Complexity Sciences: Theoretical and Empirical Approaches to Social Action 152750901X, 9781527509016

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Complexity Sciences

Complexity Sciences: Theoretical and Empirical Approaches to Social Action Edited by

Manuel Lisboa and Dalila Cerejo

Complexity Sciences: Theoretical and Empirical Approaches to Social Action Edited by Manuel Lisboa and Dalila Cerejo This book first published 2018 Cambridge Scholars Publishing Lady Stephenson Library, Newcastle upon Tyne, NE6 2PA, UK British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library Copyright © 2018 by Manuel Lisboa, Dalila Cerejo and contributors The review was made with the support of CICS.NOVA - Interdisciplinary Centre of Social Sciences of the Universidade Nova de Lisboa, UID/SOC/04647/2013, with the financial support of FCT/MCTES through National funds. All rights for this book reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior permission of the copyright owner. ISBN (10): 1-5275-0901-X ISBN (13): 978-1-5275-0901-6

TABLE OF CONTENTS

Chapter I ...................................................................................................... 1 Introduction: Sociocybernetics Framework Chaime Marcuello-Servós Chapter II ..................................................................................................... 7 A Sociocybernetic Approach to Enhancing Research Reflexivity: An Epistemology Model for Social Analysis José A. Amozurrutia Chapter III ................................................................................................. 46 Proposal for the Development of a Thinking Culture as a Large System Formed by Multiple Sub-systems Margarita Maass Chapter IV ................................................................................................. 65 Complexity and Social Actions: Interaction and Multiple Systems Leandro Aramburu and Chaime Marcuello-Servós Chapter V .................................................................................................. 79 Reflections on the Sociocybernetics of Social Networks Bernard Scott Chapter VI ................................................................................................. 88 Man, Motivation and Emotion at Work in Organizations: Behaviour, Action and Emotion in a Multi-System Environment Bernd Hornung Chapter VII .............................................................................................. 125 Reasoning on Emotions: Drawing an Integrative Approach Ana Ferreira Chapter VIII ............................................................................................ 140 Toward an Intersystemic Analysis of Gender-Based Violence Manuel Lisboa

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Chapter IX ............................................................................................... 155 Emotional Expression Indicators as a Systemic Approach to Exploring Social (Inter)Action: The Case of Portuguese Intimate Partner Violence Victims Dalila Cerejo Chapter X ................................................................................................ 173 Gender Violence in Spain: A Qualitative and Systemic Approach José A. Amozurrutia, Santiago Boira, María F. del Castillo and Chaime Marcuello-Servós

CHAPTER I INTRODUCTION: SOCIOCYBERNETICS FRAMEWORK CHAIME MARCUELLO-SERVÓS

Sociocybernetics is a strange word. There are few people who understand its meaning, history and scope. It is a neologism created in the mid-80s of the past century. The editor of a collection of papers, Felix Geyer, coined it in cooperation with his publisher. In 1998, during the World Congress of Sociology at Montreal, the executive committee of the International Sociological Association (ISA) established the Research Committee 51 (RC51) on Sociocybernetics as the last step of a long process initiated in the ’80s with the Ad Hoc Group by Francisco Parra-Luna. Considering this institutional process, Sociocybernetics could be understood as the target and object of the RC51 and the people involved in its activities. Sociocybernetics is the result of the “sociocyberneticians”, but this answer drives us into a circular definition, which requires a second-order observation. Moreover, in a first attempt, if we are inside the ISA logics, Sociocybernetics could be understood as a field in Social Sciences, like Family Research (RC06), Sociology of Education (RC04), Social Indicators (RC55) or any other of the current fifty-six research committees on the ISA. However, as Bernd Hornung has proposed several times in different conversations and conferences: “Sociocybernetics is not a particular field; it should be defined as a paradigm” because it is a way of thinking and doing social sciences. In practice, the RC51’s own definition can help to comprehend this notion. Sociocybernetics can be defined as “Systems Science in Sociology and Other Social Sciences” – systems science, because sociocybernetics is not limited to theory but includes application, empirical research, methodology, axiology (i.e., ethics and value research), and epistemology. In general use, “systems theory” and “cybernetics” are frequently

