsibility in research and innovation is notable in changes to S&T policies. In 2011, the Ministry of Science and Technology issued the Opinions on accelerating the development of science and technology for people’s livelihood. In 2012, the Ministry of Science and Technology and the Ministry of Finance jointly launched the Science and Technology for People’s Livelihood Initiative with the aim of making the benefits of S&T innovation accessible to the whole population (MST 2012). In 2016, the State Council issued the 13th Five-Year Plan for Science, Technology and Innovation, which clearly stated that efforts should be made to: advocate responsible research and innovation, improve research ethics, strengthen research ethics education, raise the research ethics awareness of science and technology workers, and remind the enterprises to pay attention to and undertake social responsibilities in technological innovation activities such as protecting the eco-environment and ensuring safety. (State Council 2016). As the government has gained more understanding of the risks associated with scientific research and the application of technologies as well as related ethical and social responsibilities, a number of policy measures aimed at promoting responsible research and innovation have been introduced, particularly in the fields of biomedicine and agricultural sciences. The State Council, the Ministry of Health and the Ministry of Science and Technology have issued relevant laws, guidelines and ethical review procedures to regulate GM crops (the Regulations on the safety management of agricultural GMOs issued by the State Council in 2001), human stem cell research (the Ethical guidelines for human embryonic stem cell research, jointly issued by the Ministry of Science and Technology and the Ministry of Health in 2003) and biomedical research involving humans (the Ethical review measures for biomedical research involving humans, issued by the Ministry of Health in 2007) (State Council 2001; MST-MoH 2003; MoH 2008). Recognizing the limitations of the top-down management model adopted by the government, policymakers have introduced the concept of ‘social governance’, seeking to further mobilize public participation in the management of social affairs. This new concept is already reflected in the country’s innovation policy. When formulating the Outline of the National Medium and Long-Term Science and Technology Development Plan in 2003, the government devised various forms and channels to encourage the public’s participation (Fan and Tong 2008). In 2008, in order to improve the public’s participation in the governance of GM food technologies, the Chinese Academy of Sciences and the Beijing Xicheng District Government organized a consensus-building meeting, creating a platform for open dialogue between the public and experts (RCEST 2008). The government plays an important role in innovation. As the investor of innovation resources, it takes on the responsibility for increasing strategic input in S&T development. As the manager of innovation activities, it should take a more flexible approach in the innovation management system. While exercising strict management,

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it should tolerate failures in innovation and encourage innovators to make bold explorations without fear of failure. As the defender of the innovation market, it should pay attention to the protection of the market mechanism. As the coordinator of the distribution of innovation benefits, it should uphold the rule of law and adopt proactive policies to ensure that the benefits of innovation are more widely shared among the public. The government should not only be brave enough to stir up vested interests and speak out for innovation but should also establish the coordination mechanism for the distribution of innovation gains, improve the rule of law and work to cushion the social impact of the innovation process, mitigate social resistance and improve the sustainability of innovation.

12.5 Challenges in Promoting Responsible Research and Innovation in China While social changes in recent years have created favourable conditions for the promotion of RRI in China, RRI still faces many serious challenges that limit its ability to address innovation risks in China.

12.5.1 How to Balance the Responsibility for and Efficiency of Innovation Today, innovation has already become the dominant discourse in China’s economic and social development. In the context of this ‘new normal’, decision-makers look to innovation not just as a new driver for development and but also as a solution to the economic and social problems caused by the traditional model of development. Against such a backdrop, what are the consequences of emphasizing ‘responsibility’ for innovation? Will innovation be overburdened by too much ‘responsibility’? There are still a considerable number of policymakers and scientists who insist that, at the current stage of China’s technological and social development, overemphasis on the responsibility for and risks of research and innovation may mislead policymakers, misinform the public, cause unnecessary panic and ultimately hinder the development of science, technology and innovation in China (Zhang and Zhao 2014). According to the results of a national survey on the research ethics awareness of Chinese S&T workers, 30.3% of respondents supported the argument that ‘emphasis on research ethics will limit the freedom of scientific research and the development of science’ (SSARES 2015). This shows that there are still a considerable number of people who have doubts about ethical responsibilities for research and innovation. The extent of social and ethical responsibility to be taken on by research and innovation is still a highly controversial issue in policy and scientific circles. Therefore, only with a better balance between responsibility and efficiency in innovation can RRI truly take

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root and make a real impact on China’s science, technology and innovation system, instead of being an empty slogan catering to the Western ideological trend.

12.5.2 How to Enhance Communication, Mutual Trust and Cooperation Among Different Actors Consultation and cooperation among the government, the scientific community, the public and industry are important conditions for the implementation of RRI. At present, the communication and interaction among various actors in China is still weak, and it is difficult to form a ‘synergy’ in RRI practice. For example, the lack of communication between the scientific community and the public is a problem long criticized by people, and scientists themselves also recognize this. In the second National Survey of Science and Technology Workers, 55.6% of respondents noted that the lack of communication between scientists and the public was a serious problem, while another 41.6% pointed to the problem of lack of collaboration between scientists and the business sector (STGSSTW 2010). In contrast, up to 76.3% of respondents in the public survey in 2009 said they did not know enough about the work of scientists (STPISTW 2009). The government and the business sector, which are the key players in R&D investment and innovation, also need to strengthen coordination, with a focus on their respective priorities. The government should play a bigger role in setting the right values and meeting public needs, while the business sector needs to find a balance between efficiency and social responsibility. In addition, the governance model requires various non-government actors to play a more active role in the making of science, technology and innovation decisions. However, currently, the government still plays a dominant role in China. Therefore, how the government can guide and establish an interactive consultation mechanism is both a challenge in the process of further deepening the reform of the S&T system and a prerequisite for the effective promotion of RRI in China.

12.5.3 How to Promote Public Participation in Science and Technology Governance Another major question is how to improve the level of public participation in S&T governance. At present, the Chinese public still faces a number of challenges in people’s participation in S&T governance, such as unclear objectives, incomplete mechanisms, inefficient procedures and insufficient awareness and capacity. To overcome those difficulties, the government needs to play an active role in promoting and guiding the development of relevant rules and regulations and in building an institutional environment that promotes public participation (Fan and Tong 2008). In the meantime, the scientific literacy of the Chinese public still needs to be improved.

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According to the 2010 Survey on the Scientific Literacy of Chinese Citizens, people with basic scientific literacy accounted for only 3.27% of China’s total population (Ren 2011). The low scientific literacy of the public has also constrained, to some extent, people’s ability to participate in S&T governance. In addition, China is a big country with a large population, and there are big gaps between people from different social classes, regions and ethnicities in economic development and education. In such a big and diverse country, promoting the public’s participation in innovation and S&T governance is indeed a very difficult task.

12.6 Summary The Chinese Government has put forward the strategy of ‘innovation-driven development’, elevating innovation to a key position in the national strategy. Therefore, effective management of the risks associated with innovation has become an increasingly important issue in promoting innovation, development and social governance in China. We need to be clear about the real purpose of innovation and development and think deeply about innovation’s social impact and value orientation. Innovation is sustainable only when it is recognized by society, accepted by the public and serves people’s well-being. This is the only way to avoid and mitigate innovation risks and achieve sustainable economic and social development. To achieve that goal, scientific communication is needed to create a better national environment for supporting innovation in various sectors. The concept of ‘responsible research and innovation’ has paid full attention to and taken into full account the public’s demands and the social consequences and values of science, technology and innovation. Therefore, study of the theory and practice of RRI will help increase the sustainability of technological innovation and social development in China and facilitate China’s participation in global exchanges and cooperation on S&T innovation and development. Some are concerned that, given the current stage of China’s economic and social development, overemphasis on the risks in and responsibilities for innovation may add unnecessary burden on innovation and slow its pace. However, the goal of responsible innovation is not to hit the brakes on the fast-moving car of innovation, but to use the steering wheel to guide innovation towards meeting people’s need for happier and better lives and achieving fuller, balanced and sustainable development. Acknowledgements Author Notes The chapter is adapted from two published papers: Zhao Yandong, Pay attention to innovation risk, promote sustainable innovation, China Social Science Review, 2019, no. 4; Zhao Yandong, Liao Miao, Responsible research and innovation in China, China Soft Science, 2017, no. 3.

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Zhang X (2015) Ethical arguments for suspending genetic editing of human embryos. Sci Technol Rev 13 May Zhao Y (2010) The development of nanotechnology requires philosophy and ethics. Chinese Social Sciences Today, 21 September

Yandong Zhao studied sociology in the Graduate School of the Chinese Academy of Social Science, Beijing, China, where he obtained his doctorate. He is currently a professor in the Department of Sociology, Renmin University of China. His research interests include the sociology of science, the sociological study of disasters and risks, the sociology of education, social stratification and mobility. He is experienced in organizing large-scale social surveys and has published more than 100 articles in academic journals. Miao Liao is an associate professor of the Department of Philosophy in Changsha University of Science and Technology (China). She was a postdoctoral researcher in the Chinese Academy of Science and Technology for Development (CASTED). She holds a PhD in the philosophy of science and technology and a BA in philosophy. She has been involved in several international projects on sociotechnical integration, the governance of biotechnology, the ethics of science and technology, and responsible research and innovation, funded by NSF-US, ESRC-UK and the EU Horizon 2020 programme. Her research interests are ethical, legal and social issues of emerging technologies, responsible research and innovation, and technology assessment

Chapter 13

Exploring Emerging Public Attitudes Towards Autonomous Vehicles Chris Tennant

Abstract Autonomous vehicles promise to introduce artificially intelligent physical agents into uncontrolled social spaces for the first time. Public attitudes suggest uncertainty about the technology, but existing research focuses too much on engineering public acceptance instead of engaging with public concerns. I suggest that autonomous vehicles are a test case of the relationship between the public and artificial intelligence technologies and argue for the importance of a deeper, more carefully theorized understanding of public responses. This chapter reports a series of surveys designed to contribute to that effort. Keywords Autonomous vehicles · Public perceptions · Technological optimism · Deficit model

13.1 Autonomous Vehicle Technology The exceptional excitement over autonomous vehicles (AVs) seen in the middle of the last decade may now have been tempered, but huge sums are still being invested in the technology.1 Companies such as Tesla, Waymo, GM’s Cruise and Baidu are already making conditional deployments limited either by relatively narrow geographies or by the need for driver supervision. AVs are artificially intelligent agents that will share social spaces with human road users: as such, they are in the vanguard of an expanding array of AI applications that we will share the world with. The technology is often presented as inevitable and monolithic, with the expectation that it will be as universal as the internal combustion engine. But there is no inevitability about 1

‘Uberworld: The world’s most valuable startup is leading the race to transform the future of transport’, The Economist, 3 September 2016; ‘Driverless cars are stuck in a jam’, The Economist, 10 October 2019, https://www.economist.com/leaders/2019/10/10/driverless-carsare-stuck-in-a-jam.

C. Tennant (B) Department of Psychological and Behavioural Science, London School of Economics and Political Science, London, UK e-mail: [email protected] © China Science and Technology Press 2021 B. Schiele et al. (eds.), Science Cultures in a Diverse World: Knowing, Sharing, Caring, https://doi.org/10.1007/978-981-16-5379-7_13

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the forms the technology will take, just as there was contingency in how automotive technology emerged in the early twentieth century (Norton 2008). The extent to which individual driverless vehicles are integrated into the wider transport system will vary in different societies, and there is likely to be a diversity of business models across the world. Furthermore, the challenges now experienced in bringing the technology to maturity are likely to elicit diverse responses in different jurisdictions. How the public responds to AV technology will shape the technology’s emergence and set the template for the introduction of further AI applications (Tennant et al. 2019). At the moment, the public is uncertain about AVs, which some promoters take as flagging the need for public education, but effective engagement with the public depends upon both understanding and respecting people’s attitudes to such technologies.

13.2 Existing Research into Attitudes Towards Autonomous Vehicles There is an extensive literature on public attitudes to science and technology. In fact, from nuclear energy to genetically modified foods (Bauer 2015), from geneedited embryos (Gaskell et al. 2017) to neuroscience (O’Connor and Joffe 2013), public attitudes towards any technology with social impact have received attention. Frequently, the motivation behind such research is to encourage the acceptance of new technologies. AV technology is no different. A wide range of studies have explored public attitudes to AVs, and many of them have identified variables antecedent to acceptance of the technology (Becker and Axhausen 2017; Gkartzonikas and Gkritza 2019). How does the public view AV technology? Although some literature reviews have concluded that public attitudes are broadly positive (Gkartzonikas and Gkritza 2019) colleagues and I have carried out a review of attitude surveys in English languageacademic journals and in British newspapers (to January 2018). There we found a divergence of views, as well as a wide variation in survey methodologies (Tennant et al. 2019). Surveys that asked broad questions, such as about the respondents’ ‘general opinion’ about AVs, often found positive views (for example, König and Neumayr 2017; Liljamo et al. 2018), while others that asked more concrete questions about how ‘comfortable’ respondents would feel about using an AV tended to find more negative views (European Commission 2015, 2017). It was noticeable, too, that many non-academic surveys reported in the British press also found respondents expressing negative views (for example, Continental 2017; YouGov and Smith 2016). There is also a clear difference between views in the West and in Asia. People from developed Western countries express more negative views about AVs than respondents in many Asian countries (Schoettle and Sivak 2014; TÜV Rheinland 2018). An important task in future research will be to identify the factors underlying those quite substantial differences.

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What does the survey data tell us? It is common to argue that people have not yet experienced driverless technology, and until they do their opinions do not tell us much about how they will feel about the technology when they have (HLSTSC 2016:8; Sharples et al. 2016). Yet this ignores the fact that how people imagine future technology shapes how they process new information about such novel objects. People are likely to fit their understanding of AVs into their existing experience, relating it to other new technologies, or to their ideas about mobility and, more specifically, driving (Tennant et al. 2019). For promoters of a technology, it becomes important to shape those expectations, and many seek to ‘educate’ the public about the benefits of AV technology (see, for example, Sanbonmatsu et al. 2018), continuing a long tradition of treating the publics as ignorant and public resistance to new technology as born out of a deficit of knowledge (Sturgis and Allum 2004). An alternative approach reverses the roles, allowing public responses to educate technology developers as to how best to collaborate, or engage, with the publics in socially responsible innovation (Stilgoe et al. 2013; Stirling 2008). But much AV attitude research draws on the marketing paradigm of attitude research established by Ajzen and Fishbein (1973), seeking to understand the drivers of respondents’ willingness to use or willingness to purchase AVs (for example, Daziano et al. 2017; Kyriakidis et al. 2015).

13.3 A Complementary Approach My colleagues and I developed a series of surveys motivated by the desire to take a more comprehensive view of the road as a complex system rather than focusing on the view through the windscreen of the AV and the attitudes of potential users of AVs. In particular, we consider it to be a mistake to expect AVs to follow a Rogerian technology adoption path (Rogers 1983). The traditional Rogerian path sees early adopters of the technology leading the way, and when others observe some of the benefits enjoyed by those leaders they follow. With AVs, the introduction of the technology will be more complex. Many of the benefits require the penetration of the vehicle fleet by autonomous vehicles to be widespread (Bansal and Kockelman 2017): in the early years, AVs will need the cooperation of non-users to navigate the road successfully or they will struggle to emerge from narrowly defined protected areas (what developers call ‘operational design domains’). As Bansal and Kockelman (2017) argue, regulation will be important in facilitating the emergence of the technology. Again, the support of non-users will be essential to the success of regulatory changes.

13.4 A Series of Surveys Our first survey, of respondents from 13 European countries, looked at how drivers think about the road as a social space and how they interact with their fellow road

256 Table 13.1 Comfort with the prospect of autonomous vehicles, 13 European countries, 2015 (n = 9,012)

C. Tennant How would you feel?

Driving alongside (%)

Riding as passenger (%)

Totally comfortable

8

7

Quite comfortable

24

21

Not very comfortable

33

33

Not at all comfortable

21

25

Don’t know

14

14

users (Tennant et al. 2015). Against that background, we also asked our respondents whether they were comfortable with the idea of AVs: not just the prospect of using or riding as a passenger in an AV but also the prospect of sharing the road and driving alongside one. More respondents were uncomfortable than comfortable with that prospect (Table 13.1). Our subsequent research has concentrated on attitudes towards AVs rather than the road as a social space, but we have nevertheless sought to explore how survey respondents imagine interacting with AVs when they encounter them on the road. In particular, we sought to explore whether the slightly greater discomfort with riding in an AV, as opposed simply to driving alongside one, reveals anything about people’s attitudes towards the technology. Since our initial survey in 2015, we have conducted three further survey waves, in 2016, 2017 and 2018/19, progressively refining the question set to understand better attitudes towards this novel technology.2 In 2016, the survey was carried out in the UK and 10 European Union countries. Details of the methods used in the 2016 survey are provided elsewhere (Tennant et al. 2019). Methods used in subsequent surveys largely replicated that approach but with some refinement of survey items. In 2017 and 2018/19, the survey was carried out in the UK and the US. In all the surveys, we again asked whether respondents were comfortable with the prospect of using or riding in an AV, and whether they were comfortable with the prospect of driving alongside AVs. Responses were measured on a 7-point scale from ‘totally uncomfortable’ to ‘totally comfortable’, which meant respondents could select a middle (‘neither’) position. There was an additional ‘Don’t know’ option. The results are summarized in Table 13.2. Once again, more respondents expressed discomfort than comfort, and typically a majority described themselves as uncomfortable with the prospect of using an AV (with the exception of the EU respondents, many more of whom selected the neutral 2

The surveys conducted in 2015 and 2016 were part of a consultancy project for Goodyear Tyre and Rubber Corporation: full details of this are provided in Tennant et al. (2016, 2019). Subsequent surveys were funded from departmental funds of the researchers at London School of Economics and City, University of London.

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Table 13.2 Comfort with the prospect of autonomous vehicles, series of surveys

‘Riding in’ as a passenger

UK 2016

UK 2017

UK 2018/19

EU 10 2016

US 2017

US 2018/19

Comfortable

25%

32%

32%

27%

28%

29%

‘Neither’

14%

11%

14%

20%

16%

16%

Uncomfortable

55%

53%

50%

43%

51%

51%

Don’t know

6%

4%

4%

11%

5%

4%

1.450

780

1.447

10.377

2.394

1.242

28%

33%

36%

30%

33%

30%

n ‘Driving alongside’

n

Comfortable ‘Neither’

13%

14%

14%

22%

20%

21%

Uncomfortable

55%

49%

46%

39%

43%

45%

Don’t know

4%

4%

4%

9%

5%

4%

1.450

774

1.447

10.377

2.424

1.242

Mean scores for scale points 1 ‘Totally comfortable’ to 7 ‘Totally uncomfortable’; ‘Don’t know excluded ‘Riding in’

3.27

3.50

3.55

3.56

3.48

3.47

‘Driving alongside’

3.41

3.98

4.03

3.74

4.07

3.97

or ‘don’t know’ options). However, discomfort about driving alongside AVs was not as strong: the mean scores reveal that people do not feel as strongly about this issue, as fewer people described themselves as ‘totally’ or ‘very’ uncomfortable with driving alongside compared to using an AV. Instead, although more described themselves as uncomfortable than comfortable, most of those said they were ‘quite’ rather than ‘totally’ or ‘very’ uncomfortable. Local contextual factors are likely to affect the comparability of survey results across time and place. Nevertheless, our results suggest that the shared lack of experience of the technology, together with broadly similar levels of general support for new technology in the Western countries surveyed, contributes to the fairly consistent picture presented above. We note again that surveys of attitudes in East Asia express more favourable attitudes towards the technology.