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Chapter I interchangeable or appear in combination. Hence, they can be considered as synonyms, although the two terms come from different traditions and are not used uniformly in different languages and national traditions. Sociocybernetics includes both what are called first order cybernetics and second order cybernetics. Cybernetics, according to Wiener´s original definition, is the science of “control and communication in the animal and the machine”. Heinz von Foerster went on to distinguish a first order cybernetics, “the study of observed systems”, and a second order cybernetics, “the study of observing systems”. Second order cybernetics is explicitly based on a constructivist epistemology and is concerned with issues of self-reference, paying particular attention to the observerdependence of knowledge, including scientific theories. In the interdisciplinary and holistic spirit of systems science, although sociology is clearly at the centre of interest of sociocybernetics, the other social sciences, such as psychology, anthropology, political science, economics, are addressed as well, with emphases depending on the particular research question to be dealt with.1

This long quote must be reread and reconsidered. Sociocyberneticians want to recognize the link with “systems science”. This first is one of the three main roots. The resonance with Bertalanffy's general system theory,2 Kenneth E. Boulding and many others such as Parsons and Luhmann is clear. The second is “cybernetics”. This was another new term. It was the title of Norbert Wiener’s book Cybernetics: Or Control and Communication in the Animal and the Machine published in 1948. The third root is “second order cybernetics”, as von Foerster (2003) proposed. At this point, it is useful to paraphrase his words: “Sociocybernetics’ description is nothing but Sociocybernetics”.3 These three pillars underpin Sociocybernetics – as in the construction of the knowledge paradigm of Rolando García (2000) inspired by the genetic epistemology of Jean Piaget – and as in the work of social scientists practising “the emerging sciences of complexity”. According to von Foerster, when you learn and become interested in cybernetics, “definitions are not good”.4 And he continued by saying, “Don’t ask, what is ‘cybernetics’? Ask, when is cybernetics?” Maybe, 1

See the website of the RC51 https://sociocybernetics.wordpress.com/about/whatis-sociocybernetics/ or http://sociocybernetics.unizar.es/whatis.html 2 1968, General System Theory: Foundations, Development, Applications, New York: George Braziller. 3 The original words are: “We can use the insight that computing a description is nothing but computing. This way we reach a final paraphrasing of the forever renewed process of knowledge acquisition” (von Foerster, 2003, 232). 4 Listen to the voice of Heinz von Foerster directly in 2’40” at: https://www.youtube.com/watch?v=GWcyHbmsXS0

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that’s the same in the case of Sociocybernetics: a way of looking at things while conscious of the circularity of communications that produces effects in social systems and in individuals. This is the framework for this book. It is a collection of papers selected from the communications of the 11th International Conference of Sociocybernetics celebrated at the Algarve University in Faro (Portugal). Complexity and Social Action: Interaction and Multiple Systems was the theme for the conference and is the focus for this book. Then, as now, recent events in different contexts of the world force us to think better and create new theory settings, new approaches and new insights into the current social dynamics that many consider to be on the verge of rupture. If, at the height of the recent global crisis, financial issues, social uprisings, forced government collapses and increasing inequalities within several spheres of the social world were some of the events that necessarily put collective and individual social action into new perspectives, recent events like the war in Syria, the refugee crisis, Brexit and the election of Donald Trump are similarly challenging. Sociocyberneticians propose that it is no longer possible to think of social phenomena in a disconnected way, since their foundations and limits are not clear. The understanding of social action and interaction, as cause and consequence of social phenomenon, depends on the capacity to consider and analyse all possibilities in action systems, their diversity and relations integrating micro, macro and meso perspectives. It is therefore, imperative for the sociocybernetic approach to address such a challenge.

These pages address that challenge. The book is divided into ten chapters, including this introduction, that show the interaction between multiple systems and topics, using sociocybernetic ways of thinking and transdisciplinary approaches. José A. Amozurrutia presents “A sociocybernetic approach to enhancing research reflexivity: An epistemology model for social analysis” and proposes an operationalization of Jean Piaget’s genetic epistemology for the analysis of research activity in social projects. He considers that epistemology is grounded on the construction of general knowledge, and applies it to the cognitive processes of social agents in their research activity. Its main use takes the form of a construction and development knowledge field model, oriented to finding possible paths and equilibration trajectories in system development processes. Margarita Maass offers a “Proposal for the development of a thinking culture as a large system formed by multiple sub-systems”. Focusing on

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Chapter I

Mexico as a multicultural and diverse country, she is concerned primarily with a proposal for the development of a thinking culture as a large system formed by multiple sub-systems. She describes how sociocybernetics helps us understand and explain culture as an ethno-ecosystem. Moreover, she explains how sociocybernetics allows us to construct a methodology for facilitating an emerging community of local knowledge system. Leandro Aramburu and Chaime Marcuello-Servós put forward “Digital generation, emotions and social movements: A conceptual framework”. The authors explore, first, information and communication technologies and their contextual consequences; second, some conceptual milestones for understanding how the digital generations are building a social architecture where emotions and meanings are supported by a different way of doing and thinking; and third, a theoretical framework is proposed that conceptualizes and describes the effects of the “internetization” and “digitalization” of our lives and, especially, its effects in the emergence of social movements. Bernard Scott presents “Reflections on the sociocybernetics of social networks”. He uses concepts from sociocybernetics to explore how the term “social network” is used, asks what is social about a social network and argues that what is usually intended are forms of reciprocity between social actors and the expectation structures that underpin them. In his paper, Scott goes on to consider the various forms that social networks may take and discusses related topics, such as social network, social system, social media, social empowerment, and the form of the emerging global conversation. Bernd Hornung’s contribution is focused on “Man, motivation and emotion at work in organizations – Behaviour, action and emotion in a multi-system environment”, using the example of a university hospital as a particularly complex system. The chapter outlines a number of possible problems resulting from such a multi-system situation at the level of the individual working in such a context. He uses research on emotions in organizations, recent trends in the development of health problems in the working population and, last but not least, the phenomenon of burn-out. The author concludes with a number of suggestions about how work satisfaction might be promoted and developed by running a business organization in a sociocybernetically informed way. Ana Ferreira addresses “Reasoning on emotions: Drawing an integrative approach”. She discusses Barbalet’s theoretical perspective on emotions and António Damásio’s work to show that socially imprinted non-conscious physiological variables are available to actors facing uncertainty, allowing unconscious decision-making when rational and

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conscious analysis is impossible. As she says, by “not precluding knowledge specialization, but rather, crossing socially-constructed disciplinary boundaries, we aim to gather a deeper understanding of social action”. Manuel Lisboa’s theme is “Toward an intersystemic analysis of gender-based violence”. He proposes an analysis of gender-based violence against women supported by systems theory, the result of questions raised over the last 20 years in the course of several studies of violence against women. He proposes a holistic and systemic analysis of the phenomenon. According to this analysis, we must consider three dimensions: (i) the study of the relationship between structural traits, both social and cultural, and the individual actors’ actions; (ii) the relationship between the rational control of these actions and the emotional factors also present; and (iii) how the social actors directly involved in acts of violence act according to their own syntheses of all existing constraints. Lisboa considers the first two aspects. Dalila Cerejo’s chapter is concerned with “Emotional expression indicators as a systemic approach to exploring social (inter)action: The case of Portuguese intimate partner violence victims”. The aim of the chapter is to identify the reasons why victims stay with the abuser, sometimes during long periods of victimization. The author uses emotional expression indicators (EEI) detection in intimate partner violence (IPV) contexts. As she says, IPV is a complex social phenomenon and a multidisciplinary and systemic approach is considered crucial to unveiling more about the factors that create it. José A. Amozurrutia, Santiago Boira, María F. del Castillo and Chaime Marcuello-Servós describe “Gender violence in Spain: A qualitative and systemic approach”. The chapter offers a qualitative and systemic approach to gender violence and its recent evolution in Spain. Spanish society has experienced a deep transformation in the last three decades. The authors analyse the context and focus on its consequences for sex roles and gender violence. They studied these phenomena heuristically, considering the discourses of aggressors, victims and professionals directly involved in the problem. The authors find that fear, amongst other things, is the main feature of the symbolic universe around gender violence, in the period after the 1/2004 Integral Protection Measures against Gender Violence Act. This variety of chapters and authors provides a sample of the activities of sociocyberneticians. We hope you enjoy reading the book and encourage you to reflect on how the chapters interact. Sociocybernetics

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Chapter I

can be seen as a self-reproducing and evolving system in which people, ideas and findings interact in an autopoietic way.

Works Cited García, R. (2000). El conocimiento en construcción. Barcelona: Gedisa. von Bertalanffy, L. (1968). General System Theory: Foundations, Development, Applications. New York: George Braziller. von Foerster, H. (2003). Understanding: Essays on Cybernetics and Cognition. New York: Springer-Verlag. Wiener, N. (1948). Cybernetics: Or Control and Communication in the Animal and the Machine. Cambridge: MIT Press.