13.5 Stated Reasons for Comfort with AVs Our surveys include a number of questions addressing more specific ideas about AVs. We frame those by asking respondents to think about their reasons for their level of comfort and suggesting a range of possible considerations in the form of statements that they may agree or disagree with. The questions are asked both about comfort with driving alongside AVs, and separately about comfort with riding in an AV. Table 13.3 provides some examples.

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Table 13.3 Reasons for comfort with the prospect of autonomous vehicles, US survey, 2017 Strongly disagree

Disagree

Neither agree nor disagree

Agree

Strongly agree

Don’t know

Mean

Mean

US (%)

US (%)

US (%)

US (%)

US (%)

US (%)

US

UK

–

–

–

–

–

–

–

–

As a point of 2.1 principle, humans should be in control of their vehicles at all times

8.0

24.9

33.3

30.4

1.4

3.83

3.77

Machines 4.4 don’t have the common sense needed to interact with human drivers

10.7

25.8

33.0

23.4

2.8

3.62

3.65

Reasons for comfort with riding in

–

–

–

–

–

–

–

–

I would feel uncomfortable if I wasn’t in control of my car

3.5

9.4

19.1

36.8

29.3

1.8

3.81

3.82

I’d like to be able to forget about the driving sometimes

11.6%

16.0%

24.5%

32.7%

13.7%

1.5%

3.21

3.01

2,728

738

Reasons for comfort with driving alongside

n (varies slightly for each question)

We can combine the responses to these questions to create an overall ‘perception’ of AVs scale score: for 2017 we used a 14-item scale (see appendix for items). Repeated measurement of this scale score will enable researchers to track sentiment towards AVs and more particularly to track how changes in specific issues may contribute to changes in sentiment. Further, an ‘index’ instrument of this kind would enable deeper interpretation of differences in sentiment between different countries and different demographics. At the moment, concerns about AV reliability and reluctance to give up control of the wheel contribute most to our measure of perceptions of AVs. By contrast, respondents tend to place less store by the promised benefits of the technology. However, benefits such as the opportunity to engage in

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other activities if relieved of the driving task, or the promise of reduced congestion, may start to become appreciated when the technology can actually be used, and that may contribute to a change in overall sentiment towards AVs.

13.6 Correlates of Comfort with, or Sentiment Towards, AVs Correlates are often treated as predictors of attitudes towards, and more specifically propensity to use or buy, new technological objects. Given the interest in predicting the acceptance of AVs, candidate factors have proliferated in the literature. Becker and Axhausen (2017) list 24 from the literature; Gkartzonikas and Gritza ( 2019) summarize a range of factors from 43 studies into nine categories. Our own surveys suggest that demographic variables play only a modest role, with slightly greater discomfort among older respondents and women. Attitudes towards technology more generally play a key role, and we created a measure of technological optimism based on a collection of statements. Our measure of technological optimism in the 2017 survey comprised 10 items (see appendix for full list). They included, for example, the statements listed in Table 13.4 (percentage frequencies are provided for the US respondents, and the mean response on a scale of 1−5 for both US and UK respondents). Our UK correspondents’ technological optimism score correlated with their perceptions of AVs score with a positive coefficient of 0.472 (p < 0.01), and similar correlations can be found in each of the six surveys in Table 13.2. Attitudes towards driving also predict attitudes towards AVs, but less strongly. Enjoyment of driving and what we call ‘driving sociability’ both correlate negatively.

13.7 Driving Sociability Driving is governed not only by road regulations but also by unwritten rules of cooperation with other road users. These function in much the same way as situational scripts (Abelson 1981). Common sense is required to know when to move to the edge of or even off the road if possible (breaking the formal rules) in order to let another vehicle pass. Different drivers approach the task of driving differently. Some consider it to be a cooperative task in which all road users need to help each other progress, while others tend to see the road in part as a combat zone, where you need to be forceful—the other driver should move to the edge or even off the road if possible to make way for you, but not the other way round. Those latter drivers’ experience of the road is often shaped by the sense that others are being aggressive towards them rather than by some powerful road-hogging instincts of their own. As noted above, respondents who tend to regard driving more as a cooperative task also tended to

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Table 13.4 Technological optimism scale questions, US survey 2017 Strongly disagree

Disagree

Neither agree nor disagree

Agree

Strongly agree

Don’t know

Mean

Mean

US (%)

US (%)

US (%)

US (%)

US (%)

US (%)

US

UK

4.5

11.6

25.7

42.4

15.0

0.8

3.54

3.58

Machines are 3.2 taking over some of the roles that humans should have

8.8

23.0

41.3

22.9

0.9

3.74

3.78

Science and technology make our way of life change too fast

18.3

24.2

31.9

17.4

0.8

3.36

3.35

3.652

1.031

We have no option but to adapt to the new technologies that are coming

n

7.4

hold a slightly more negative perception of AVs. We established a 12-item scale to measure ‘driving sociability’ (items in appendix). We asked our respondents to imagine interacting on the road with AVs as opposed to other human drivers. Specifically, we showed them diagrams of typical interactions on the road, such as a situation where ‘you’, the driver, are stuck behind an obstruction, and you need help from the oncoming traffic to help you get around the obstruction. We can present this situation in a 2 × 2 conditions format: the respondent is asked to imagine themselves in both situations: (a) blocked by the truck or (b) in the oncoming traffic with the opportunity to slow down and allow a blocked vehicle out, as well as (c) with the oncoming car (blocked, or moving) either (c) a regular human-driven vehicle or (d) an AV. Figure 13.1 shows (a) and (d). It is difficult to get good data from online survey questions such as this (it is hard to be sure how respondents are reading rich visual stimuli). With that caveat, what is interesting is that our respondents default to assuming that they will interact with AVs as they do with human-driven cars. We speculate that, without any direct experience of sharing the road with AVs, people simply default to what they know. Nevertheless, we also find that respondents whom we measured as more cooperative on our driving sociability scale were more likely to say they would help an AV that was obstructed than were more combative drivers: this is despite the fact that more

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Fig. 13.1 A scenario used in our survey

cooperative drivers among our respondents had less favourable perceptions of AVs. In fact, it may be that more combative drivers will seek to take advantage of AVs’ cautious driving style (Titcomb 2016). Indeed, participants in focus groups that we ran did suggest they would do exactly that; one participant had no doubt that in the situation depicted in Fig. 13.1 they would nip round the truck, confident that an oncoming AV would slow down, whereas they might be more hesitant with an oncoming human-driven car.

13.8 Conclusion Our survey data identifies similar attitudes towards AVs across various Western countries. Sources of information are scant, leaving the public to rely on industry hype (Stilgoe 2019) offering generalized utopian visions (Hildebrand 2019). Diversity in responses may emerge when the technology actually confronts local road cultures.

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We intend these surveys to be part of an ongoing series. People’s expectations of the technology will change, influenced by product launches as well as negative news events such as AV crashes. There is a wide recognition that widespread deployment of the technology is much further off than first thought. This provides the time needed to identify properly and engage with public hopes and concerns in order to deploy the technology to achieve societal goals rather than participate in a race to deploy AVs as if that were a goal in itself. Acknowledgements This research was carried out by the author and Sally Stares at City, University of London. Dr Bradley Franks, Dr Matt Hall and Professor Martin Bauer of the London School of Economics also participated in earlier stages of the research. Dr Susan Howard provided advice and assistance to the main researchers throughout the programme.

Appendix This appendix lists survey items used to build the main scales mentioned in this chapter, provided by replicating the relevant questions (for example, Q13) from the 2017 survey. Perceptions of AV (PAV) scale The Perceptions of AV (PAV) scale comprises items in Q13 and Q16. Those items used in the scale are highlighted in italics, and (R) denotes where we reversed the scoring direction for the item, so that higher values in all cases indicate more positive attitudes towards AVs. ‘Please think about your reasons for the choice you made in answering the previous question about driving alongside autonomous (driverless) cars and respond to the next set of questions.’ Q13. ‘Thinking about your choice in the previous question, how much do you agree or disagree with the following statements?’ Response options: Strongly agree, Agree, Neither agree nor disagree, Disagree, Strongly disagree, Don’t know. • Most accidents are caused by human error so autonomous vehicles would be safer • I wouldn’t mind whether I was driving alongside human drivers or autonomous vehicles • I don’t know enough about how autonomous vehicles work • Autonomous cars could malfunction (R) • As a point of principle, humans should be in control of their vehicles at all times (R) • I feel that autonomous cars would pose more risk to me than other drivers pose • Autonomous cars could greatly reduce congestion • I’d be scared seeing an autonomous car with no driver inside • I wouldn’t feel in control with autonomous cars on the road around

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• Autonomous cars would behave more predictably than human drivers • Machines don’t have the common sense needed to interact with human drivers (R) • Machines don’t have emotions so they might be better drivers than humans • I wouldn’t mind as long as all cars were autonomous but mixing human drivers and autonomous vehicles will not work • It will become easier to drive my own car as more of the cars around me become autonomous Q16 ‘Please think about your reasons for the choice you made in answering the previous question about using an autonomous (driverless) car and respond to the next set of questions. Response options: Strongly agree, Agree, Neither agree nor disagree, Disagree, Strongly disagree, Don’t know. • • • • • • • • • • •

Most accidents are caused by human error so autonomous vehicles would be safer Autonomous cars could malfunction (R) I would miss the enjoyment of driving (R) I feel that being driven by an autonomous car would be riskier than driving myself I would feel uncomfortable if I wasn’t in control of my car (R) I would take the opportunity to do other things while the autonomous car takes care of the driving It would make no difference to me whether I was in control of the car or not Riding in an autonomous car would be easier than driving myself I don’t know enough about how autonomous cars work I wouldn’t mind as long as the autonomous car did everything and didn’t expect me to take back control sometimes I’d like to be able to forget about the driving sometimes

Technological optimism scale The technological optimism scale comprises items in Q8. Those items used in the scale are highlighted in italics, and (R) denotes where we reversed the scoring direction for the item, so that higher values in all cases indicate more favourable attitudes towards technology. Q8 ‘To what extent do you agree or disagree with the following statements?’ Response options: Strongly agree, Agree, Neither agree nor disagree, Strongly disagree, Don’t know. • • • •

Science and technology make our way of life change too fast (R) I’m not interested in new technologies (R) We have no option but to trust those governing science Science and technology are making our lives healthier, easier and more comfortable • I enjoy making use of the latest technological products and services when I have the opportunity • The idea of artificially intelligent robots is scary (R)

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• If I’m in a plane I need to know the pilot is there to take over from the autopilot if necessary (R) • New technologies are all about making profits rather than making people’s lives better (R) • I am worried about where all this technology is leading (R) • We have no option but to adapt to the new technologies that are coming • Machines are taking over some of the roles that humans should have (R) • The more that we can use technology to control the natural world, the better • When my safety is involved I’m happy to rely on technology Driving sociability scale The driving sociability scale comprises items in Q10 and Q11. Those items used in the scale are highlighted in italics, and (R) denotes where we reversed the scoring direction for the item, so that higher values in all cases indicate more sociable orientations towards driving. Q10 ‘Please tell us to what extent you agree or disagree with the following statements about driving in general.’ Response options: Strongly agree, Agree, Neither agree nor disagree, Strongly disagree, Don’t know. • • • •

You need to be able to communicate with other road users when you are driving The other motor vehicles all have the same right to be on the road As drivers, we all need to help keep the traffic flowing Being able to make eye contact with other drivers is an important element of driving • Each driver has to prioritise their own progress over other people’s (R) • As drivers we all need to cooperate with the other drivers on the road Q11 ‘And now, please give us your opinion on the following statements, by telling us for each one how often it applies to you. Response options: Always, Usually, Sometimes, Occasionally, Never, Don’t know. • I think of other cars as just traffic rather than thinking about the drivers inside them • I find that other drivers try to bully me on the road (R) • I don’t mind being at the back of a queue of traffic, because we all get there at the end • When I am in a queue of traffic that is merging with another I just force my way in (R) • When another driver has made way for me I feel it’s my turn to make way for someone else later on • If another driver impedes me I will impede another driver later on (R) • When queues of traffic are merging drivers should take turns • It’s ok for someone to push into a queue if they are in a hurry (R) • If it slows me down I won’t help other drivers (R)

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References Abelson RP (1981) Psychological status of the script concept. Am Psychol 36(7):715–729 Ajzen I, Fishbein M (1973) Attitudinal and normative variables as predictors of specific behaviors. J Pers Soc Psychol 27(1):41–57 Bansal P, Kockelman KM (2017) Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies. Transp Res Part a: Policy and Practice 95:49–63. https://doi. org/10.1016/j.tra.2016.10.013 Bauer M (2015) Atoms, bytes and genes: public resistance and techno-scientific responses. Routledge, New York Becker F, Axhausen KW (2017) Literature review on surveys investigating the acceptance of automated vehicles. Transportation 44(6):1293–1306. https://doi.org/10.1007/s11116-0179808-9 Continental (2017) Driverless cars—the road to nowhere?, https://www.continental-tyres.co.uk/car/ media-services/newsroom/driverless-cars-road-to-nowhere Daziano RA, Sarrias M, Leard B (2017) Are consumers willing to pay to let cars drive for them? analyzing response to autonomous vehicles. Transp Res Part c: Emerg Technol 78:150–164. https://doi.org/10.1016/j.trc.2017.03.003 European Commission (2015) Special Eurobarometer 427: Autonomous systems. http://ec.europa. eu/ommfrontoffice/publicopinion/archives/ebs/ebs_427_en.pdf European Commission (2017) Special Eurobarometer 460: Attitudes towards the impact of digitisation and automation on daily life. http://ec.europa.eu/commfrontoffice/publicopinion/index. cfm/Survey/getSurveyDetail/instruments/SPECIAL/surveyKy/2160 Gaskell G, Bard I, Allansdottir A, da Cunha RV, Eduard P, Hampel J, Zwart H (2017) Public views on gene editing and its uses. Nat Biotechnol 35(11):1021–1023. https://doi.org/10.1038/nbt.3958 Gkartzonikas C, Gkritza K (2019) What have we learned? a review of stated preference and choice studies on autonomous vehicles. Transp Res Part c: Emerg Technol 98:323–337. https://doi.org/ 10.1016/j.trc.2018.12.003 Hildebrand JM (2019) On self-driving cars as a technological sublime. Techné: Res Philosop Technol 23(2):153–173 HLSTSC (House of Lords Science and Technology Select Committee) (2016) Oral evidence to the autonomous vehicles inquiry, session 1, UK Parliament. http://data.parliament.uk/writtenevide nce/ommitteeevidence.svc/evidencedocument/science-and-technology-committee-lords/autono mous-vehicles/oral/42659.pdf König M, Neumayr L (2017) Users’ resistance towards radical innovations: the case of the selfdriving car. Transp Res f: Traffic Psychol Behav 44:42–52. https://doi.org/10.1016/j.trf.2016. 10.013 Kyriakidis M, Happee R, de Winter JCF (2015) Public opinion on automated driving: results of an international questionnaire among 5000 respondents. Transp Res f: Traffic Psychol Behav 32:127–140. https://doi.org/10.1016/j.trf.2015.04.014 Liljamo T, Liimatainen H, Pöllänen M (2018) Attitudes and concerns on automated vehicles. Transp Res f: Traffic Psychol Behav 59:24–44. https://doi.org/10.1016/j.trf.2018.08.010 Norton PD (2008) Fighting traffic: the dawn of the motor age in the American city. MIT Press, Cambridge, Massachusetts O’Connor C, Joffe H (2013) How has neuroscience affected lay understandings of personhood? A review of the evidence. Public Underst Sci 22(3):254–268 Rogers EM (1983) Diffusion of innovations, 3rd edn. Free Press, Collier Macmillan, New York and London Sanbonmatsu DM, Strayer DL, Yu Z, Biondi F, Cooper JM (2018) Cognitive underpinnings of beliefs and confidence in beliefs about fully automated vehicles. Transp Res f: Traffic Psychol Behav 55:114–122. https://doi.org/10.1016/j.trf.2018.02.029

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Schoettle B, Sivak M (2014) Public opinion about self-driving vehicles in China, India, Japan, the US, the UK and Australia. Transport Research Institute, University of Michigan. https://deepblue. lib.umich.edu/itstream/handle/2027.42/109433/103139.pdf?sequence=1 Sharples S, Moore T, Moran H, Burnett G, Meng X, Galea M, McAuley D (2016) Written evidence to the House of Lords Science and Technology Committee, AUV0049, UK Parliament. http://data.parliament.uk/rittenevidence/committeeevidence.svc/evidencedocu ment/science-and-technology-committee-lords/autonomous-vehicles/written/41871.html Stilgoe J (2019) Who’s driving? new technologies and the collaborative state. Palgrave, in press Stilgoe J, Owen R, Macnaghten P (2013) Developing a framework for responsible innovation. Res Policy 42(9):1568–1580. https://doi.org/10.1016/j.respol.2013.05.008 Stirling A (2008) ‘Opening up’ and ‘closing down’: power, participation, and pluralism in the social appraisal of technology. Sci Technol Human Values 33(2):262–294. http://www.jstor.org/stable/ 29734034 Sturgis P, Allum N (2004) Science in society: re-evaluating the deficit model of public attitudes. Public Underst Sci 13:55–74 Tennant C, Howard S, Franks B, Bauer MW, Stares S (2016) Autonomous vehicles— negotiating a place on the road: a study on how drivers feel about interacting with autonomous vehicles on the road. London School of Economics and Political Science. https://www.lse.ac.uk/business-and-consultancy/consulting/consulting-reports/autono mous-vehicles-negotiating-a-place-on-the-road Tennant C, Stares S, Howard S (2019) Public discomfort at the prospect of autonomous vehicles: building on previous surveys to measure attitudes in 11 countries. Transp Res f: Traffic Psychol Behav 64:98–118. https://doi.org/10.1016/j.trf.2019.04.017 Tennant C, Stares S, Howard S, Hall M, Franks B, Bauer M (2015) The ripple effect of drivers’ behaviour on the road. Report submitted by LSE Enterprise to Goodyear. London School of Economics and Political Science. http://www.lse.ac.uk/business-and-consultancy/consulting/con sulting-reports/the-ripple-effect-of-drivers-behaviour-on-the-road Titcomb J (2016) Driverless cars to be unmarked to stop motorists bullying them. The Telegraph, 31 October TÜV Rheinland (2018) TÜV Rheinland releases wide-ranging study on global consumer perception of autonomous vehicle safety. News release, 15 February. https://insights.tuv.com/blog/t%C3% BCv-rheinland-releases-wide-ranging-study-on-global-consumer-perception-of-autonomousvehicle-safety You G, Smith M (2016) Majority of public would be scared to take a ride in a driverless car. YouGov, 26 August. https://yougov.co.uk/topics/lifestyle/articles-reports/2016/08/26/majoritypublic-would-be-scared-take-ride-driverle

Chris Tennant worked for 25 years in the financial services industry in London before studying for a doctorate at the London School of Economics. He continues to be a Visiting Fellow at LSE’s Department of Psychological and Behavioural Science. His research interests are the interplay between moral values and rational explanation, media representation of contested science, trust and accountability. In 2020, he joined the Driverless Futures? project at UCL’s Science and Technology Studies Department, researching the introduction of autonomous vehicle technology and the different policy options for its governance.