CHAPTER II A SOCIOCYBERNETIC APPROACH TO ENHANCING RESEARCH REFLEXIVITY: AN EPISTEMOLOGY MODEL FOR SOCIAL ANALYSIS JOSÉ A. AMOZURRUTIA

In this chapter, I propose an operationalization of Jean Piaget’s genetic epistemology for the analysis of research activity on social project analysis. Although this epistemology is grounded on the construction of general knowledge, I applied it to the cognitive processes of social agents in their research activity. Its main use is a construction and development knowledge field – CDKF – model that is oriented to finding possible paths and equilibration trajectories in system development processes. We put this into practice by following the work of five academic research projects hosted by the LabCOMplex (CEIICH/UNAM) in Mexico. These researchers have been using the Adaptive System – SiAs in Spanish – strategy proposed by the author since 2007. The use of this system features a strong emphasis on second order reflexivity in terms of the cybernetics of cybernetics (von Foerster, 1973 and Scott, 2011) and on heuristic methodology, based on a sociocybernetic perspective (Geyer, 1995, 2005 and Hornung, 2006 a and b). The heuristic methodology applied to this research is further supplemented with interdisciplinary research activity derived from the Cibercultur@ approach (González, Maass and Amozurrutia, 2007), which gives special attention to system thinking, distributed intelligence and dialogical communication between observed researchers and my own reflections and observations of them. My final goal is to use the CDKF model to represent the dynamics of cognitive processes during research activities. In the first part, I provide a brief overview of sociocybernetics and Cibercultur@ strategies; I then make use of Piaget’s theoretical corpus

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from which the CDKF model evolved and apply it to social research. In the second part, I summarize the observed researchers’ projects, challenges and contexts for dealing with social projects through system thinking. In the third part, I describe CDKF model construction, and end with its application in a case study analysis.

1. Introduction 1.1. The observer and the problem In the past five years, my attention has been drawn to attentive and thoughtful attitudes towards knowledge developed by social problem observers who carry out their activities through social and systems thinking. This interest stems from a commitment to interdisciplinary research within a segment of Cibercultur@ and my own second order observations, which convinced me of the benefits of applying the sociocybernetic approach to social reflexivity. From this perspective, I’ve posed several questions about the types of challenges researchers must overcome, as well as sought new forms of concept assimilation and strategies for category integration, both of which are focused on a better understanding of problems and social explanations. My reflections follow von Foerster’s and Piaget’s systemic thinking, Piaget’s and García’s epistemological thinking, and Bourdieu’s and Moscovicci’s social thinking. Von Foerster, Piaget and sometimes García are the main references to the systemic models – SiAs – I`ve constructed and applied in different social analysis projects. In this chapter, my research focuses on Piaget`s genetic epistemology organized as an analytical research unit within a systemic consolidation into a unit of analysis that operates in a computer program, which I will apply to six case studies. In the analytical research unit, understood as a hierarchical category construction, lies the intuition that as we achieve better forms for constructing and/or developing knowledge, we will gain a better understanding of the key cornerstones of social analysis. Complementing second order reflexivity, I include two essential components of Piaget’s genetic epistemology in the CDKF model: a multidialectical process conception in the balancing process of regulations and compensations, and the alpha, beta and gamma mechanisms in compensations. These are key to establishing relationships between the three mechanisms and organizing the CDKF model within a system/environment co-evolutionary process.

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The cybernetics of cybernetics, that is, systemic thinking within the conception of the research project as a complex system, is at the same time the main activity developed in model construction and its application to social analysis processes. My observation is oriented toward the researchers’ reflexivity. As a second order observer, I analyse Piaget`s subject-object interaction mechanisms between the researchers’ activity with their object of study, or, more precisely, with the object of construction. The latter is simultaneously another social actor observing more actors. This chain of researcher observations includes reflexivity on subject-object perturbation and the presence of blind spots. From this point of departure, merging von Foerster’s “second order observer” reflexivity with epistemological constructivism’s “knowing subject” will allow proposing an observing subject constructor for social problem analysis. Although both authors have different conceptions of the “knowledge builder”, i.e., von Foerster in terms of an observer of others and of himself, and Piaget in terms of subject-object/subject interactions, they have in common many reflexive attributes that make similar world constructions within a moderate constructivism framework. But what is the background of these observing subjects?

2. Sociocybernetics, Cibercultur@ and genetic epistemology The epistemological framework of sociocybernetics draws important ideas from Maturana and Varela’s biological perspective (1999), Spencer Brown’s mathematical perspective (1968), von Glasersfeld’s radical constructivism (1990), and von Foerster’s neuro-cybernetic perspective (1973, 1984, 1996). Luhmann’s social systems theory (1998) integrates these in an encompassing social system theory that is not easy to put into practice but shifts social problem analysis to the same level of complexity as that of physical and natural sciences. The second contribution of sociocybernetics comes from the diverse perspectives of its members, who provide unique viewpoints for understanding knowledge. Such is the case of the “subject-oriented approach and its perverse” by Arne Kjellman (2003), of “cybernetics and the integration of knowledge” by Bernard Scott (2004), of the “unity of science by means of epistemological constructivism” by Bernd Hornung (2006), and of “cybersemiotics” by Soren Brier (2009), among other members of ISA’s Research Committee 51. Key concepts in sociocybernetics focus on von Foerster´s cybernetics of cybernetics, in parallel with a more classical perspective of second

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order observation of social problems, i.e., a social reflection on social thinking. Von Foerster´s observation identifies blind spots in research activities, connected to an observer’s presence in the observed process and a necessary heuristic strategy to approach the object of study, i.e., a nontrivial system conception. This observation is remarkably underscored by systems thinking, especially with regard to the Luhmannian recognition that there can be no system without an environment and no environment without a system. In between, system development reduces the gradient of complexities and co-evolution takes place. System conception in sociocybernetics is non-trivial: permanent system feedback and feed-forward mechanisms require a heuristic strategy to adapt systems to the environment, and vice versa, in a non-linear path. This non-trivial conception of activities, agents, institutions or social groups crafted as system interactions requires specific models so as to understand their history and present behaviour. The explicit attention to this co-evolution process implies a more integrated and detailed understanding of self-organization, self-catalysis, self-description and system selfproduction, all of which are essential attributes of the sociocybernetic approach. Since 2010, members of the LabCOMplex research group have participated in sociocybernetic meetings.1 We have promoted Piaget’s epistemological constructivism and García´s contributions on complex systems in social science.2 Recently, some of us presented some thoughts on the relationship between sociocybernetics and Cibercultur@ (in Almaguer P., Amozurrutia J.A., González L., Maass M., and Meza M., 2012). 1

Almaguer (2010, 2011), Amozurrutia (2004, 2008, 2009,2010), González L. (2010) and González, J.A. and Amozurrutia (2004). 2 In the inaugural conference of the sociocybernetics meeting in Mexico (2008), Rolando Garcia presented his view on complex systems and the relevance of genetic epistemology as a strong means of understanding and providing better explanations for a complex social systems approach. In the same conference, Margarita Maass presented “La epistemología genética, la interdisciplina y los sistemas complejos de Piaget y García como base para las Comunidades Emergentes de Conocimiento Local” as a paper. José A. Amozurrutia also presented a paper on “Genetic epistemology, basic mathematics and systemic thinking as essential disciplines for social research”, and finally Jorge González presented “Cibercultur@, sociocybernetics and complex systems: The growing challenge between ‘associationism’ and ‘constructivism’”. These were the first genetic epistemology papers presented in the sociocybernetics field. The main ideas of this chapter were presented as a paper at the 2012 RC51 meeting in Faro, Portugal.

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3. Cibercultur@ approach One of the main ideas of Cibercultur@ is to dedicate special attention to communication processes. Based on what could be called a “togetherness spirit” of group collaboration research, Cibercultur@ seeks to promote a better and more effective dialogical conversation oriented toward the emergence of distributed intelligence. Group intelligence looks for a permanent re-equilibrium of knowledge, derived from an improved availability for listening to the differences and viewpoints of others. Communication derives from a stimulation of interest and the desire to share a problem. This is fostered via permanent connectivity and face-toface communication, with or without virtual means, and is oriented into consistent meaning and shared sense. Communication in Cibercultur@ means putting the information together while having in mind an epistemological knowledge and awareness of that same construction. Recursively, these knowledge processes let us creatively rethink and formulate new questions for old problems. Information need not only be organized and integrated in computer systems; it also works with paper and pencil. The main purpose of complexity is to enhance these activities with computer technologies in order to increase and maximize reflexivity for problem analysis. Multiagent modelling and simulation strategies are key development computer tools. Systems thinking in Cibercultur@ goes hand-in-hand with constructivist epistemology; and the cultivation of these disciplines within a culture of communication yields two results: a theoretical discipline integration3 by means of interdisciplinary research, and the praxeological approach of these three cultures to social problems. Both goals exist in the framework of a heuristic strategy associated with grounded theory and with the configuration of knowledge-emergent communities.4

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This integration condenses three areas of knowledge: communication, information and knowledge, and at the same time is related to a diverse social corpus linked to a wide range of authors like Vygotski, Moscovicci, Bourdieu, Freinet, Freire and many others. 4 A variety of perspectives within the Cibercultur@ approach have been presented in Amozurrutia (2009), González, L. (2010), González, L. and Maass, M. (2008) and Maass M. (2008, 2009).