Part IV

Professions and Institutions

Chapter 14

The Evolution of Scientific, Technical and Industrial Culture in France Samuel Cordier

Abstract To better understand and know this period, to analyse the place of scientific culture in all the regions that make up France, and to evoke the factors that shape the current landscape of scientific and technical culture, I propose to put the evolution of French scientific, technical and industrial culture into a historical perspective. Keywords France · Territories · Scientific culture · Audiences · Commitment · Participatory

14.1 Historical Elements The history of scientific culture, over the past 60 years, which has come both from actions derived from associative structures and public policies, proves that actors of scientific culture are constantly innovating to conquer ‘distant’ audiences, both geographically and sociologically, in places of scientific culture. Since the 1960s, a network of actors, notably associations such as Planet Sciences or from the world of popular education, has been developing throughout France. The 1970s marked the beginning of a period in which initiatives to bring audiences closer to knowledge-producing centres were born. These changes are the result of both questioning by researchers, including physicists, about their place in society and about economic and political changes. As the idea of a technical and industrial scientific culture materializes, associations are investing in rural, intermediate and urban areas, university laboratories are opening their doors, and researchers are turning to the public. In 1973, at an international congress on particle physics organized in the south of France (in Aix-en-Provence), physicist Michel Crozon (1932–2008) and a Swiss colleague decided to present physical general and nuclear experiments in the street. ‘This approach was based on the just awareness by researchers that we had to inform (and listen to!) the public, especially those who do not attend museums, and the S. Cordier (B) Heritage curator, Director of the zoological museum of Strasbourg, Strasbourg, France e-mail: [email protected] © China Science and Technology Press 2021 B. Schiele et al. (eds.), Science Cultures in a Diverse World: Knowing, Sharing, Caring, https://doi.org/10.1007/978-981-16-5379-7_14

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need to justify themselves on the legitimacy of unfinished scientific research (events involved almost exclusively researchers in the basic sciences)’ (Guyon and Maitte 2008). The following year, in 1974, the Scientific and Cultural Action Liaison Group was founded.1 Its structure was designed to support cultural actions in the field of science. As a result of this reflection, universities and public research institutions would develop actions to reach audiences in the regions. At the end of the 1970s, ‘science shops’—places of mediation in which those structures received concrete requests from civil society—opened their doors in the universities of Grenoble, Lyon, Paris, Strasbourg, and then, in the early 1980s, in Lille, Marseille and Orsay. The creation of places dedicated to scientific culture in the regions is closely linked to the entry of science into cultural spaces and the emergence of cultural centres; ‘In accordance with André Malraux’s project, cultural centres are open to multi-purpose cultural projects that, more often than not, take into account the scientific theme’ (Guyon and Maitte 2008). In the early 1980s, political changes had a direct impact on the world of technical and industrial scientific culture. On the one hand, Defferre laws contributed to decentralization.2 On the other hand, the Minister of Research and Technology, Jean-Pierre Chevènement, favoured the development of a regional network of scientific culture ‘that foreshadows the current network of centres of scientific culture and complements the City of Science and Industry under construction’ (Guyon and Maitte 2008). Research and technology assemblies, organized from 1981, were allowed to formulate projects—the centres for scientific, technical and industrial culture— which would ‘provide specialized spaces (exhibitions, exploratory, documentation, press rooms), places of debate and confrontation, planetariums …) in order to adapt to the diversity of citizens’ motivations’ (Chevènement 1982: 204). In 1984, Jean-Marc Lévy-Leblond proposed a definition of scientific and technical culture in which the relations between scientific culture and relations with the public in places far from the centre of knowledge production appear clearly stated: The objectives of scientific and technical culture are to cultivate science and technology, to encourage their relocation, to break down the territories, to spring from all areas of activity and social investment: politics, economics, research, training, social, ethics …, renewing the approaches of society and the world. To achieve these goals, we must use all the supports, the living and sensitive forces: the school, the street, the factory, the laboratory, the office, the socio-cultural and cultural facilities, the clubs, the youth associations … (Levy-Leblond 1984). Since 2011, projects supported by the Office of the General Commissioner for Future Investments for the development of scientific and technical culture and equal opportunities have fostered the emergence of innovative projects, some of which 1

Science & Société, http://science-societefr/tag/glacs/. Gaston Defferre (1910–1986) was a French politician, former Mayor of Marseille, Minister of Spatial Planning, and Minister of the Interior and of Decentralization. He was one of the main architects of the 1982 decentralization (the law bearing his name), which granted more responsibilities to regional authorities across France. The 1980s were also the decade of the creation of Scientific, Technological and Industrial Culture Centres in each region.

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are closely linked to the territories. Among the winning projects, several aims to implement actions throughout the country, some to develop inter-regional actions and others to strengthen regional or even local structures at the level of a city or agglomeration, in terms of scientific culture. Among the regional projects, the Building Together a Region of Knowledge (Cerco) project aims to build, at the level of a region, Lorraine, a beautiful territorial network by bringing together most of the actors of the Hubert Curien project. The Innovation for Mediation in the Territories (Inmédiats) project, the objective of which is to ‘reduce social, cultural and geographical distances by offering innovative ways of accessing scientific content’, brings together actors scattered throughout the country and relies on digital technologies (Bardon 2012). Inmédiats actions include FabLabs, Living Labs and experimentation and evaluation of uses related to the development of immersive virtual worlds or ‘serious’ games. Finally, innovative initiatives returned to museums at the beginning of the twentyfirst century. Indeed, participatory science programmes link the production of knowledge, the public and the territories. In their favourite fields—the natural sciences— several museums offer their audiences the opportunity to contribute to research by using rigorous protocols to discover the biodiversity that surrounds them. The originality of this approach is that it concerns both urban areas and rural areas.

14.2 Changes in the Legislative Framework in the Field of Scientific Culture Over the past five years, the passing of laws and decrees and the publication of strategic documents have accompanied the evolution of structures dedicated to scientific culture. While the law of 4th January 2002, which sets out the conditions for the government’s approval of an institution, is still in force, several developments should be noted. Act III of Decentralization (Act no. 2013-660 of 22nd July 2013 on higher education and research), now integrates scientific, technical and industrial culture into the fields of research and higher education. The ‘spreading of humanist culture, notably through the development of the humanities and social sciences, and scientific, technical and industrial culture’ (Article 7), is now part of the mission of higher education, which must ‘promote the interaction between science and society’ (Article 6).3 The Act also moves the coordination and funding of scientific culture’s actions to the regions, each of which ‘coordinates, subject to the Government’s missions and as part of the national research strategy, territorial initiatives aimed at developing and

3

LOI no. 2013–660 du 22 juillet 2013 relative à l’enseignement supérieur et à la recherche, https://www.legifrance.gouv.fr/affichTexte.do;jsessionid=3452B807A1F0B55FCCEB4 1CE5ED2F4A5.tpdjo09v_3?cidTexte=JORFTEXT000027735009categorieLien=id.

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using technical and industrial scientific culture, especially among young people’, and contributes to their funding. In March 2017, the report of the Museums of the 21st Century mission was delivered to the Minister of Culture.4 The aim was to define the issues that animate these cultural actors and to draw up a road map that could mobilize the entire network of museums in France (both national and regional). The main objective was to answer the question ‘What museum do we want for tomorrow?’ It appears that the museum must finally be truly democratized by opening up to all cultures and environments and evolving to become an ever more lively and friendly place. In practical terms, this means two things: • The focus must be on universal accessibility (opening hours, rates, ease of access for all, especially people with disabilities) and on hospitality to improve the visitor experience, especially for families through the expansion of spaces dedicated to children. • Museography needs to be redesigned. Museum mediation must be restored, first with a decisive place attributed to the presence in the rooms but also giving access to the backstage of museums, then through the desire to better exploit online resources. In March 2017, a national strategy for technical and industrial scientific culture was presented to the Minister of Culture and the Secretary of State for Higher Education and Research5 : • The strategy is based on four government priorities: gender equality; climate change and sustainable development; Europe; and the history of science and technology. • The strategy is based on four government priorities: the implementation and recognition of the main players (digital; knowledge and uses; and democratic debate and support for public policy); a shared scientific approach within our society; technical and industrial culture; and innovation.

14.3 ‘Thumbelina’ The past five years have also been marked by economic changes. Many structures have had to adapt to a constrained economic environment to continue their activities.

4

Rapport de la mission ‘Musées du XXIe siècle’, https://www.culture.gouv.fr/Espace-documenta tion/Rapports/Rapport-de-la-mission-Musees-du-XXIe-siecle2. 5 La stratégie nationale de culture scientifique, technique et industrielle, https://www.enseignem entsup-recherche.gouv.fr/cid113974/la-strategie-nationale-de-culture-scientifique-technique-etindustrielle.html.

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Also, I would like to quote from a small book by a French philosopher, Michel Serres (1930–2019). The book, Thumbelina: the culture and technology of millennials (Serres 2014: 96) summarizes the context in which mediators today work in the field of scientific culture. The title refers to the thumbs used by digital children to send SMS messages from their mobile phones. For Michel Serres, Western societies have already experienced two revolutions: the transitions from oral to written, and from written to print. The third—the rise of a digital society and new technologies—is equally decisive and is accompanied by political, social and cognitive changes. The philosopher argued that the expansion of the digital world is leading to major anthropological change, particularly in the organization of knowledge and the use of human cognitive abilities such as memory. In this context, he also questioned the future of education and pedagogy in the information society.

14.4 Current Trends in Scientific Mediation In an article published some time ago in the journal Nectart, Laurent Chiconeau— currently director of the Quai des savoirs ‘place of scientific culture’ in Toulouse, France, wrote: ‘Everywhere in France, the interest in knowledge-sharing activities, regardless of the disciplines involved and the modalities of this sharing, is alive and expanding, both for the people who conduct these mediations and for the public’ (Chiconeau 2017). I propose to detail several trends that are causing the current proliferation and the widening of the public and practices. The first is linked to a greater openness of scientific culture professionals to artists, practices and considerations about contemporary creation. The second is linked to the manufacturers’ movement, in response to a growing public demand to ‘do it’, in the form of the practice workshop, mixing traditional DIY (do it yourself) and digital manufacturing. This is called a ‘maker movement.’ This movement has been very popular for 10 years thanks to Neil Gershenfeld, a professor at the Massachusetts Institute of Technology. The first FabLab allowed people to make (almost) anything, thanks to some digitally controlled machines, including the famous 3D printer. What is interesting is that, in these places, learning is done by peers designing and carrying out projects individually or collectively. Several dimensions— learning through practice, valuing trial-and-error approaches, project dynamics— have attracted the interest and support of many scientific centres, scientific museums and universities. France ranks second for the number of FabLabs installed, behind the United States. Along with FabLabs, many places dedicated to open innovation are developing. The practices of scientific, technical and industrial culture have been diversified towards greater co-construction of knowledge and innovation.

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The third trend is towards YouTube and the new popularizers. Girls and boys passionate about science, without necessarily having scientific training, YouTubers talk about what interests them, makes them dream, surprises them or amuses them in short videos. Their channels—such as ‘Florence Porcel’ ‘Mental Ballad’ or ‘The Skewed Face’—have tens or even hundreds of thousands of subscribers. In three years, the YouTubers have brought a breath of fresh air with a good dose of humour into scientific culture.

14.5 The Commitment of Researchers Finally, a strong trend currently in France is linked to the commitment of research staff to scientific culture. Much work involving research staff is being done, including training and mediation for and with PhD students. A recent survey listed some 40 current training courses for researchers in France. Direct exchanges between researchers and the public are multiplying, whether in the context of events such as ‘My thesis in 180s’ or the ‘European Night of Researchers’ or throughout the year in the form of actions implemented by universities or public research institutions. The benefits of such events are important, and the relationship between the research world and the work of researchers is no longer the same. As Mélodie Faury, a researcher at the University of Strasbourg, sums it up: What we feel very strongly is that the human relationship that is created in these situations is important. It can sometimes be an emotional moment between the researcher, the students, the children. That has an impact on our idea of what a scientist is. We come out with perhaps more questions than answers, but also with a lot of new ideas about something much more accessible. The researchers don’t seem that far away; the researcher can talk to me. (Durrive et al. 2013). Finally, it seems that scientists are taking advantage of these events. The exercise requires an effort to formulate their purpose, their research, but can also feed their work. As Matteo Merzagora, director of Espace Pierre Gilles de Gene in Paris, says: When I hear the reception, I think of those moments when a researcher and the public meet. And see what happens in between, not only among the public, but also among the researchers. There is a tendency in mediation operations, in scientific culture, to invite researchers only for what they know. And the audience only because of what they don’t know. Whereas if you really think about being a researcher, he spends most of his time dealing with things he doesn’t know. That’s what he’s passionate about. And the public has a lot to share, and wants to tell the researcher. So I think we now have the opportunity, through cultures that have developed, like the creator, to achieve a relationship to knowledge that has been modified. We

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can build spaces where researchers also come for what they don’t know and for what they know.6

14.6 Conclusion Like Laurent Chiconeau (2017), one wonders whether all these new practices are responsible for a better recognition of technical and industrial scientific culture as an integral part of the common culture of the twenty-first century. I may have shown the richness and diversity of practices at work today in France, but, paradoxically, we are living in a curious period when misinformation, fake news and false science rub shoulders with Wikipedia, the largest encyclopaedia ever created. There have never been more people who distrust science, while access to immense resources for education, creativity and the sharing of traditional and digital know-how has never been greater. This is why it is more necessary than ever to develop critical thinking. By sharing the scientific approach, citizens can be empowered to develop and reinforce their curiosity, open-mindedness and critical thinking. Since March 2020, the measures taken to stem the spread of Covid-19 have called into question the functioning of our societies. Therefore, the cultural sector, particularly our museums, scientific, technical and industrial heritage and culture, is not immune to this crisis. An entire professional community has been affected. We have had to learn to work differently, in telework and without direct relationships, and to imagine a new agenda. Also, for some cultural structures, this crisis has accentuated economic constraints and called into question the sustainability of their actions. In France, the rest of Europe and elsewhere, the initiatives of professionals to continue despite everything are innumerable. They demonstrate the commitment, responsiveness and adaptability of the players. Due to the closure of public places, they almost all invest in the digital field in order to continue to offer a rich and diversified cultural product. Also, professional networks play an important role by uniting those initiatives and organizing exchanges in the form of webinars. To return to the more specific context of the year 2020, and to the current health crisis, I quote an excerpt from a column by philosopher Bruno Latour in the French daily Le Monde: ‘I make the assumption, like many, that the health crisis prepares, induces, encourages [us] to prepare for climate change’ (Latour 2020). While this crisis raises questions and reflections on the part of researchers and professionals in our community, those of visitors and users of tomorrow’s museum structures will be just as important. Is a new relationship with the public being forged? Will museums be more accessible after this crisis? In this context, the structures of scientific, technical and industrial heritage and culture remain key interlocutors for societal, scientific and environmental issues. 6

L’Expé, http://www.experimentarium.fr/medias.

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References Bardon A (2012) Inmédiats: des centres de culture scientifique aux agoras de l’innovation. EchoSciences Grenoble, 29 May. https://www.echosciences-grenoble.fr/articles/inmediats-des-cen tres-de-culture-scientifique-aux-agoras-de-l-innovation Chevènement J-P (1982) ‘Discours de clôture au Colloque National sur la Recherche et la Technologie’, Actes du Colloque National Recherche et Technologie. Éditions du Seuil, Paris Chiconeau L (2017) La culture scientifique et technique est-elle en train de se faire une place au panthéon de la culture? Nectart 5:58–65. https://www.cairn.info/revue-nectart-2017-2-page-58. htm?contenu=resume Durrive B, Faury M, Henry J (2013) Réflexivité et dialogue interdisciplinaire: un retour sur soi selon l’autre. In Béziat J (ed) Analyse de pratiques et reflexivité: regards sur la formation, la recherche et l’intervention socio-éducative. L’Harmattan, pp 153–166 Guyon É, Maitte B (2008) Le partage des savoirs scientifiques: les centres de culture scientifique, technique et industrielle. La Revue pour l’histoire du CNRS, no. 22 Latour B (2020) La crise sanitaire incite à se préparer à la mutation climatique. Le Monde, 25 March Levy-Leblond J-M (1984) La culture scientifique et technique: entre le mot et la chose, entretien réalisé par M. Barrère. La Recherche, no. 156 Serres M (2014) Thumbelina: the culture and technology of millennials. Rowman & Littlefield

Samuel Cordier is Heritage curator, Director of the zoological museum of Strasbourg (France). A doctor in the museology of science, in 2005 he defended a thesis titled ‘Trends and particularisms of provincial collections in the eighteenth century. He has carried out his professional activity in France at the natural history museum of Nîmes, at the Research Institute for Development (IRD) at the Science Pavilion, Centre for Scientific, Technical and Industrial Culture of Bourgogne-FranceComté, as well as at the Office for Museum Cooperation and Information (Ocim) at the University of Burgundy.