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4. Genetic epistemology5 Piaget is particularly well-known in the educational and psychological fields but at the same time he left us important philosophical contributions. Genetic epistemology is Piaget´s key proposition. His constructivism is not radical: the Piagetian subject constructs reality not in any possible way, far away from reductionisms and relativisms, but by means of constructions of relations between external processes considered as knowable objects or other subjects, and internal processes knowledge constructions done by the subject itself. According to García, knowledge construction or knowledge development is always the result of a dialectical interaction between an external empirical complex in an object or in subjects and an internal knowledge complex in subjects. A very similar approach is found in Luhmann’s encounter of complexities between the system and the environment. Genetic attribution in this context refers to a permanent evolution of structures or system transformations, i.e., temporal organization of processes, within networks of causalities rather than a chain of linear causalities derived from rigid structures. In García’s terms, knowledge derives from a dynamic equilibrium between structured phases and structuring knowledge phases. Piagetian epistemology assumes that objects are constructions of relations which are always a product of a subject’s interaction with other subjects and objects. In a broad sense, all actions are integrations and/or differentiations of relations organized in processes. They may be in equilibrium or non-equilibrium states; the equilibration process explains the path from one knowledge level to another. The main purpose of our observing subject as a constructor is to identify those processes and how we may understand and explain the changes in them, i.e., how to explain re-equilibrations or de-equilibrations in the research process.6 Before presenting the CDKF model in the next section, I will now summarize the empirical complex associated with the challenges and projects of the researcher and the question that led me to reflect upon and try to understand the inherent system thinking and knowledge development characteristics and approaches. 5 This section is based on Piaget (1961, 1966, 1976, 1977, 1981, 2005) and a more extensive synthesis can be found in Amozurrutia (2011, chapter 4). 6 Although the terms “unbalanced”, “rebalanced” and “balanced” are similar to “equilibrium”, I prefer the latter because it does not refer to a physical standardization of differences based on the concept of minimum variance, but rather to heterogeneous weighted contributions in system equilibrium.

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5. Empirical complex and researchers’ challenges As a first observation of the research process, I will distinguish several relations between different empirical and knowledge domains: There is the researcher’s domain as an observer aware with his/her limitations. He/she observes direct and explicit components of a social problem and the observation of implicit components in the observables and the blind spots in himself and in his/her research group. The organization of the empirical complex, i.e., actors, actions, environment, derives from the explicit and implicit empirical evidence in the unit of observation. The knowledge complex derives from the integration of two or more theoretical corpuses integrated in the unit of analysis. The coupling and inter-definition of the unit of observation with the unit of analysis derive what I refer to as knowledge construction, also known as the object of study. My target in observing researchers is oriented toward the unit of observation/unit of analysis construction in the CDKF model, from which it will be possible to answer the research questions posed in the researchers’ problem analysis.

5.1. SiAs approach The Adaptive System for Social Analysis – SiAs – is not a simple spreadsheet application but rather a modular toolkit based on several types of functions and mathematical expressions associated with a knowledge database and an observables database construction and organization. As modular system software, SiAs is organized as an adaptive structure designed to register observables within variables as nuance functions. The system algorithms – integrating variables and categories, generate diachronic, synchronic graphic representations, sentences explaining variable and category meanings. SiAs has three main valuation levels, i.e., the observables level; the variable and categorical integration – abstraction functions – level; and the inference or generalization level. This information is organized in a knowledge database. Due to flexible language characteristics and potential ease in dynamically constructing and reconstructing applications, the SiAs spreadsheet version allows the research group to permanently construct and adapt the unit of analysis according to evolutional needs. The SiAs modular structure requires researcher creativity and innovation in order to integrate the theoretical corpus as categories and to construct meanings and discourse explanations related to problem questions and system answers (Amozurrutia, 2011).