Chapter 15

Emerging Practices Based on New Media in the Chinese Science Popularization Industry: Transformation in the New Era of Science Communication Fujun Ren, Xuan Liu, and Jianquan Ma Abstract Science popularization (SP) in China can be divided into the for-profit SP industry and non-profit SP undertakings. The SP industry is the sum of the activities providing SP products and SP services to the state, society and the public on the basis of market mechanisms and related activities. The industry has SP content and services as its core products and involves the four links of creation, production, dissemination and consumption of SP products, which not only spread scientific knowledge, thought, spirit and methods but also create jobs and increase the public’s scientific literacy. According to the classification of cultural industries, SP industries can be divided into science news, SP news, SP books, SP magazines, SP radio and television programmes, science fiction movies, SP plays, SP exhibition halls, SP tourism, SP websites and so on. Science communication has entered a new era using highly integrated digitalization in society and the economy, so the SP industry in China is gradually changing. Today, as emerging technologies find wide application and permeate everyday life, the public relies on web-based information resources, content, services and a variety of media and information service platforms to satisfy its demand for SP. New media platforms, such as websites, Weibo and WeChat, have become more and more important for SP. This chapter describes the background and development of China’s SP industry and research related to the industry. We use representative comprehensive SP brands from government and private enterprise—China Science Communication and GuoKe (guokr.com)—as typical cases and analyse their status and the characteristics of new media platforms based on 5 W theory. Through comparative analysis, we identify problems in the development of the new media SP industry in China and make suggestions on that basis. Keywords Science popularization industry · New media · Case study

F. Ren (B) · X. Liu · J. Ma National Academy of Innovation Strategy, Beijing, China e-mail: [email protected] J. Ma e-mail: [email protected] © China Science and Technology Press 2021 B. Schiele et al. (eds.), Science Cultures in a Diverse World: Knowing, Sharing, Caring, https://doi.org/10.1007/978-981-16-5379-7_15

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15.1 The Science Popularization Industry 15.1.1 Science Popularization Science popularization (SP) began in the 1840s. At the beginning, it mainly emphasized the popularization of science to the public; that is, the use of simple language in a way that common people could understand. Its main function was to let people know about major events and discoveries on the academic and scientific research frontiers. In China, the words ‘science popularization’ appeared after 1949. Its connotation gradually expanded from emphasizing the popularization of scientific knowledge to the popularization of scientific ideas, methods, spirit and ethics (Liu Xinfang 2010). The Science Popularization Law of China promulgated in 2002 defines SP as: ‘activities in which the state and society, in a manner that is easy for the public to understand, accept and participate in, popularize scientific and technological knowledge, advocate scientific methods, disseminate scientific ideas and promote scientific spirit’.1

15.1.2 SP Industry SP in China can be divided into for-profit SP industry and non-profit SP undertakings. The Science Popularization Law of China stipulates that SP undertakings may be operated under the market mechanism, which legally demarcates the relationship between the SP industry and SP undertakings. The National Medium-and Long-term S&T Development Plan of China promulgated in 2005 emphasizes the need to:,encourage the development of business oriented popular science activities by relaxing restrictions to allow private and overseas capital to access popular science activities and by formulating preferential policies for establishing diversified investment mechanisms; and to advance the reform of public good popular science system in order to activate vitality, increase service conscientiousness, and enhance sustainable development capability. (MST n.d.) Meanwhile, the National Public Literacy Scheme of China (2006–2010–2020) promulgated by the State Council clearly highlights the concept of the ‘for-profit SP industry’ and requires ‘formulating policies and measures to foster the SP market, support the for-profit SP industry, and drive the development of the SP culture industry’.2 In 2010, the Secretariat of the Communist Party of China Central Committee set guidelines for promoting both public SP undertakings and for-profit SP undertakings and further pointed out the direction of development of the SP 1

Science Popularization Law of China, http://www.npc.gov.cn/wxzl/wxzl/2002-07/10/content_2 97301.htm. 2 National Public Literacy Scheme of China, http://www.gov.cn/gongbao/content/2006/content_2 44978.htm.

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industry. Against this backdrop, Chinese scholars have carried out research on the concept, classification and format of the SP industry, while there are few relevant studies but rich practice in other countries. Although there is little specific research on the SP industry abroad, there is a rich theoretical research literature on cultural industries, including the SP industry. UNESCO, in Cultural industries: a challenge for the future of culture, published in 1982, discussed the origin and demarcation of the cultural industries, their impact on culture and their trends of development and outlook (UNESCO 1982). According to British scholar Justin O’Connor (1999), the cultural industries are those activities that deal primarily in symbolic goods—goods whose primary economic value is derived from their cultural value. That definition encompasses 16 industries called the ‘classical’ cultural industries (broadcasting media, film, publishing, recorded music, design, architecture, new media) and the ‘traditional arts’ (visual art, crafts, theatre, music theatre, concerts and performance, museums and galleries). Ieva Moore (2014) examined the definition of the cultural industries from the perspective of historical development and believed that they integrate creative conceptualization, production and commercialization and that the cultural industries should be put in the context of digital transformation rather than just based on culture or creative culture. In China, there has been some specific research on the SP industry. Lao Hansheng (2004), from the perspective of the cultural industries, defined the SP culture industry as an industry that meets the need for scientific information, products and services. He divided the industry into public, quasi-public and commercial segments according to the orientation of the activity (Lao Hansheng 2005). Zeng Guoping et al. (2010), referring to the National Scientific Literacy Scheme, expounded the legitimacy of SP culture industry research in the context of SP as part of culture and the cultural industries in an attempt to establish a four-quadrant system of SP industry research. Ren Fujun et al. (2011) believed that the SP industry should be classified in relation to the classification of the cultural industries. Yang Dongmei (2015), examining the necessity to develop the SP industry with a focus on modern science museums, pointed out that the purpose of developing the SP industry is to allow science museum operators to derive profit from SP products and services, to meet consumers’ demand, and to increase public scientific literacy. The author emphasized the public orientation of science museums and argued that for-profit SP undertakings should better support public SP services. Based on the foregoing, we offer the following definition of the SP industry: the SP industry is the sum of the activities of providing SP products and SP services to the state, society and the public on the basis of market mechanisms and their related activities; it is an industry that has SP content and services as its core products and involves the four links of creation, production, dissemination and consumption of SP products and that not only spreads scientific knowledge, thought, spirit and methods but also creates jobs and increases the public’s scientific literacy. According to the classification of cultural industries, cultural industries can be divided into nine categories, such as news services; radio, television and film services; cultural leisure and entertainment services; and network cultural services. In the SP

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industry, those categories become science news, SP news, SP books, SP magazines, SP radio and television programmes, science fiction movies, SP plays, SP exhibition halls, SP tourism, SP websites and so on.

15.1.3 The Relationship Between the For-profit SP Industry and Non-profit SP Undertakings in China Ren Fujun et al. (2010) argue that public SP undertakings are meant to conduct notfor-profit SP activities by providing SP public services (including goods) as a public function assigned or encouraged by the state and that for-profit SP undertakings, which constitute the SP industry, are meant to provide consumers with SP products and services that meet SP demand under the market mechanism. Gu Huang et al. (2012) introduced ‘public good’ theory and argued that SP resources are quasi-public goods. For example, rural SP and SP festivals are goods with a fairly strong public nature, and SP games are less public goods. If products in the SP culture industry are seen as a sequence of quasi-public goods arranged in descending order by scientific content and in ascending order by other content, the sequence also shows a descending order in the goods’ public nature; SP venues representing a typical SP good with a strong public nature and sci-fi works such as Astro Boy are thus SP products of a weak public nature. We can see coordination between government and the market and between public SP undertakings and for-profit SP undertakings. Handy examples include: • SP festivals organized by government but with participation by for-profit SP undertakings • SP policies encouraging the development of the SP industry • SP products and services offered in the market that supplement public SP goods. All of these represent the integration of public SP undertakings and for-profit SP undertakings. On more specific levels, the abovementioned three examples also have fundamental differences in the integration of public SP undertakings and for-profit SP undertakings and represent two fundamental types of integration. The first type is integration of approaches, or internal integration, as is the case in the first and second examples. In internal integration, public SP undertakings are not merely about the provision of SP public goods by the government but the act of the government coordinating the non-government sector to improve SP services. For internal integration, while for-profit SP undertakings follow the market mechanism, the government also plays an important role in guiding and supporting the SP industry. This in essence is a win–win integration of public SP undertakings and for-profit SP undertakings as two approaches to SP. The second type of integration is the external integration of public SP undertakings and for-profit SP undertakings as two distinctive categories of entities, in which

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the former is dominated by the government and the latter dominated by the nongovernment sector, as is the case in the third example. Those two types of integration supplement and reinforce each other and develop side by side.

15.2 New Media and New Media SP 15.2.1 Definition of New Media and the Strengths of New Media SP The term ‘new media’ was introduced by Peter Goldmark, Director of the CBS Technology Center, in 1967. As for what new media are, different people have different views. Xiong Chengyu, a professor at Tsinghua University, believes that new media is a relative concept and that ‘new’ is a term relative to ‘old’. The concept of new media has changed alongside the evolution of media. Radio is a new medium compared to newspapers, TV is a new medium compared to radio, and the internet is a new medium compared to TV. The prevalence of the internet makes internet media the fourth largest media category after newspapers, radio and television. Over time, online media have become a synonym for new media. However, with the advance of the times and the progress of science and technology, there has been a surge in new media forms using increasingly diverse communication methods and content, such as digital TV, vehicle-mounted TV, elevator advertising, WeChat, mobile TV and so on. With the development of new media, new media SP has also developed swiftly. Compared to SP using traditional media, SP activities carried out on new media have a host of advantages. First, the new media allow more lively means of communication. The trend of convergence on new media makes it possible to present text, audio and video in an integrated format, which is mind-blowing for the audience and thus enhances the SP effect. Second, there is more interaction in the SP process. Traditional media transmit a large volume of SP information to the audience through one-way communication. The audience can only passively receive the information, with no chance to respond and react in real time. New media, on the contrary, are more interactive. Through SMS, WeChat, online forums, instant communication and other channels, we can communicate with audiences in both ways, which is consistent with the idea of modern science and technology communication. Lastly, more targeted SP publicity is possible. The technical features of new media have made distributed communication a reality. Internet service providers can push information and services to users based on the users’ personal demands. Fragmentation is a unique feature of new media SP. The availability of mobile terminals makes it possible for people to consume the content that interests them anytime and anywhere, unconstrained by time and space.

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15.2.2 The Current Status of New Media SP in China The rapid development of the internet has provided a more convenient and effective communication platform for the popularization of science. Table 15.1 shows the changes in the number of Chinese internet users and internet penetration rates in recent years, based on the data in the Statistical report on China’s internet development released by the China Internet Network Information Center (CNNIC). It can be seen that the number of internet users and the internet penetration rate in China are growing rapidly year by year. The number of mobile phone users in China has been steadily increasing. By the end of 2016, it had exceeded 1.322 billion (MIIT 2017). Given the background of the further popularization of 4G networks and the continuous development of smartphones and wireless networks, mobile phone applications producing high data traffic, such as video and music, have attracted more and more users. By the end of 2017, the number of mobile internet users in China had reached 753 million, up by 57.34 million compared to the end of 2016. The proportion of internet users who use mobile phones to access the internet increased from 95.1% in 2016 to 97.5% (CNNIC 2018). With the rising proportion of mobile internet users, the mobile phone is now the number one terminal for accessing the internet, and its huge user base is the potential audience for new media SP. According to the results of the 2015 survey on the scientific literacy of the Chinese people, the internet has become the main channel for people in China to obtain scientific and technological information. Some 53.4% of the Chinese people are now accessing scientific and technological information through the internet and mobile internet. And among people with high scientific literacy, the proportion is as high as 91.2%.3 This shows that the internet has become the primary channel for people with high scientific literacy to obtain scientific and technological information. Figure 15.1 shows the relative weight of the main channels for the Chinese people to access scientific and technological information. In terms of the utilization of internet and mobile internet channels, WeChat, search engines such as Baidu and Google and portal websites such as Tencent, Sina and Xinhuanet are the most commonly used channels for the Chinese people to obtain scientific and technological information; knowledge websites such as Guokr.com, ScienceNet.cn and Baidu Baike as well as Weibo are also commonly used channels for people in China (Fig. 15.2). As can be seen from the data above, new media SP has become an effective means for people to acquire scientific knowledge. The development of the internet SP industry required not only a material and technological foundation, but also the necessary demand from internet users. As a new means of science popularization, new media SP has begun entering a stage of rapid development and is receiving more attention from society. First, there has been strong commitment from the government. Many policies adopted by the government in recent years contain specific provisions on new media SP. Second, 3

China citizens’ scientific literacy report IV, China Science and Technology Press, 2018.

– –

27.9

28.9

28.8

3.84

2009

18.7

34.3

19.0

4.57

2010

Source 41st statistical report on China’s internet development, CNNIC, February 2018

Year-on-year growth of internet penetration rate (%)

22.6

Year-on-year growth of netizen numbers (%)

Internet penetration rate (%)

2.98

2008

No. of netizens/100 million people

Year

11.1

38.1

12.2

5.13

2011

10.5

42.1

9.9

5.64

2012

8.8

45.8

9.6

6.18

2013

Table 15.1 Changes in the number of Chinese internet users and the internet penetration rate in recent years

4.6

47.9

5.0

6.49

2014

5.0

50.3

6.0

6.88

2015

5.2

52.9

6.2

7.31

2016

5.5

55.8

5.6

7.72

2017

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Books

23.2%

13.3%

Journals and magazines Broadcasts

10.5%

Relatives, friends and colleagues

23.7% 25.0% 34.9%

16.2%

38.5% 38.6%

Newspapers

53.4%

Internet & mobile internet

91.2% 93.4% 86.8%

TV

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% All citizens

Citizens with high scientific literacy

Fig. 15.1 Main channels for the Chinese people to access scientific and technological information. Source China citizens’ scientific literacy report IV, China Science and Technology Press, 2018 Others 5.4% 4.1% SP apps

9.7% 5.5%

Science blogs

9.5% 6.9%

Digital Science Museum

10.9% 6.2%

E-journals

13.3% 9.2%

E-newspapers

18.7%

8.9%

E-books

17.8%

12.1%

Weibo

28.0%

Knowledge websites (e.g. Guokr.com, Baidu Baike)

15.5%

33.5%

Portal websites (e.g. Tencent, Sina, Xinhuanet)

11.1% 53.7%

Search engines (e.g. Baidu, Google)

15.1%

57.3%

WeChat

11.7%

51.0% 0%

Often use, trust

20%

23.1% 40%

60%

80%

Often use, do not trust

Fig. 15.2 Channels used by the Chinese people to access scientific and technological information from the internet and level of trust in the scientific and technological information communicated through online channels. Source China citizens’ scientific literacy report IV, China Science and Technology Press, 2018

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Table 15.2 The number of SP websites built with government funding Year

2008

Number of SP websites

1,844 1,978 2,126 2,137 2,443 2,430 2,652 3,062 2,975

Year-on-year growth (%) –

2009 7.3

2010 7.5

2011 0.5

2012 14.3

2013

2014

– 0.5 9.1

2015 15.5

2016 – 2.8

Source Ministry of Science and Technology of the People’s Republic of China, China science popularization statistics, 2008–2017 editions, Scientific and Technical Documentation Press, Beijing

huge government investments have been made, especially in landmark projects. For example, in the first three years of the construction of the China Digital Science and Technology Museum, the government invested over 50 million yuan, which is the largest single investment ever in new media SP. There is a very positive external environment for the development of new media SP at both the policy and investment levels. Under such circumstances, SP websites have sprung up in China, and the internet has become a new front line of SP, playing a significant role in promoting scientific knowledge. According to the data in China science popularization statistics,4 by the end of 2016, 2975 SP websites had been built in the country with government funding (Table 15.2). That means those websites were built by government’s purchases of services or institutions supported by public funds, including government departments; branches of the China Association for Science and Technology (CAST); mass media; science museums; education and research institutions; other societies and organizations; individuals; and enterprises. The absolute number of SP websites is also increasing year by year, covering all 31 provinces, autonomous regions and municipalities directly under the central government in the mainland. With the support of multimedia technology, SP websites are also taking diverse forms. Video and audio content is commonly seen and heard on the internet. Virtual museums, online live broadcasting, interactive games and other new SP forms are also frequently used by SP websites. Some SP websites, such as the China Digital Science and Technology Museum, the Virtual Science Museum of China and China Public Science and Technology Net, have been quite successful. In general, the technical communication capability of websites is increasing, and more and more SP pages can now be found on various types of websites. Many Chinese portal sites have developed some types of SP content, including special columns and topic pages. The four major portal sites (Sina, NetEase, Tencent and Sohu) all have technology channels on their secondary pages. People’s Daily Online also has a special science and technology channel dedicated to the dissemination and popularization of scientific knowledge. It has opened several interesting and interactive columns, such as a lecture hall on the history of human invention and a digital science and technology museum. As a key member of the New Media SP Alliance, it provides a special SP

4

Ministry of Science and Technology of the People’s Republic of China, China science popularization statistics, 2008–2017 editions, Scientific and Technical Documentation Press, Beijing.

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engine on its web page, with which the visitors can search for detailed information about professional SP websites and columns.

15.3 Case Analysis As mentioned above, with the development of network infrastructure and the application of new media technology, the number of Chinese citizens who obtain scientific and technological information through the internet and mobile internet increased from 26.6% in 2010 to 53.4% in 2015, and the main sources of information have been WeChat, websites and Weibo. According to the Report on SP search behavior released by CAST, the SP search index of Chinese netizens in 2018 was 9.164 billion (an increase of 19.17% over 2017), and the SP search index of mobile terminals was 3.36 times that of PC terminals (CAST 2019). SP new media have become an important way for people to obtain SP information. Based on the big-data evaluation indexes of the Chinese new media industry, such as China SP Sites Ranking5 and the WeChat Communication Index (WCI),6 we have selected representative comprehensive SP brands from government and enterprise new media SP—China Science Communication and GuoKe (guokr.com)—as our research objects. The specific principles for selection were that the brand must rank in the top five; have independent SP websites, WeChat and Weibo accounts; and be a comprehensive SP brand. According to the 5 W communication element theory, the information communication process has five components: the subject, content, media, audience and effect. As websites, Weibo and WeChat are different communication media, they have their own characteristics and styles, and they differ in content, audiences and communication effects. The following sections discuss the SP subject, the SP content, the SP audiences and the communication effect of three different media.

15.3.1 SP Subject: China Science Communication and GuoKe China Science Communication is a new media SP brand initiated by CAST in 2014. By 2018, it had 23 websites (channels) and 29 mobile applications. China Science Communication has selected more than 20 subprojects from more than 10 leading internet operators, including People’s Daily Online, Xinhua, Tencent and Baidu, using animation, audio, video, virtual reality and other creative forms to present and communicate science to the public. By the end of February 2018, China Science Communication channels had launched nearly 19 terabytes of content resources, 5 6

China SP Sites Ranking (2018), https://www.wkepu.com/top/2018.html. WeChat Communication Index, http://www.gsdata.cn/.