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Chapteer II

Figure 1 shows the main m steps in the t research ddynamic appliied to the six case sttudies. A soccial problem exists becauuse there aree several observers w with a similar perspective of the des-equiilibration pheenomenon (1A and 1B, in figure 1). Main operatio ons are organnized in the ob bservables database (DB Bobs, 2A), rellating to independent variablles. The constrruction of the knowleddge database (DBkwd, 2B B) field relattes to the nu uances of dependent variables forr observabless and categoory criteria for their integration inn valuation infferences. A reepresentative S SiAs node (3) integrates databases inn a complex opperation. The conditional syymbol in (4) represents r the main seccond order reeflection aroun nd the compleetely heuristicc strategy. Permanent aactualization activities a in th he knowledge database (2B B) and the permanent oobservables reegistry (2B) complete the research cyccle. Basic research trajjectory takes the following g route 1A/1B B > 2A/2B > 3 > 4 > 2A/2B > 3 > 4 in figure 1. From this methodologiccal perspectiv ve, I pose several quesstions about thhese trajectoriees to researchhers. Figure 1. C Co-evolution of our obseerving subjectt constructor and the empirical coomplex

Hence thhe focus is on o how researrchers assimillate and acco ommodate new ideas reelated to systeem thinking in i their own rresearch experrience. In the first ressearch stage, I analyse thee researcher’ss knowledge situation

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before combining the sociocybernetic approach with Cibercultur@’s interdisciplinary research proposition. In the second stage, I analyse research projects developed from bottom-up and top-down dialectical methodologies associated with grounded theory. Other research initiatives demonstrated availability to participate in a seminar to share relevant methodological and systemic thinking components, although their objects of study, ages, discipline trajectories and university academic levels were quite different. Table 1 summarizes the main characteristics of the researchers’ projects. Table 1. Researchers and projects analysed

5.2. The research projects and questions The main questions in the selected projects were: x How to explain the behaviour of the population of Mexico City, the media, and the authorities regarding the influenza pandemic of 2010 (li); x How to evaluate a new proposal for a higher education musical programme (fc); x How to build cultural policy criteria for university evaluation (er); x How to propose new cultural legislation for the state of Nayarit (em); x How to evaluate the science policy promoted by the responsible national official institution from the perspective of the field of the power derived from Bourdieu’s capitals (mc). As we can see in table 1, the researchers’ ages are quite different; researchers over 35 years had different system assimilation capacities than researchers under 25, who showed better qualifications.

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As stated, questions to the researchers were asked during two stages of the research process. The first group of questions intended to register initial conditions and researchers’ expectations with regard to system thinking within a computer system. Questions were oriented toward: q1) the central play of the unit of analysis; q2) the different possibilities of interest in graphical and text system representations; and q3) the researchers’ predisposition for participating in dialogical reflection with the tutor and other researchers in an academic seminar context. The second group of questions was specific to system thinking and interaction with the SiAs system concepts strategy, and the expected results. Question (q4) considers how researchers confronted the process of transforming data into observables, (q5) deals with how researchers remember the process construction in the first approximation of the unit of analysis, (q6) deals with how researchers remember their conception of interphase, differentiation and integration system functions, evaluation factors, observables and knowledge database and (q7) deals with how researchers experience the system adaptation capacity with regard to their discussions with other researchers. Each of these questions required several cognitive operations in order to understand what system thinking applied to a social problem means, and, consequently, how researchers epistemologically approach the sociocybernetic research process with regard to the analysis of social problems. To get some insight into these questions and processes, the next section presents the epistemic frame, i.e., the axiological criteria, for analysing and explaining trajectories and operations based on a different spatial representation of knowledge regarding the six projects in table 1.

6. CDKF model integration In this section, I will show the components and relations in the knowledge field in three steps. The first take on a macro perspective, that is, Piaget’s general knowledge conception. Next, I complement those components and relations with a meso perspective, which is the most familiar conceptualization of Piaget’s concepts. Finally, I present the main basic and micro operations that take place inside meso and macro functions and subsystems.