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more than 180,000 SP picture-texts, 14,000 SP videos (animations) and more than 150 SP games, registering a total of 18.2 billion visits, over 74% of which came from mobile terminals. Founded in 2010 with the slogan ‘Science and technology is interesting’, GuoKe is an open and diversified brand of scientific culture. It is committed to spreading scientific knowledge in an interesting way, actively advocating a scientific and rational lifestyle and making life better with science. With 18 new media brands and nearly 10 million users, GuoKe has become the most influential SP brand in China. GuoKe built a media matrix, including strong scientific brands such as Guoke.com, ‘Scientific people’ and ‘Rumour crusher’, more than 10 generic scientific brands (such as GuoKe Research Institute, Health 9-to-5, GuoKe Children’s Academy), and derivatives such as MOOC College, and Zaihang salons. GuoKe also set up the Pineapple Science Awards, created a GuoKe laboratory and launched a cultivation programme. On GuoKe, netizens can follow people in whom they are interested and communicate with each other. GuoKe has its own professional SP team, the members of which pay close attention to the latest scientific and technological progress and select topics close to the public’s lives. They are good at using a unique perspective and vivid language to spread scientific and technological knowledge. GuoKe is one of the most popular new media SP brands among the public, especially young people.

15.3.2 SP Content China Science Communication and GuoKe both insist that content is king and constantly innovate expression forms, using graphics, audio, video and SP games to attract users. As a national SP platform, China Science Communication has a strong advantage on content authority. Taking quality of content as its top priority, it has leveraged its advantage of having 210 affiliated academic societies across the country to strengthen the scientific review of SP content. Each topic is reviewed by two or more experts in the field. In the special column titled ‘China Science Communication—Science Encyclopedia’ on Baidu Baike, there are 114,000 authoritative scientific entries compiled by some 3000 well-known experts, attracting nearly 4.6 million visits every day. More than 2000 experts and scholars, including nearly 100 academicians, have been invited to shoot videos or write manuscripts. GuoKe also pays attention to the authenticity of its SP content. It set up a theme website called ‘Rumor Crusher’, established the rumour-cracking process and created the scientific rumour database ‘Rumor Encyclopedia’ to become the pioneer of scientific rumour dispelling in the SP industry. In addition, GuoKe has followed the latest papers, making timely reports and interpreting the latest progress in scientific research, and has been good at looking for appropriate scientific topics in emergencies and during important public events. The quality of GuoKe information is guaranteed from three aspects. First, it has its own editing team, including more than 20 professional editors, more than 80 scientific consultants and more than 1500

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Table 15.3 SP website ranking of China Science Communication and GuoKe PV rank (global)

UV rank (global)

Rank in China

China science communication

538,600

586,047

—

GuoKe

63,615

51,787

4,104

Source Data from Alexa (www.alexa.cn), 19 February 2021

scientific authors, which ensures the quality of its SP information. The second is more than 1200 ‘GuoKe Masters’—a group of GuoKe users who love their expertise and have achieved much in their fields— who provide intellectual support for topic selection and content. The third is about 100,000 active community users, who, gathered in the GuoKe community through their interests, generate tens of thousands of interactions every day. Their topics can cover all fields of SP. From the perspective of content characteristics, the content of China Science Communication is comprehensive and large and updated in good time. It has established an SP service cloud platform, which integrates the construction of new media SP with traditional SP. According to the topics most frequently discussed by the public, its SP topics are divided into eight categories, including science frontier, encyclopaedia, health, science fiction, science characters and module topics. The contents are mostly new, closely related to current affairs, and integrated from the perspective of topics that users are most concerned about. China Science Communication provides SP video content through VTV Express and SP mobile games and PC games through ‘Fun Science’, to popularize science in an all-round way. Its SP knowledge is highly practical and time-sensitive. As an open and diversified new media SP brand, GuoKe has both SP and social networking functions. Its SP knowledge is closer to life and its SP method pays more attention to interactions. Its SP content mainly consists of three sections: scientific people, GuoKe groups, and questions and answers. Its highlight lies in interesting SP and social SP. The scientific people section gathers all kinds of SP knowledge provided by GuoKe’s science writers. The subjects cover more than 20 categories, such as physics, biology, the environment, astronomy, medicine, geography, chemistry and agriculture, including anti-rumours, opinions and other aspects. ‘GuoKe Group’ is an online community communication platform on SP topics. Members can follow their personal interests to join different groups, read SP content in which they are interested, and communicate and interact with others. By March 2018, GuoKe had created 644 interest groups for members to participate in discussions.

15.3.3 Audiences and Effects of SP Websites Because the interaction effect between the website and the audience is not obvious, we introduce the Alexa network ranking list as an analysis indicator (Table 15.3).7 7

Alexa, http://www.alexa.cn/.

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Alexa is currently recognized as an authoritative statistical website with the largest number of URLs and publishing ranking information in the world. Its ranking is calculated based on the geometric average of the number of web user links and page views accumulated in three months. The most commonly used indicator for evaluating website traffic, ‘PV’, refers to the number of page refreshes. Each time a page is refreshed, the traffic number increases by one. ‘UV’ refers to the number of unique visits, or the number of people visiting a certain site from different IP addresses. There are great differences in the numbers of visitors to different SP websites. The numbers of page views and of visitor visits on GuoKe are significantly higher than for China Science Communication. Although the SP websites set up by government have more abundant SP information resources, the SP websites set up by enterprises have a wider influence on the audience. But, on the whole, the ranking of SP websites in the entire network is relatively low.

15.3.4 Audience and Effect of SP Weibo Weibo was originally a social platform providing microblogging services. With the development of mobile network technology and of smartphones, the main operating carrier of Weibo has shifted to mobile clients. In 2009, the promotion and popularization of the Weibo platform, led by Sina Weibo, started the rapid development of microblogs in China. According to the latest financial report released by Sina Weibo, the number of monthly active users in September 2020 was 511 million, of whom about 94% were mobile users, and the average daily number of active users was 224 million.8 We selected the Sina Weibo platform for analysis, as it has always been the leader in China in numbers of users and visits. By 31 January 2021, using SP as the label qualifier to search on the Sina Weibo platform, we found that there were 6680 accounts, including 1960 authenticated users.9 We also selected the official Weibo accounts of China Science Communication and GuoKe and counted the information posted and interactions from 1 to 7 December 2020. GuoKe set up its Weibo account earlier, and the number of fans has exceeded 10 million, so it is relatively well known. Although China Science Communication set up its Weibo account later and has relatively fewer fans, the frequency of posting is higher, and the total number of weibos (posts) is very close to that of GuoKe (Table 15.4). Weibos include texts, pictures, videos, links and other forms of expression. The text content was limited to 140 characters in the early days, but that limitation was lifted in 2016; however, most users still publish information in a relatively short and concise way. The weibos posted by China Science Communication and GuoKe within the scope of these statistics were mainly composed of two parts: a limited amount of text plus additional content (‘text + pictures’, ‘text + article’ and ‘text 8

‘Weibo releases 2020 third quarter financial report’, media release, 28 December 2020, http://fin ance.sina.com.cn/stock/usstock/c/2020-12-28/doc-iiznezxs9422515.shtml?cref=cj. 9 Data from Sina Weibo (https://weibo.com/) search results.

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Table 15.4 SP weibo information for China Science Communication and GuoKe Date of the first weibo

Total number of weibos

Number of fans

China Science Communication

23 July 2014

43,906

4,170,628

GuoKe

14 November 2010

47,862

10,120,626

Source Data from Sina Weibo (https://weibo.com/), 19 February 2021

+ short video’). The text mostly gives the weibo a title or topic description in order to attract the attention of the audience, and the real SP information is presented in the pictures, articles and videos in the additional content. The text part is usually original, while the specific SP content is mostly forwarded or conveyed from its website. The topics mainly focus on current affairs or news related to science and technology, health knowledge, rumour-squashing and so on. In the period analysed, China Science Communication posted more weibos, with an average of 25 weibos per day, while the average of GuoKe was nine, reflecting the richness of SP resources owned by China Science Communication (Table 15.5). Based on the social and interactive advantages of Weibo, we used dissemination power and interactivity indicators to evaluate the effect of Weibo SP. The dissemination power of Weibo is represented by the number of likes and reposts of the posted weibos. More likes means higher numbers of readers and recognition from the audience, which leads to the stronger influence of the weibos. More reposts indicates that the scope or spread is wider. The interactivity analysis of Weibo includes the number of comments per weibo and the total number of comments. The more comments, the stronger the interaction of Weibo (Table 15.6). There was a gap between the number of comments, reposts and likes of China Science Communication and GuoKe. GuoKe has more advantages in dissemination power and interactivity, both on the overall number and the average.

15.3.5 Audience and Effect of SP WeChat WeChat is not only a communication and social platform but also a platform for tools, media and marketing. According to Tencent’s latest financial report, the monthly number of active WeChat users was over 1.12 billion (in September 2020),10 and the frequency of messages being sent through WeChat exceeded 45 billion (2018),11 indicating that WeChat has achieved extensive coverage of mobile internet users in China. The widespread application of WeChat and the large number of WeChat 10

‘Tencent releases third quarter 2020 financial report, QQ monthly active users hit a new low’, Sohu, 12 November 2020, https://www.sohu.com/a/431392914_100191017. 11 Peng Lin Ye Dan, ‘In 2018, there were approximately 1.08 billion WeChat monthly active users, and 45 billion WeChat messages were sent every day’, People.cn, 10 January 2019, http://tc.peo ple.com.cn/n1/2019/0110/c183008-30513620.html.

12

GuoKe

11

18

2/12

14

25

3/12

11

28

4/12

8

25

5/12

Source Data collecting from Sina Weibo (https://weibo.com/), 19 February 2021

30

China Science Communication

1/12

3

28

6/12

Table 15.5 SP weibos posted by China Science Communication and GuoKe, 1–7 December 2020

9

23

7/12

9.71

25.28

Average of 7 days

68

177

Total number over 7 days

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Table 15.6 SP weibo effect of China Science Communication and GuoKe, 1 to 7 December 2020 Average Average Average Total likes reposts comments likes China Science Communication GuoKe

46.12

16.67

7.11

269.02

181.35

53.39

8,165

Total Total Total reposts comments interactivity 2,951

18,294 12,332

1,285

12,401

3,631

34,257

Source Data collected from Sina Weibo (https://weibo.com/), 19 February 2021

subscription accounts have made possible the rapid dissemination and wide diffusion of information. As WeChat has become an important new media tool for communicating and sharing information, WeChat subscription accounts have also become an important way of delivering SP. The WeChat platform can synchronously or asynchronously disseminate information in various forms, such as voice, pictures, animation and video, and has the characteristics of efficient and accurate dissemination. At the same time, subscribers to SP WeChat subscription accounts can share information using the functions of ‘Send to WeChat friends’, ‘Share to Moments’, and ‘Share to mobile QQ’. According to the statistics, by 31 December 2020, there were 4487 SP WeChat subscription accounts. They published more than 57,000 SP articles in only one month (December 2020), and the total number of reads exceeded 23.45 million.12 WeChat has been an important tool in the new media SP industry. Since WeChat is a social platform with relatively private personal information, users can obtain and read WeChat subscription accounts in a personally visible way. Therefore, the direct audience of WeChat SP is the group that subscribes to SP accounts. At the same time, based on the characteristics of social platforms, WeChat SP information can expand its audience by means of the share function. Our assessment of the dissemination effect of SP WeChat subscription accounts mainly comes from the statistical results available from the Gsdata platform. Gsdata is recognized as a highly authoritative index for evaluating the effect of WeChat subscription accounts. It establishes WeChat subscription account rankings by calculating the WeChat Communication Index (WCI). It can analyse whether information is acquired by the audience within certain times and how many readers the information has acquired, including two specific measurement indicators of total readings and likes. We counted the data for China Science Communication’s and GuoKe’s WeChat subscription accounts for the week from 13 to 19th February 2021 (Table 15.7). China Science Communication and GuoKe are relatively active, measured as both the number of fans and the number of interactions, and have strong communication power.

12

Data from search results on the Gsdata platform (http://www.gsdata.cn/).

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Table 15.7 SP WeChat effect of China Science Communication and GuoKe, 13–19 February 2021 Active fans

Total reads in 7 days

Total likes in 7 days

Average reads

WCI

Average rank in all WeChat subscription accounts

China Science Communication

695,355

3,679,905

17,717

65,712.6

1,748.09

27

GuoKe

723,855

2,775,264

20,602

59,774.9

1,695.23

47

Source Data from search results on Gsdata platform (http://www.gsdata.cn/), 19 February 2021

15.3.6 Comparative Analysis On the whole, the subject matter of China’s new media SP industry has become more diverse, and both its quantity and its quality have increased. Compared with traditional SP, new media SP has shown greater development in forms of expression, audience scale and influence. The updating of SP information is timely, and the content and setting have both common features and their own characteristics. The forms of presentation are relatively diverse, and the topics are closely related to people’s daily lives. The contents of SP website columns are mainly pictures and texts, and video information is increasing. SP weibos mostly post SP pictures and short videos related to social events and daily life. SP WeChat mostly publishes long SP articles covering the fields of health, news, human emotions and so on. The audience size and influence of various SP platforms are different. Governmentsupported new media SP brands have sufficient SP information resources, but they are slightly less influential than SP brands established by for-profit enterprises. However, there are still some problems in new media SP industry. First, the popularization of SP subjects has weakened the online discourse power of the leading SP practitioners. In the internet era, everyone has the opportunity to publish and disseminate scientific information. In that context, the leading SP experts have no obvious advantages as the leading online SP media. Although the leading SP platforms are rich in the scale of their information and forms of expression, and updates are relatively fast and timely, their authoritative information is often not so attractive as other news, and even less so than pseudoscientific information, which greatly reduces their communication effect. Although well-known brands such as China Science Communication and GuoKe are developing well, the number of SP websites, including Weibo and WeChat, is still small compared to the overall number of websites. As shown in Table 15.8, the numbers and interactions of Weibo users labelled with ‘SP’ are significantly lower than for others. Among more than 885,000 WeChat subscription accounts, there were only 4,487 related to SP. The ‘key opinion leader’ status of leading SP platforms needs to be further strengthened. Second, original content and high-quality content are relatively lacking. The online SP platforms should have dual responsibilities, both as the publishers of SP information and as the gatekeepers of SP information. Although China Science

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Table 15.8 Weibo account information with different labels Label

Total accounts

Authenticated institutional accounts

Authenticated individual accounts

SP

6,680

1,050

910

Food

5,156,3905

2,015,367

12,829,496

History

3,405,509

3,843

10,595

Philosophy

795,698

1,124

3,483

Source Data collecting from Sina Weibo (https://weibo.com/), 19 February 2021

Communication and GuoKe ensure the authority of their content through professional SP teams and close contact with scientists, on the whole, most other SP platforms do not have that advantage, resulting in a large amount of plagiarism and forgery. The limited number of original online SP works in China has resulted in homogeneous and non-distinctive content. Due to their lack of professional SP experts, some platforms pay attention only to the accuracy of their content, lacking popularity and interest and resulting in low interest from readers. The spread of pseudoscientific information, fake SP news and malicious plagiarism have a negative impact on the SP information dissemination and new media SP industry. Third, the advantages of new media’s interactivity need to be used more widely. At present, although SP websites all provide search functions for personalized needs, the information retrieved is limited, and most SP websites cannot interact with the audience for SP consultation (except for the Q&A column on GuoKe). The interaction between Weibo and WeChat SP platforms and audiences is insufficient and cannot manage the precise pushing of personalized SP information. The new media SP industry needs to improve its own construction and service capacity.

15.4 Suggestions for the Development of the New Media SP Industry We offer five general suggestions for the development of the new media SP industry. First, fully integrate all forces to build a team of outstanding SP talent. SP institutions should strengthen the construction of talent teams, establish their own SP expert groups, and unite scientists, SP experts and the public to encourage them to jointly make SP creations through relevant mechanisms or training. SP workers should get rid of the shackles of traditional thinking, update their SP creation concepts and master new media operations and skills. Second, ensure that SP content is real, timely and interesting. In the era of new media, it is difficult to distinguish the authenticity of all kinds of information. SP platforms should check the authenticity of information; establish a monitoring and rapid correction mechanism for SP information; promptly organize authoritative departments and scientists to speak out and seize the commanding heights of public opinion

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when facing emergencies; and cover SP topics that are close to public life and interesting. SP platforms should make comprehensive use of graphics, 3D animations, interactive games and other forms to present SP knowledge in a vivid and easy-tounderstand form. They also need to explore new technologies and applications, such as artificial intelligence, virtual reality and holographic projection, and constantly innovate their SP methods so as to enhance the attraction and vitality of SP. Third, build the SP industry ecology and realize deep integration. As the internet is a decentralized, flattening ecological system, SP has been developing from a traditional top-down ‘pyramid’ into a point-to-point network. SP platforms should learn from China Science Communication’s and GuoKe’s approach, strengthen their toplevel design and build a new media matrix to form their own industry ecosystem. That ecosystem can not only promote the integration of one-time SP content collection, multiple creations and multichannel presentation, but also produce the cross-media dissemination of SP content, so as to enhance the universality and effectiveness of SP. Fourth, practise precise SP and enhance interactive experiences. In the era of new media, SP has shifted from ‘media-centred’ to ‘audience-demand-centred’. SP platforms should be good at using emerging technologies such as big data and cloud computing to fully explore and analyse audience needs to achieve two changes. One is to shift SP services from their original generalized audience and homogenized content to meet the diverse and individual needs of subdivided audiences using personalized content and precise pushing of content. The other is to change their mode of SP from one-way delivery of information to interaction and experience sharing both online and offline to improve the audience’s participation and satisfaction. Fifth, innovate operating modes and increase support. Capital support is essential to the new media SP industry. As the supervisor of the SP industry, the government should study and release relevant policies and measures, such as establishing SP industry funds, to support the research, promotion and application of SP projects and create a good development environment. As one SP actor, the government should take full advantage of its lead in SP resources and the advantages of enterprises close to market demand, and establish an SP industry development mode featuring policy guidance, market operation and social participation. Other SP actors, such as enterprises, non-government organizations and individuals, should use new media platforms to strengthen brand cultivation and gradually form a multidimensional funding source system.

References CAST (China Association for Science and Technology) (2019) Report on search behavior of Chinese netizens’ popular science demands (first quarter of 2019). CAST, Beijing. https://www.cast.org. cn/art/ 019/4/26/art_1281_94546.html CNNIC (China Internet Network Information Center) (Feb 2018) 41st statistical report on China’s internet development. CNNIC, Beijing

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Dongmei Y (2015) Discussion on the development of the SP industry and modern science and technology museums. Sci Technol Econ Inner Mongolia 13:25–26 Fujun R, Yizhong Z, Xuan L (2011) Research on science popularization industry development: relevant issues. Studies Sci Popularization 3:5–13 Huang ZGG (2010) Thoughts on the science popularization–culture industry. Studies Sci Popularization 5(1):5–11 Hansheng L (2004) A strategic study on the development of popular science in China. Sci Technol Rev 8:55–59 Hansheng L (2005) Study on the strategic framework for the development of China’s SP cultural industry. Studies Sci Sci 2:213–219 Huang Gu, Guoping Z (2012) The integration of science popularization enterprise and science popularization industry: a study based on the theory of public goods. Studies Sci Popularization 7(1):23–28 MIIT (Ministry of Industry and Information Technology) (Jan 2017) Province-by-province statistics of telephone users, 2016. MIIT, Beijing Moore I (2014) Cultural and creative industries concept—a historical perspective. Procedia Soc Behav Sci 110:738–746 MST (Ministry of Science and Technology of the People’s Republic of China). China science popularization statistics, 2008–2017 editions. Scientific and Technical Documentation Press, Beijing MST (Ministry of Science and Technology) (no date) National medium- and long-term S&T development plan of China, http://www.most.gov.cn/kjgh/kjghzcq/ O’Connor J (1999) The definition of ‘cultural industries’. http://www.pedrobendassolli.com/pes quisa/ cc1.pdf Ren F, Zhang Y, Zhou J et al. (2010) Report on the development of the SP industry during the 12th Five-Year Plan period. CAST, Beijing UNESCO (United Nations Educational, Scientific and Cultural Organization) (1982) Cultural industries: a challenge for the future of culture. UNESCO, Paris Xinfang L (2010) A study on the history of science popularization of the People’s Republic of China. University of Science and Technology of China

Fujun Ren is a professor, director of National Academy of Innovation Strategy, China. He has a PhD from Harbin Institute of Technology and has published more 20 academic books, research reports, and more than 110 academic papers. He has presided over more than 20 national research projects, including projects funded by National Program 863, National Natural Science Foundation of China. He has served as chairman of academic conferences at home and abroad many times, and has been invited to give plenary speeches at LSE and other universities and important international conferences. He has served in various positions, including as Vice President of the Beijing Association for Science and Technology, Deputy Director-General of the China Science Writers Association, and Secretary-General of the CAST – Tsinghua University Center for Science and Technology Communication and Popularization. Xuan Liu is an Associate Research Fellow of the National Academy of Innovation Strategy, China Association for Science and Technology (CAST). She has received a PhD degree from the University of Science and Technology of China, During her PhD study, she was also a visiting PhD student in the London School of Economics and Political Science (LSE). She has presided as project head or participated in more than 30 international cooperation projects, national research projects and ministerial-level and provincial work. She has published more than 40 journal papers, conference papers and research reports in both English and Chinese as the first or corresponding author. From 2014 to 2018, she served as a member of the Scientific Committee of Public Communication of Science and Technology (PCST) and been invited to be keynote speaker at important

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international academic conferences. Her main research interests are the culture of science, public engagement with science, the innovation environment and ecology. Jianquan Ma is a postdoctoral researcher at the National Academy of Innovation Strategy and at Tsinghua University. She received a PhD degree from Tsinghua University, during her PhD study she was also a visiting PhD student at the Institut d’Études Politiques de Paris (Sciences Po). She has participated in more than 30 international cooperation projects, national research projects, and ministerial-level and provincial work. She has published more than 20 journal papers, conference papers and research reports in both English and Chinese as the first or corresponding author. Her main research area is scientific culture, innovative environment and science and technology policy.

Chapter 16

Science Communication in the New Era: Skills Education at Science and Technology Museums Xiang Li, Xuan Liu, and Peng Ren

Abstract As informal educational institutions with a long history, museums are attracting increasing attention from scholars in China and abroad for their functions of promoting the public understanding of and participation in science and boosting the public’s scientific literacy. Based on a historical review of the development of natural history museums, science and technology museums and contemporary science centres, this paper seeks to explore the direction of informal educational institutions represented by interactive science centres from the perspective of the demand for skills in scientific literacy. The background to and reasons for the formation of diverse forms of science venues in different periods are also explained. Keywords Science and technology museums · Museums · Science centres · Scientific literacy · Public participation

16.1 Introduction The development of science and technology (S&T) museums has gone through several stages: individual collections, natural history museums, science and industry museums, and science centres. In previous studies, many scholars have analysed the existing forms of S&T museums from the functional and conceptual perspectives, especially traditional natural history museums and the emerging science centres. However, as an important means of science popularization and a special place for presenting science, China’s S&T museums have now been given the task of improving the scientific literacy of all Chinese citizens. Therefore, the requirements for S&T museums will also change with the evolving concept of scientific literacy. Given the increasing value of S&T and the sustained demand for innovation, the demand for X. Li (B) · X. Liu National Academy of Innovation Strategy, Beijing, China e-mail: [email protected] P. Ren Beijing Yimu Animation Technology Co, Beijing, China e-mail: [email protected] © China Science and Technology Press 2021 B. Schiele et al. (eds.), Science Cultures in a Diverse World: Knowing, Sharing, Caring, https://doi.org/10.1007/978-981-16-5379-7_16

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skills takes up an increasing share in the content of scientific literacy, raising new requirements for S&T museums. Thinking about the national target of building a powerful country of science and technology, S&T museums now undertake more distinctive missions in supporting S&T innovation.

16.2 The Origins of Science and Technology Museums and Natural History Museums 16.2.1 International Origin: Collection, Research and Other Functions The word ‘museum’ comes from the Greek word ‘muse’, which signifies any one of a number of goddesses of science and art. The English word ‘muse’ is taken from the French verb ‘muser’ meaning ‘to think deeply’. This shows that the fundamental mission of museums as public spaces is to promote the understanding and progress of the collective (Schiele 2007). Although the functions of museums vary depending on the subject matter, the location and other factors, on the whole, all museums are dedicated to the missions of research, collection and exhibition (Burcaw 2011). In the early days of S&T museums, research and collecting were also their primary tasks. Particularly at the time when museums were dominated by traditions, their collections were not only of artistic and display value, but also contained first-hand information for research. Thus, in addition to being a source of knowledge, museums in this period should also be taken to be research institutions. The ‘cabinet of curiosities’ during the Renaissance could be considered the forerunner of S&T museums. Since the concept of science had yet to take shape, this period could be seen as the prehistoric era for S&T museums. At the end of the sixteenth century, natural history museums started to be built, and their unitary function of collecting gradually expanded to include the discovery and transmission of knowledge. Since the twentieth century and the establishment of science and industry museums, which had the mission of promoting the use of technology, and science centres, which focused more on interactions with visitors, public education became the main function of the museums. Except for natural history museums, all the science centres successively established since the mid-twentieth century have gradually weakened their collecting and research functions (Schiele 2007).

16.2.2 Chinese Categorizations and Naming of Science-Related Museums In China, the number of science-related institutions has increased sharply in the past three decades. A sound economic foundation has been important to support

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the building of S&T museums all around the country. The naming and design of the museums also reflects the distinct Chinese view of science, which has been inevitably influenced by the introduction of science into the country. The emphasis on the practical value of science made skills education an important task of science museums, although that training is usually the main job of other sectors, such as formal education and vocational training. According to the definition provided in the China science popularization infrastructure development report (2006–2010), museums in the field of S&T can be roughly divided into three categories based on the content of their exhibits: S&T museums (science centres), natural history museums, and specialized (industrybased) S&T museums (Ren and Li 2011). Since the 1980s, the construction of S&T museums in China has made rapid progress (in numbers at least), achieving nationwide coverage in just a few decades and laying a solid foundation for the dissemination and popularization of S&T at the science popularization infrastructure level. China Science and Technology Museum (Beijing) is a typical case. In the Chinese context, the term ‘science and technology museum’ is often equivalent to what is known internationally as a ‘science centre’ or an S&T museum that focuses on science education. The natural history museums in China are basically the same as their peers in the West, with only one slight difference in the disciplinary classification of the exhibits (Ren and Li 2011). In general, despite their different focuses and functions, S&T museums and natural history museums in China are similar to those in the West, and are all focused on the functions of S&T exhibition and education. At the same time, China also has a large number of industry museums. Although their names do not seem to have much to do with S&T, the contents of exhibitions in some industries are very closely linked with S&T. For example, in museums such as the China Railway Museum, the Beijing Automobile Museum and the China Maritime Museum in Shanghai, the exhibits are often the same as the ones displayed in science and industry museums in the UK and the US. In China, although they are also presented in the form of S&T products, the technological contents of the exhibits have not been given adequate exposure. In technology-intensive industries such as textiles and printing, the exhibits are often displayed as part of history and local culture in provincial museums, city museums and other comprehensive museums.

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16.3 New Requirements for Science and Technology Museums in the Age of Big Science 16.3.1 Dissemination of (Scientific) Knowledge is the Basic Function of Science and Technology Museums From the above review of the history of S&T museums, it is easy to see that even though functions such as collection (and preservation),1 research and display had all played a dominant role in different historical periods, contemporary S&T museums, similarly to other types of museums, are founded with the mission of disseminating scientific knowledge, principles and methods. Whether it is a natural history museum with exhibition as its main form or a science centre focusing on interactions, the dissemination of knowledge is always the basic mission. All their other functions (the promotion of culture, experience of science and participation in science) are developed on that basis. In the early stage of S&T museums, although the collection of artefacts and the display of identity were often the goals pursued by the exhibitors, the circulation of knowledge enabled by the appreciation of physical objects was also self-evident. After the birth of the natural history museums, the dual functions of collecting and research turned the museum itself into a source of scientific knowledge and activated the museum’s function of disseminating scientific knowledge. Then, with the opening of S&T museums, the greatest value of the exhibits was to present the achievements of S&T to visitors and change their perception of science, technology, engineering and other fields. Therefore, the dissemination of knowledge would happen naturally, no matter whether the planner’s goal was to enlighten the public or to advocate for the social groups they represented. In contemporary times, although some scholars have made a distinction between S&T museums that focus on display and science centres that emphasize interaction, and pointed to the various differences between the two types of museums in terms of philosophy and content, the dissemination of scientific knowledge is still the common goal and fundamental function of contemporary S&T museums (Durant 1992).

16.3.2 Supporting Scientific and Technological Innovation is the Future of Science and Technology Museums With the advent of the era of big science, science is no longer a personal act of scientists working behind closed doors, but a public undertaking that requires the financial and human resources of the whole society. As scientific knowledge has become a source of value creation, its production and dissemination are now receiving 1

To some extent, the Chinese word ‘collection’ in the museum field also partly indicates preservation and conservation.

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increasing attention. Scientific research itself is increasingly in need of huge financial support, and the proceeds from the application of scientific results are in turn supporting the development of the scientific undertaking. Therefore, the generation and dissemination of scientific knowledge cannot be regarded simply as the pursuit of knowledge itself. Factors such as the value of knowledge and the potential impact on innovation must also be considered (Zeng 2006; Li 2006). There is a growing demand for innovation, and the generation and circulation of knowledge may both affect innovation, and thus affect the behaviours that may produce results from which society can benefit. Therefore, S&T museums, as important places and means for the dissemination of scientific knowledge, must also think about their contribution to innovation. As an important way to disseminate S&T, and as institutions that are heavily dependent on government funding, S&T museums are duty-bound to provide services for innovation. As far as such a capacity is concerned, while undertaking the tasks of science communication in the national innovation system, S&T museums also need to pay attention to their own independent innovation in order to fit into the country’s overall innovation culture (Xu 2012). Such innovation includes not only updates of exhibition methods, forms and venues, but also a change in the contentbased approach to exhibition. The British scholar John Durant argued that, if natural history museums try to present a complete picture of science, serving a scientific feast in chronological order, science centres present it through fragmented knowledge, expecting the viewer to grasp scattered knowledge in a science buffet (Durant 1992). Reviewing that argument, which was made in 1992, in a contemporary perspective, it is clear that the innovation process—a part of science that has long been regarded as outside the realm of science—is missing from the picture. Although the great achievements of S&T are displayed in science and industry museums, the span from principle to finished product is so huge that the creative, innovative process of shaping knowledge often gets overlooked. While showcasing the sources and results of innovation, S&T museums rarely hold exhibitions on the process of innovation. It is like a good meal missing the invisible—the vitamin driving the advance of technology in contemporary society. Exhibitions on the theme of innovation provide the best entry point for the interaction between S&T and society and an important process by which science and technology make their impact on and receive feedback from society. Therefore, the exhibition of science and technology without the process of innovation is bound to be a one-sided show, not the display of ‘science itself’ envisioned by Durant. At the same time, S&T museums also undertake the important function of representing scientific culture, both as vehicles of the culture of science and as public cultural infrastructure. This is essentially different from other channels of science communication because, as the definers and bearers of a culture, the very existence of S&T museums gives expression to a culture called ‘science’. Such manifestation cannot be limited to the dissemination of information. On the contrary, it is necessary for S&T museums to integrate into the cultural system and answer the question ‘What is science?’ for the public. S&T museums are non-formal educational institutions, so the expression of science culture in the museums, unlike in textbooks,

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cannot be in the form of abstract definitions because, even if the definitions are constantly updated, they are still precise descriptions with clear boundaries; rather, S&T museums must present concrete ideas in order to help the public gain more direct experience of scientific knowledge, principles and processes and achieve a more holistic understanding of what science is.

16.4 Enhancing Scientific Literacy: A Common Goal of Science Popularization Venues at All Times Since the concept of ‘science literacy’ was introduced, its meaning has undergone continuous evolution through the arguments of successive generations of scholars. Some scholars have studied the evolution of the concept and discussed the role of S&T museums in enhancing scientific literacy (Ucko 1985). It is worth noting that most of those arguing for science literacy believe that skills should be included in the concept. Although there are still different interpretations of the term ‘skill’, it is widely recognized as an important component of science literacy. In the late 1980s, the Committee on the Public Understanding of Science (COPUS) set up working groups in key areas of public understanding of science. The team led by Richard Gregory, which focused on the study of interaction, noted the rapidly growing number of interactive science centres in the UK and published a collection of papers titled Sharing science in 1989. On that basis, COPUS decided to conduct further studies on the role of museums in the public understanding of science. In the autumn of 1990, the COPUS Museums Working Group was set up. Its research subjects included both specialized S&T museums and general museums offering science exhibitions (Durant 1992). It is evident that the contribution of S&T museums to the enhancement of scientific literacy has received much attention from the public understanding of science community and become an important area of research. Although some studies have concluded that the role of S&T museums in this field is limited (Frøyland 2000), there is still broad space for advancing such research. Such a phenomenon exists not just today. If we look at S&T museums in different periods from the angle of scientific literacy, we can also see a strong connection between the two.

16.4.1 The Period of Natural History Museums: The Public Was Required to Have Basic Scientific Literacy in Order to Receive Science During the period when science was far from being universally accessible, science, which was in its infancy, needed to present itself in order to gain wider recognition, including for scientific research and research results. It is precisely because the

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concept of scientific literacy had not yet been widely proposed, and the majority of the population was still poorly educated in science, that the scientific research process and its results could be packed into the limited space of the same museum, where the functions of collection and exhibition could co-exist, and the public, who knew nothing about science, could be easily satisfied with the acquisition of basic scientific knowledge. In other words, science at this time was still a high culture, far from being deeply connected with most people’s lives.

16.4.2 The Period of Science and Industry Museums and Science Centres: Scientific Literacy Became an Important Aspect of Cultural Quality After several rounds of industrial revolutions, the fruits of S&T have entered every part of our daily lives. As a result, the scope of scientific research was clarified, and there was also a surge in science-related information and news in the developing media. Science was no longer just the business of creating knowledge, but became a unique industry itself (Bauer 2010). As science developed into a more powerful culture, understanding science also became a necessity in our daily lives. The popularization of science, like the popularization of the written word, became an undertaking that needed no justification. Thus, the S&T museums that sprang up during this period included both science and industry museums that showcased the rich fruits of industrial development and science centres that gave the public a deep understanding of science through interactive experiences. Understanding science was the precondition for understanding society and acquiring the basic skills for survival. This expanded interpretation of scientific literacy led to the creation of science, technology, and science and industry museums that differed from natural history museums, such as the Science Museum in London, the German Museum in Munich and the Technical Museum in Vienna.

16.4.3 The Period of Demand for Innovation: Scientific Literacy Became a Necessary Condition for the Cultivation of Innovative Talent If scientific literacy is a requirement of the present, then scientific literacy driven by innovation is a requirement for the future. Scientific literacy is not only a means to ease the lives of individuals, but also a source of innovation and an important link in the innovation system. Therefore, a scientifically qualified person cannot merely survive in the society, but can also influence others and society as a whole. Understanding innovation is becoming an integral part of understanding science, and creating value with science is now a major component of contemporary scientific

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culture. Now that the science centres of today have turned science that only exists on paper and in legendary stories into a part of social construction, the science centres of the future will need to demonstrate the application of science and expand the scientific culture into a culture of innovation—or at least a culture that contains elements of innovation.

16.5 The Demand for Skills: Science and Technology Museums in Need of Transformation Influenced by the culture of innovation, ‘makerspaces’ and living labs are quickly emerging in China and abroad. They have shown us how innovation is driving the dissemination and sharing of knowledge. Of course, these new concepts are vastly different from museums in the traditional sense, in both their forms and their basic functions, and therefore cannot be simply and directly transplanted to the construction of S&T museums. However, it is worth noting that innovation-oriented knowledge and skills are becoming an increasingly common public demand and are the future direction for the expansion of science literacy. If we consider the evolution of the content of scientific literacy in different periods as an independent variable, then the form of S&T museums is a dependent variable that changes with it. It is necessary to re-examine the different forms of S&T museums born in different periods, with the demand for scientific literacy in mind, in order to see how they have been adapting to the culture of innovation.

16.5.1 Natural History Museums and Science and Industry Museums Natural history museums and science and industry museums have a long and profound cultural tradition, and all have ‘science’ in their names. Due to their long history and rich collections, these museums carry important cultural values of their own and are well positioned to disseminate what is suited for exhibition. Because of their focus on the word ‘museum’, they share similar traditions with general museums. As a kind of S&T museum, they correspond to the science museum’s own innovation in the innovation culture, including interactive displays in science centres, as well as exhibitions on the history of innovation and the innovation process. The key element is the essential feature of museums referred to in Sect. 16.5.1, which belongs in the category of ‘knowing’. Following this trajectory, we are likely to see the creation of an ‘innovation museum’ with innovation as its theme.

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16.5.2 Science and Technology Museums (Science Centres) Undertaking the mission of driving innovation and taking interactive participation as the primary means of exhibition, S&T museums (science centres) are focused on the transfer of skills rather than the mere dissemination of knowledge. Traditional museums (and most of the existing science centres) disseminate knowledge through exhibitions, including interactive exhibitions that are widely used in contemporary science centres to encourage public participation. However, such a process of dissemination still hardly involves the transfer of skills. The concept of interaction and the new technologies used are still an extension of the concept of ‘display’, and the desired result is just the presentation of content, which can be achieved through the transformation of traditional museums. The acquisition of skills is not an interactive process, but rather a process that requires repeated training, which involves a great deal of ‘tacit knowledge’ (OECD 1996). In the existing research literature on scientific literacy, there is no shortage of calls for more emphasis on skills (Ucko 1985): Scientific literacy can only be cultivated through the experience of attentive observation, not through verbal instruction. Explaining science and technology without proof is like teaching a man to swim without letting him go into the water. However, as the author then elaborates: The goals of exhibition can also be achieved by reading a book or watching TV, but the science and technology museum, through its displays, gives the public a real sense of participation in science and allows them to understand the way scientists see the world. This argument suggests that ‘skills’ in this context are not the ability to apply science, but the sense of immersive participation. The goal is still the faithful presentation of the image of science in the eyes of scientists and has nothing to do with the transfer of innovation skills. In other words, although getting a person into the water is the necessary precondition for him to learn to swim, it still requires the coach to teach him every move in person. The limitation of contemporary science centres is that they can provide the swimming pool but not hands-on coaching. Of course, the ‘coach’ in a science centre is not necessarily a figurative being, but more about the transfer of tacit knowledge that contributes to the enhancement of skills.

16.6 Conclusion Either for S&T museums with Chinese features or for museums commonly known as science centres around the world, a new path must be taken to meet the growing demands for skills—that is, the ability to innovate—in scientific literacy. As opposed to natural history museums, which are more ‘museum’-oriented, science centres are more focused on the extension of ‘science and technology’, especially on the practical

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demand of incorporating them into acts of innovation. If natural history and S&T museums provide a complete picture of the evolution of scientific culture, giving us a holistic view of science and creating a universal culture for innovation, then science centres need to place greater emphasis on providing relatively direct support for acts of innovation in society and pay more attention to the transfer of skills based on the dissemination of knowledge. Compared to the emphasis on ‘knowing’, as in other channels of science communication, these institutions, because of their own features, tend to focus more on ‘doing’. As a result, they will take a new path that differs from that of traditional museums in order to respond to the new demand for boosting scientific literacy in the new era. If a museum is seen as a temple where elite knowledge is stored and disseminated, then skills education usually has to give way to the transfer of coded knowledge and the unidirectional transfer of elite culture. In this case, science communication conducted inside the museums is consistent with communication under the deficit model. However, if a museum is seen as a forum for visitors to communicate, engage and increase their understanding (Chinnery 2012), then the reconfiguration of the cultural space is often followed by the transfer of the museum’s discursive power, and the broad-based and full participation of the public is the most distinctive feature of contemporary museums in performing their function of informal public education. In this context, skills education, with its emphasis on the transmission of tacit knowledge, must stand on the historical stage as an essential component of science communication in museums. This is not only a necessary requirement for guiding the development of existing S&T museums, but also the only way to review the theoretical history and practical experience of museum development. S&T museums, which belong to the family of natural science museums, must first follow the common empirical law that works for all museums, before demonstrating their distinctive features and unique social functions. The introduction of STEM, STEAM, core concepts and other educational concepts has provided the theoretical basis for Chinese S&T museums to connect with the world, some in a very short period of time, while engaging in rapid expansion. However, just as the original purpose of setting up science centres was to inspire people to devote themselves to and participate in the scientific process, hands-on, skills-based education is the foundation for the sustained operation of S&T museums. It also provides convincing evidence that physical exhibits are still needed in museums despite the availability of virtual reality and augmented reality. Skills-based basic education and advanced theoretical guidance should be developed in parallel, and the science communication function of S&T museums should be continuously improved through the mutual confirmation of theories and practices.

References Bauer M (2010) The science culture industry and its impacts. La Stampa, Italy Burcaw GE (2011) Introduction to museum work. Chongqing University Press, Chongqing

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Chinnery A (2012) Temple or forum? On new museology and education for social change. In: Ruitenberg C (ed) Philosophy of education. Philosophy of Education Society, Urbana-Cham paign, Illinois, pp 269–276 Durant JR (1992) Museums and the public understanding of science. Science Museum Frøyland EKHA (2000) The contribution of museums to scientific literacy: views from audience and museum professionals. Public Underst Sci 9:393–415 Fujun R, Zhaohui Li (2011) Report on development of China’s PST infrastructures. Social Sciences Academic Press, Beijing Guoping Z (2006) Science communication and popularization in the context of the national innovation system. Studies Sci Popularization 1:13–18 Li Z (2006) Generation of scientific knowledge and its evolution. Tsinghua University Press OECD (Organisation for Economic Co-operation and Development) (1996) The knowledge-based economy. OECD, Paris Schiele B (2007) Science centers for this century. China Science and Technology Press Ucko DA (1985) Science literacy and science museum exhibits. Curator: The Museum Journal 28(4):287–300 Xu S (2012) Reflections on the innovative development of science and technology museums (Part 1). Science & Technology Association Forum, 6

Xiang Li is an Assistant Research Fellow of the National Academy of Innovation Strategy, China Association for Science and Technology (CAST). He received his PhD degree from Tsinghua University in China (2017), studied in the London School of Economics and Political Science (LSE) as a visiting research student during his PhD study (2013–2015) and worked in the American Institute of Physics (AIP) during his early career (2018–2019). He has been studying in the field of science museums and science centres since his PhD research. Based on his academic training in the history of science and STS, he visited museums, science centres and related institutions (the Royal Society, for example) in the UK, the US, the EU, Africa and South America and interviewed many of their curators, scholars and explainers, which provided him with a great amount of original data. His current research interests are the culture of science; science museums and science centres; and the innovation environment. Xuan Liu is an Associate Research Fellow of the National Academy of Innovation Strategy, China Association for Science and Technology (CAST). She has received a PhD degree from the University of Science and Technology of China, During her PhD study, she was also a visiting PhD student in the London School of Economics and Political Science (LSE). She has presided as project head or participated in more than 30 international cooperation projects, national research projects and ministerial-level and provincial work. She has published more than 40 journal papers, conference papers and research reports in both English and Chinese as the first or corresponding author. From 2014 to 2018, she served as a member of the Scientific Committee of Public Communication of Science and Technology (PCST) and been invited to be keynote speaker at important international academic conferences. Her main research interests are the culture of science, public engagement with science, the innovation environment and ecology. Peng Ren is the chief sales officer of Beijing Yimu Animation Technology Company. He received his master’s degree from the University of Birmingham in the UK (2018) and obtained the tittle of Associate Museum Research Fellow in 2020. During his study in the UK, he investigated a number of museums and science centres around the country. He has been working in science popularization practice since coming back to China in 2018. He has been working on research into science museums and science centres in China and has already visited more than a hundred such institutions. Exhibits he has promoted were used broadly by museums and science centres such as

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the China Science and Technology Museum and Beijing Science Center. He has published many papers on science museums and science popularization studies.

Chapter 17

Science Museums: The Brazilian Case Luisa Massarani and Jessica Norberto Rocha

Abstract Over the past 30 years, Brazil has shown enthusiasm for science museums. However, due to the political crisis, important challenges are being imposed on science communication in the country. In this chapter, we present an overview of the recent history of science museums in Brazil and explore some of today’s critical issues, such as funding and public policies for science and technology communication initiatives, access and accessibility. This chapter has been based on documents and a bibliographical review, as well as on data produced by our research group. Keywords Science museums · Public policies · Diverse audiences · Access · Accessibility · Science communication

17.1 Introduction Brazil has witnessed a wave of enthusiasm for science museums over the past 30 years, during which time a few hundred new facilities have been built across the country. However, critical challenges have been faced, due mainly to the current political crisis. On the other hand, there has also been a growing tendency for science museum teams to try to extend their reach to more diverse audiences and to forge relations with publics who have not traditionally been frequent visitors. Ensuring that museum exhibitions and science communication itself encompass a diversity of voices, knowledge and social representations is, of course, not a simple task. This is particularly true in Brazil, which is a geographically immense country that grapples not only with economic and social inequalities but that has also seen constant shifts in its public policies in the areas of education, science and technology

L. Massarani (B) National Brazilian Institute of Public Communication of Science and Technology and Master of Communication of Science, Technology and Health, Casa de Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil J. N. Rocha Cecierj Foundation, Rio de Janeiro, Brazil © China Science and Technology Press 2021 B. Schiele et al. (eds.), Science Cultures in a Diverse World: Knowing, Sharing, Caring, https://doi.org/10.1007/978-981-16-5379-7_17

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(S&T), culture and, consequently, science communication, all in response to political changes and economic crises. This chapter traces a brief history of science museums in Brazil and presents an overview of the vulnerabilities that have been encountered in the construction of this field. We also reflect on the challenges faced in devising practices to enhance access and accessibility at these scientific–cultural spaces. In this text, we have adopted a broad view of the concept of science museums, following the understanding of the Brazilian Association of Science Museums and Centers, which include not only science museums and natural history museums but also interactive science centres, planetariums, zoos, aquariums and botanical gardens, all of which are institutions devoted to science communication.

17.2 A Brief History Until the mid-twentieth century, Brazilian science museums had ties to the field of natural history. They included the Real Horto (Royal Garden, founded in 1808; now the Jardim Botânico do Rio de Janeiro [Botanical Garden of Rio de Janeiro]); the Museu Real (Royal Museum, founded in 1818; now the Museu Nacional [National Museum]), also in Rio de Janeiro; and the Museu Emílio Goeldi (Emílio Goeldi Museum), in Pará; as well as specific technical collections, such as the Museu do Ouro (Museum of Gold), in Minas Gerais (Massarani and Moreira 2016). Generally speaking, those spaces followed the traditional design of museums that hold objects and collections meant for preservation and that are devoted to static, non-interactive exhibitions. In the 1920s, the anthropologist and science communicator Edgard RoquettePinto (1884–1954) founded the Department of Education at the Museu Nacional (National Museum), which is believed to be Brazil’s first such department attached to a museum. The unit was responsible for attracting a diverse public to the museum, beyond just the educated elite; additionally, it circulated natural history collections and educational pictures by lending them to schools (Lopes 1997; Moreira et al. 2008; Pereira 2010). The subsequent decades brought a number of initiatives to create science museums, most of which proved unsuccessful. José Reis (1907–2002), an important Brazilian science communicator, presented the Governor of São Paulo with a proposal in 1946 that would have established a science museum and centre for historical documentation with the purpose of safeguarding the memory of Brazil’s scientific heritage. Although Reis’s idea was well received, it was never implemented (Reis 1984). Other proposals to create dynamic science museums in Rio de Janeiro and São Paulo were advanced in the 1950s and 1960s.1 1

Starting in the 1920s, Roquette-Pinto began planning for the creation of a dynamic science museum, along the lines of the Deutsches Museum, according to a report by Francisco Venâncio Filho, who was also an advocate of interactive museums (Venâncio Filho 1995).

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In 1954, São Paulo newspapers began publishing stories about proposals to establish a science museum and planetarium in Ibirapuera Park.2 According to Reis, who also had a hand in that proposal, the by-laws and executive committee were actually drawn up for the museum, which took its inspiration from a number of institutions: Chicago’s Museum of Science and Industry, the US National Museum, the Palais de la Découverte in Paris, and the London Science Museum (Reis 1984).3 While the museum never came to full fruition, Brazil’s first planetarium was launched in the city of São Paulo in January 1957, in Ibirapuera Park. The Palais de la Découverte, in Paris, served as a model when the scientist Carlos Chagas Filho (1910–2000) presented a proposal to government authorities in Rio de Janeiro. In the 1950s, Chagas Filho entered negotiations with Pedro Calmon, president of the Universidade Federal do Rio de Janeiro (Federal University of Rio de Janeiro) about opening a science museum there (Massarani and Moreira 2016). The project’s goal was to ‘share scientific knowledge with the public at large, as well as to complement high school education by providing students with basic ideas, mainly regarding practical demonstrations’.4 The museum, which was intended to ‘present topics in physics, genetics, nuclear energy, tropical pathology, and some aspects of petroleum’,5 was never built. When the Universidade de Brasília (University of Brasilia) was created, the initial plan was to include a science museum6 —an idea that resurfaced many times over the years. Although this museum was officialized on paper in 2014, the facility has not yet been built.7 In 1961, a planetarium was established at the Escola Naval do Rio de Janeiro (Rio de Janeiro Navy School) so students could have classes in celestial navigation; the facility was also open to the public two days a week (Steffani and Vieira 2014). Under an agreement between the Ministry of Education and the Democratic Republic of Germany, another nine sets of planetarium projectors and equipment were imported; the first of them was the Planetário da Universidade Federal de Goiás (Federal University of Goiás Planetarium), which was set up in Central-West Brazil in 1970 (Steffani and Vieira 2014).8 Another product of this agreement was the Planetário do Rio de Janeiro (Rio de Janeiro Planetarium), which opened in 1970, around the same time that there was renewed talk about creating a Palácio de C&T (S&T Palace). Also in the 1970s, planetariums were inaugurated in the cities of Florianopolis (1971), Santa Maria (1971), Porto Alegre (1972), Brasilia (1974) and Curitiba (1978). In 1979, Bahia established the interactive Museu de Ciência e Tecnologia (Bahia Science and Technology Museum), based on the experiences of San Francisco’s Exploratorium; the team at the new centre was trained by a group 2

Diário da Tarde, 6 February 1954. Diário da Tarde, 6 February 1954. 4 Jornal do Commercio, Terceiro Caderno, 14 May 1961, p. 1. 5 Jornal do Commercio, Terceiro Caderno, 14 May 1961, p. 1. 6 Jornal do Brasil, 24 May 1961, p. 11. 7 Decreto No 34.838, de 13 de novembro de 2013 (Governo do Distrito Federal). 8 Other cities where planetariums also opened under this agreement were João Pessoa (1982), Campinas (1987) and Vitória (1995) (Steffani and Vieira 2014). 3

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from the US museum. Created by law from the State of Bahia in May 1977 and launched in the city of Salvador in February 1979,9 it seems to have been the first hands-on science centre in the Southern hemisphere, nine years before the Australian National Science and Technology Centre (Questacon). Other science museums opened in the 1980s, including the Centro de Divulgação Científica e Cultural (Centre for Science and Cultural Communication) in São Carlos (1982); the Espaço Ciência Viva (Living Science Space) in Rio de Janeiro (1983), which likewise had the support of the Exploratorium; the Museu de Astronomia e Ciências Afins (Museum of Astronomy and Related Sciences) in Rio de Janeiro (1985); and the Estação Ciência (Science Station) in São Paulo (1987) (Hamburguer 2001; Massarani and Moreira 2016). The 1990s saw an acceleration in the pace of the construction of science museums in Brazil; at least 45 new centres were inaugurated. They included the Museu de Ciência e Tecnologia (Museum of Science and Technology) at the Pontifícia Universidade Católica (Pontifical Catholic University) in Porto Alegre, Rio Grande do Sul (1993); the Espaço Ciência (Science Space) in Recife, Pernambuco (1995); the Casa da Ciência (House of Science) as part of the Federal University of Rio de Janeiro (1995); and the Oswaldo Cruz Foundation’s Museu da Vida (Museum of Life) in Rio de Janeiro (1999) (ABCMC 2009). Since then, various other science museums have been built around the country.

17.3 Public Policy in Science Communication in the 2000s In 2003, Brazil entered a political period grounded in social inclusion and the reduction of social inequalities, as the government moved to enact policies to popularize science and make it a more integral part of daily life.10 Those policies were accompanied by measures to improve science education and stimulate young people’s interest in science (Ferreira 2014; Massarani and Moreira 2016). The prime expression of those goals in terms of institutionalization was the 2014 creation of the federal Departamento de Popularização e Difusão de Ciência e Tecnologia (DEPDI; Office for the Popularization and Dissemination of Science and Technology), which was part of the Secretaria de Ciência, Tecnologia e Inclusão Social (SECIS; Department of Science, Technology and Social Inclusion), within what was then the Ministry of Science and Technology (which later became the Ministério de Ciência, Tecnologia, Inovações e Comunicações (MCTIC; Ministry of Science, Technology, Innovation and Communication). This office was charged with fostering a variety of initiatives to communicate science, which included opening new science museums and travelling facilities and lending support to existing ones; encouraging efforts in extension work 9 Decree no. 25,633, May 1977, Government of the State of Bahia. Available at: http://www.secti. ba.gov.br/modules/conteudo/conteudo.php?conteudo=28. 10 In Brazil and within the ministry, both ‘science communication’ and ‘popularization of science’ are terms that are used.

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and science communication, in conjunction with universities and funding agencies; advancing periodic research on the public perception of S&T and devising indicators in partnership with international initiatives; and promoting and supporting science fairs, Olympiads and competitions that would motivate creativity, innovation and interdisciplinarity (Moreira 2006). The Office for the Popularization and Dissemination of Science and Technology also worked to establish new science museums, expand existing ones and encourage travelling facilities by providing grants or through strategically directed actions, for example, in regions where there were few or no such scientific–cultural spaces. Federal public grants were offered to various sectors of society and generally received a good response. Demand for funding increased over the years as institutions from different regions of the country took an interest in science communication initiatives. Grant money was awarded on the basis of merit and feasibility, and emphasis was generally placed on projects that reflected the country’s geographical diversity. The first federal grant to support science museums in the scope of this public policy was released in 2003; some 340 applications were submitted, of which around 35 were approved. Another grant was announced in 2004, this one to help travelling science museums and centres that used appropriately equipped vehicles to travel through large cities or into the interior of the country. The Ministry of Science, Technology, Innovation, and Communication launched two other national grants to support science museums; some 480 projects were submitted in 2009, of which 110 were approved, while around 335 proposals were submitted in 2013, of which 80 received approval. From 2003 to 2015, other grants were offered that lent some form of support to science communication projects, while not focused specifically on science museums; they included but were not limited to initiatives conducted by science museums. The following grants were announced during this period: ‘Popularização da Ciência: Olhando para a Água’ (Popularizing science: looking at water; 2005); ‘Difusão e Popularização da C&T’ (Diffusion and popularization of science and technology; 2006, 2007, and 2013); ‘Popularização da Astronomia’ (Popularizing astronomy; 2008); and ‘Divulgação Científica para o Ano Internacional da Química’ (Science communication for the International Year of Chemistry; 2010). This push by the federal government prompted state governments, funding agencies and foundations to offer grants, primarily through S&T departments and state research funding agencies. For example, FAPERJ, the Rio de Janeiro state funding agency, provided at least one grant per year in the area of science dissemination and popularization from 2007 to 2014. In northern Brazil, in Amazonia, FAPEAM offered at least one grant focused on popularizing science every year from 2006 to 2015. In Minas Gerais, FAPEMIG put out one grant in 2007 and another in 2010. Reflecting diversified demand and distinct origins, those federal and state grants paved the way for the opening of science museums where no such cultural facilities existed, while the money was also used to enhance and help diversify existing initiatives. Furthermore, the grant projects made space for new and different management teams and voices that had previously enjoyed little space, because in the previous

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decades the structures for fostering these initiatives and public policies were more rigid and closed, and generally encompassed only groups that were already part of the system. In 2014, however, the average number of federal and state grants in the area of the popularization of science declined and no grants were earmarked specifically for science museums, reducing the quantity and quality of science communication initiatives promoted by those institutions. Grants were, however, available in 2014 in the area of science fairs and Olympiads. In 2015, a grant was offered for science communication for the International Year of Light. In 2016, 2017, 2018 and 2019, grants were announced for events related to the National Science and Technology Week; in 2018, one grant was offered for projects involving girls in the exact sciences, engineering sciences and computer sciences; in 2019, there was one targeted to science programmes in the schools. While applications for all of those grants could be submitted by science museum teams, applicants were not limited to such groups, and the funds were not aimed specifically at them or their initiatives. The field also suffered during this period with the closing of the Department of Science, Technology and Social Inclusion and its Office for the Popularization and Diffusion of Science and Technology, which had played essential roles in sustaining public policies in science communication. In 2016, the Ministry of Science, Technology, Innovation and Communication merged with the Ministry of Communications, and the office lost both status and funding; it was fully closed in 2019. Once funds became tighter and political power was lost, the upward trend in the growth and reinforcement of science communication initiatives witnessed during the first 15 years of the twenty-first century reversed itself, revealing the underlying vulnerability of science museums. Older institutions also closed around the same time, including two of Brazil’s first interactive museums: Bahia’s Science and Technology Museum and São Paulo’s Science Station. In an interview given in mid-2017, the president of the Associação Brasileira de Centros e Museus de Ciência (Brazilian Association of Science Museums and Centers), José Ribamar Ferreira, said that, of the 268 institutions listed in a guide drawn up by the association, he did not know how many were still open to the public.11 One counterpoint to this was the Museu do Amanhã (Museum of Tomorrow), which opened in Rio de Janeiro in December 2015. This museum project sparked controversies because, while led by private enterprise, it was in large part financed with public funds. The costly building was designed by Spanish architect Santiago Calatrava, and its construction was part of a likewise expensive, controversial project to renew the port region where the museum is located. Nevertheless, the Museum of Tomorrow has unquestionably drawn large numbers of attendees, many of whom have been first-time visitors to a science museum. The facility received some 25,000 guests during its opening weekend. Its future is currently shaky, precisely because it depends on public funds. 11

Museus e centros de ciências ameaçados no país. Ciência e Cultura, 69 (1):14–15. https://doi. org/10.21800/2317-66602017000100007.

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It was against this backdrop of both plunging funds for S&T and the breakdown of science communication policies that a sad, symbolic event took place: one week before the National Museum, Brazil’s oldest such institution, was set to commemorate its 200th anniversary, a massive fire destroyed the building and much of its holdings.

17.4 Accessing Science Museums in a Diverse Country It is vitally important that every opportunity afforded by science museums and centres benefits all members of society, because access, accessibility and inclusion in science communication initiatives is a citizen’s right. However, guaranteeing that right in a country of continental proportions and tremendous social diversity is a major challenge. With that in mind, science communicators in Brazil—practitioners and scholars alike—have endeavoured to ascertain who has true access to science museums, while they have also analysed the impact and the potential that these facilities have to foster a more inclusive society—one that invites diversity. Brazilian studies and reports on science museums have shown that around 80% of their annual public visitors come from schools, especially young children and teens. This is compatible with data presented by Patiño and collaborators (2019), who surveyed 123 institutions from 14 Latin American countries and found that approximately 70% of the public that engages in science communication practices comprises children (under the age of 12 years) and teens (ages 13 to 18). However, unequal access is an urgent issue in Latin America, Brazil included. A report by UNICEF warns that 61% of Brazilian girls and boys—roughly 35 million children—live in poverty; they are either monetarily poor, have been deprived of one or more rights, or both (UNICEF 2018). In another report, the agency states that more than 2 million children and teens between the ages of four and 17 are not in school (UNICEF 2017). While there is a dearth of empirical and theoretical research on exclusion at museums and other scientific–cultural spaces and in science communication initiatives in Brazil, the data on school exclusion and poverty suggests a serious lack of access. Under these circumstances, whether or not one has a real right to attend school or go to a science museum depends mainly on luck; that is, whether one is born into the right social stratum. Outside of school, access to science museums is still the privilege of specific sectors of Brazilian society, despite efforts to the contrary. A number of nationwide and region-wide surveys have shown that, although Brazilians display an interest in science topics and a desire to play a more active role in public decisions related to those topics, they are not frequent visitors to science museums and centres, either because there are no such facilities where they live or because their attendance is influenced or even determined by social factors, such as income, educational level and urban violence (OMCC 2006, 2008; CGEE 2017; 2019; Massarani et al. 2019). Nationwide surveys of the public perception of S&T conducted in Brazil have detected very limited access to science museums (CGEE 2019); only 8% of Brazilians

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45.0% 40.0% 35.0% 30.0% 25.0% 20.0% 15.0% 10.0% 5.0% 0.0%

2006

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Visited a library in the past 12 months Visited a zoo, environmental park or botanical garden in the past 12 months Visited an S&T museum in the past 12 months Took part in a science fair or Olympiad in the past 12 months Visited an art museum in the past 12 months Took part in National Science and Technology Week

Fig. 17.1 Percentages of interviewees who reported visiting a science or cultural communication space or participating at an S&T event in 2006, 2010, 2015 and 2019. Source CGEE (2019:15)

reported visiting this type of scientific–cultural space in the previous 12 months (Fig. 17.1). This figure was in fact lower in the past (4% in 2006), but tripled in 2016 and then dropped again. Since the decrease occurred after the government curtailed the public policies that were driving the sector, we can conclude that those policies had been effective. A greater number of visitors attended other scientific– cultural spaces, such as zoos, environmental parks and botanical gardens—a figure that peaked at 40% but then fell to 25% in the latest study. In June 2019, Brazil’s Instituto Nacional de Ciência e Tecnologia em Comunicação Pública da Ciência e Tecnologia (National Institute of Science and Technology in the Public Communication of Science and Technology) released data corroborating the national surveys. The study focused on young people aged 15 to 24 years across all regions of Brazil. Only 6% of those interviewed reported having visited a museum or science centre in the previous year; the study also found that participation in scientific and cultural activities was low. Libraries were visited most often (35% of respondents), followed by botanical gardens or environmental parks (17%). The authors point out that ‘generally speaking, these percentages are quite low when compared to surveys in other countries, especially if we take into account the age of those interviewed’ (Massarani et al. 2019a:8). According to the report on the survey, the main reasons interviewees gave for not visiting did not reflect a lack of interest; rather, a large proportion of the respondents said they had not visited any museum

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or science space simply because there were none where they lived (Massarani et al. 2019a).

17.5 Travelling Science Museums and Centres The question thus remains: how can we serve the needs of the large numbers of people who do not visit science museums and centres because there are none where they live or because, for some social reason, they do not fit the profile of the traditional museum public? Moreover, science museums in Brazil face a problem with sustainability, since most have ties to the government or public institutions and charge no admission fees. At the same time, it is often easier to obtain funding for a new museum, which affords its sponsoring institutions an opportunity for initial visibility, than to maintain one. Smaller cities find it particularly hard to open their own museums. Travelling facilities have offered an alternative path that can mitigate these challenges. The mission of a travelling science museum is to provide access to science communication initiatives and high-quality science information to those who have none. In urban environments, travelling facilities generally set up camp in a public area without walls and serve people who pass through, free of charge. They can also travel to the urban outskirts or out-of-the-way places, to areas where violence is common, or to areas where people have no opportunity to visit a science communication or cultural environment. Travelling science museums and centres are therefore a powerful tool for democratizing knowledge and, consequently, fostering inclusion. After the 1950s, through UNESCO of Brazil and the expansion of the fields of museology and science communication, this type of travelling project was incentivized both directly and indirectly, as indicated by Trigueiros (1958), who discussed the international practice of travelling exhibitions and travelling museums using a number of UNESCO documents. However, it was his contention that the proposed UNESCO project would be costly and labour-intensive in Brazil; his proposed solution was to design a bus-museum rather than adapt a truck. The Museu Itinerante José Hidasi (José Hidasi Travelling Museum) was the first example of a travelling science museum using a vehicle as its main structure (Norberto Rocha and Marandino 2017). The travelling museum, which opened in Goiania, Goiás, in 1965, was kept on the road for 20 years by its founder, José Hidasi, a Hungarian naturalist, ornithologist and taxidermist. The goal of the museum, which has since closed, was to popularize the biological sciences through an exhibition of various animal species titled ‘Curiosidades da Natureza’ (Curiosities of Nature) (Xavier 2012). In the 2000s, one notable initiative was the Projeto de Museu Itinerante (Promusit; Travelling Museum Project) sponsored by the Museu de Ciência e Tecnologia do Rio Grande do Sul (Rio Grande do Sul Museum of Science and Technology). Inaugurated in 2001, the project drew inspiration from the Science Circus at Australia’s Questacon (the National Science and Technology Centre). Its main infrastructure is a wagon

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that carries around 60-module exhibitions; once unloaded, the structure becomes an auditorium for science communication activities. This successful experience has motivated similar projects around Brazil. In 2004, a grant for the Projeto Ciência Móvel (Travelling Science Project) marked the institutionalization of this idea. Some 50 applications were submitted, all involving vehicles. The grant funded the implementation of nine projects across the country. Financed as part of the national public policy mentioned above, which directed grant funding to a minimum of 60 other projects from 2003 to 2015, these travelling museums and science centres employed a variety of vehicles (wagons, buses, mini-buses and vans) to transport activities and exhibitions beyond the country’s large urban centres to the urban periphery, small towns, medium-sized cities and rural areas where children, teens and adults could be stimulated to learn about the universe of science and take an interest in it. The initiatives have generally been tied to universities’ extension work, science communication sectors or museums at universities, research institutes and foundations, although some also operate through private initiatives, NGOs and social services. According to a survey by Almeida and collaborators (2015), Brazil had 32 travelling science communication projects. Norberto Rocha and Marandino (2017) charted 34 travelling museums and science centres using some type of vehicle as their main infrastructure. While Brazil has a significant number of travelling museums and science centres that have covered millions of kilometres, scholars have done little research on those facilities, and few records are available on their creation, design, funding, activities or evaluations. Museum teams themselves have compiled the scant existing documents, which often are not complete enough to adequately cover the complexity of the initiatives undertaken. Further research and more studies are needed on these spaces and their activities, and their histories must be registered. We must answer these questions: How has the mission of science communication been conducted? Can travelling science museums contribute to the inclusion of visiting populations and their relationship with S&T? How might that be accomplished? What do these institutions offer the public that might leverage that process?

17.6 Accessibility Data collected in the most recent population census of the Brazilian Institute of Geography and Statistics (2010) shows that 6.7% of the population (around 12.7 million people) have great difficulty or are unable to perform basic functions and activities in any way because they are people with disabilities (Botelho and Porciúncula 2018).Those individuals come from all social spheres and include children, young people, adults, students, professionals, scientists, politicians, teachers, professors and residents of both large cities and small rural towns. However, only more recently have they been explicitly considered as a potential public for science museums.

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In 2015, Brazil passed its newest persons with disabilities legislation, titled Lei Brasileira de Inclusão da Pessoa com Deficiência (Inclusion of people with disabilities). The law defines accessibility as ‘the right that guarantees that people with a disability or reduced mobility can live independently and exercise their citizenship and social participation rights’ (Brasil 2015). A product of social pressure, the law was influenced by the UN Convention on the Rights of People with Disabilities (2006). Yet, despite the new legislation, Brazilians with disabilities continue to confront myriad barriers in accessing science communication, not only because science museums do not exist where they live, but mainly because a culture of accessibility and inclusion has not yet taken a firm hold at those institutions. Although Brazilian museums have gradually developed strategies, programmes and policies of inclusion and service for the public with disabilities, those programmes still need to become part of the facilities’ stated missions and more than just the sum of an individual’s learning. In 2016, the research group Accessible Science Museums and Centers worked with the Latin American Caribbean Network for the Popularization of Science and Technology (RedPOP) to develop a survey of the regions’ science museums to help ascertain how they address accessibility. The replies received from institutions in 12 countries showed an increased concern about the engagement of people with disabilities in S&T issues at science museums and centres. This effort also culminated in the Guide of accessible science museums and centers from Latin America and the Caribbean (Norberto Rocha et al. 2017a), which contains information about each institution’s self-reported accessibility strategies and practices. An analysis of the total of 109 Latin American museums that responded to the survey found a significant gap between policies and good intentions, on the one hand, and active, systematic practices for promoting full and equal enjoyment, on the other. We noticed that most of what was done to advance accessibility involved changes to institutions’ physical infrastructures—a strategy that in and of itself does not guarantee active inclusion. In the realm of communicational and attitudinal accessibility, for example, participant museums are still doing little to reach people with disabilities or address accessibility issues. One of those barriers is the lack of institutional practices aimed at accessibility and inclusion, which would entail, for example, the allocation of financial resources towards needs ranging from alterations in architecture and exhibition design to human resource training. There is evidence that staff at many science museums realize they are ill-equipped to effectively meet the needs of people with disabilities (Norberto Rocha et al. 2020). Carlétti and Massarani (2015) also concluded that museum personnel are not adequately trained to serve publics with disabilities and, as a result, they feel insecure when interacting with those individuals. In a survey of 370 mediators at 200 Brazilian scientific–cultural spaces, around 60% reported feeling unprepared to serve people with disabilities. Data from both the Latin America–wide and Brazilian studies show there is a strong demand to train human resources such as mediators, educators and science communicators in how to serve people with disabilities and also for managers, directors, curators and scientists to learn how to propose initiatives tailored to people with disabilities.

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At the same time, more research has been done on accessibility in Brazil over the past 20 years. In academia, new graduate-level opportunities began emerging in 2000, making room for new lines of investigation in the field. But Brazilian scientific production specifically dedicated to science communication still needs to expand and take stronger root. In 2017, we surveyed articles published on the topic of accessibility at museums and scientific–cultural spaces and on science communication activities by Brazilian authors and found that only a few articles had been published in this field, and only more recently (the first published article is from 2006). Our findings also suggest that a wider range of topics, accessibility strategies and disabilities must be addressed and that more in-depth research must be done, especially targeting journals of greater relevance and impact (Norberto Rocha et al. 2017b).

17.7 Final Considerations Brazil has had science museums for more than 200 years, although the field has become more robust only in the past 30 years, as reflected in the opening of at least 200 museums, the definition of public policies, and the foundation of the Brazilian Association of Science Museums and Centers in 2000. Over the course of their history, Brazilian science museums have seen good times and bad in the realms of preservation, funding and public policy. This has had much to do with a historical context in which a changing country with a young democracy has wavered in its public policies that value culture, education, S&T and science communication. Over the past 30 years in particular, new museums have opened for a range of publics, moving towards the inclusion of diverse populations. Yet, despite this gradual shift and the increasing efforts to reinforce inclusion, many people are still left out: those with lower educational levels, those who have not had the chance to attend school, those who live far from large urban centres or where there are no science museums, those with disabilities, the poor, and those who do not feel socially included in this universe. A decade of public policies aimed at social inclusion and at the development and communication of S&T, driven first by the ministry of science and then, on a smaller scale, by state governments, showed how the science museum sector can be stimulated. However, the withdrawal of those policies had a fast, deep impact in the form of programme discontinuity, a lack of conservation and preservation, the interruption of research and other studies, lay-offs and even definitive closings, with buildings and collections being handed over to others and memory being destroyed. Years of hard work are rapidly being undone, while we know what a slow process it is to build the sector up. For this reason, it is vital to sustain policies on stable, long-term foundations.

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Luisa Massarani is a Brazilian science communicator who carries out both practical and research activities in the field. She is the coordinator of the National Brazilian Institute of Public Communication of Science and Technology, the Master in Science Communication at the House of Oswaldo Cruz/Fiocruz (Brazil) and for Latin American SciDev.Net. She is a recipient of the Mercosur Award for Science and Technology (2014), the Brazilian Award for Science Communication (2016) and the Literature Jabuti Award (2017). Jessica Norberto Rocha is a Brazilian science communicator at Cecierj Foundation (Science Centre and Distance Higher Education of the State of Rio de Janeiro) and Faperj Young Scientist of the State of Rio de Janeiro. She is a researcher of the National Brazilian Institute of Public Communication of Science and Technology and CYTED Musa Iberoamericana: Iberoamerican Network of Science Museums and Centres. She is also a professor of the master’s degree in the communication of science, technology, and health at Oswaldo Cruz Foundation (Fiocruz) and a Fulbright Visiting Scholar grantee.

Science Cultures in a Diverse World Knowing, Sharing, Caring

Bernard Schiele, Xuan Liu, Martin WBauer (editors). Science and technology culture is now more than ever at the very heart of the social project, and all countries, to varying degrees, participate in it: raising scientific literacy, improving the image of the sciences, involving the public in debates and encouraging the young to pursue careers in the sciences. Thus, the very destiny of any society is now entwined with its ability to develop a genuine science and technology culture, accessible for participation not only to the few who, by virtue of their training or trade, work in the science and technology fields, but to all, thereby creating occasions for society to debate and to foster a positive dialogue about the directions of change and future choices. This book organized on the theme of ‘knowing, sharing, caring: new insights for a diverse world’, which was derived from the observation that globalization rests upon diversity—diversity of contexts, publics, research, strategies and new innovating practices—and aims to stimulate exchanges, discussions and debates, to initiate a reflection conducive to decentring and to be an opportunity for enrichment by providing the reader with means to achieve the potentialities of that diversity through a comparison of the visions that underpin the attitudes of social actors, the challenges they perceive and the potential solutions they consider. Thus, this book aims first and foremost to raise questions in such a manner that readers so stimulated will feel compelled to contribute and will do so. In this spirit, however significant, the results presented and shared are less important than the questions they seek to answer: How are we to rethink the diffusion, the propagation and the sharing of scientific thought and knowledge in an ever more complex and diverse world? What to know? What to share? How do we do it when science is broken down across the whole spectrum of the world’s diversity?

© China Science and Technology Press 2021 B. Schiele et al. (eds.), Science Cultures in a Diverse World: Knowing, Sharing, Caring, https://doi.org/10.1007/978-981-16-5379-7

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