6.1. A macro perspective for CDKF The construction of a knowledge field from Piaget’s epistemological theory begins from a macro-organized perspective and arrives at meso and

A Sociocybernetic Approach to Enhancing Reseaarch Reflexivity y

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micro persppectives. My departure poiint is the inteersection of two t main partitions oor subdivisionns derived from broad Piiagetian conccepts: the vertical parrtition comess from the interaction bbetween an adaptive component and an orgaanizational co omponent; thhe horizontal partition comes from m the interactioon between th he internalizatiion and exteriiorization componentss. Figure 2 details thesee componentss from a systtemic perspecctive: the horizontal ppartition or first knowledge stratum divission is equivallent to an adaptation iinput and outpput subsystem m (ad) and a cognitive org ganization subsystem ((co). It is important to high hlight the relevvance of an in nterphase between thoose subsystem ms, (is), in fig gure 2B. From m this zone emerges e a new subsysttem, which exxpands the inp put/output opeerations in thee adaptive stratum andd takes part in the knowlledge organizzation subsysstem (see figure 2C). Figure 2. V Vertical partitioons in Piaget’ss knowledge ttheory

From thhese horizonntal subdivisiions, Piaget defines thrree main mechanismss operating inn those subsy ystems. Beginnning with thee general input/outputt subsystem (aa), identiffied as the alpha behaaviour in equilibrationn knowledge activities in figure f 2C, we see a couplin ng with a network of middle subsyystems (ns), identified i as the beta behaviour in equilibrationn knowledge activities, an nd finally thee global integ gration of subsystems into a relativve totality sysstem, (to), ideentified as the gamma behaviour inn equilibrationn knowledge activities, a is acchieved.7

7

These three levels of know wledge developm ment are identiffied by Rolando o García as m inn scientific knowledge k the intra, iinter, and traans-objectual mechanisms construction ((García, 1982).

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The verrtical partition, or second d knowledgee stratum div vision, is equivalent tto the generall internalizing g or input asssimilation pro ocess (ip) shown in ffigure 3, aloong with an exteriorizatioon or outputt general accommodaation process (ep). ( Again, an n intersectionn between thesse general processes w will generate a general equiliibrium interphhase (ge). Figure 3. H Horizontal parttition in Piagett’s knowledgee theory

g integrration process for the CDKF F derived In figuree 4, we see a general from Piageet’s equilibriuum theory. In I that figuree, 4D repressents the integration oof partitions from f which emerge six maain discursivee function zones (Piaget, 2008). In 4E, the threee rectangles rrefer to the th hree main dialectical eequilibrium zoones between horizontal h andd vertical straata, and in 4F the first delimitation of o CDK zoness is shown. Fiinally, in 4G, I include the main floow of informaation and the main m forces off communicattion – not just those deerived from thhe input/outpu ut path but alsso from transv versal and concomitantt paths in the knowled dge field sppace and th he main differentiatioon of forces inn the CDK fieeld, in 4H.

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Figure 4. Vertical and horizontal partitions in Piaget’s knowledge theory and the identification of the knowledge field (F to G)

Although basic relations may be considered as micro components, they can be introduced to complement a perspective of macro processes. Piaget distinguishes three types of basic relations: empirical, of implication, and logical; which are connected in a network of interrelations associated with different integration and differentiation micro and macro operations. There is no clear division between types of relations in the chain construction process. From these types of relations, it is possible to construct chains of exogenous-endogenous bridges between physical, biological and physiological brain domains. Through them, it is possible to explain knowledge construction from different levels of observation; other types of relations are causal relations and interdependences, which will be defined later. Empirical relations define couplings between outer materialities with skin cells, immersed with dendrites and groups of neurons associated to our five senses; they are exogenous-endogenous neuron bridges. For Piaget, outer materialities are not only physical elements but also other subjects with proper relational constructions. “Action schemes” organize and integrate empirical relations in subsystems. Subsequently, these subsystems integrate through conditional phase operations, and several action schemes joined by means of “relations of implication”. This network of integrations operates as endogenous neural centres and configures new subsystems of neuronal organizations oriented to construct new meanings. Operations like distinctions, sequencing and ordering explain this level of subsystem organization.

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6.2. A meso m perspeective for CD DKF On a meeso level of orgganization, su ubsystem strucctures are in permanent p “assimilationn and accom mmodation” processes, aand they op perate on classificationns and basic set correspon ndences betw ween subsystem ms. On a deeper leveel of construuction, i.e., a higher braiin level, relaations of implication are integratedd into new su ubsystems. Thhe operations are again incorporatedd and combinned in new forms fo and connditions organ nized for new meaniings and puurposes; they y are “logic al and math hematical relations”. E Each integratioon process ressults in a new w signification n level, as concepts, caategories andd symbols, an nd new equillibrium condiitions are established. This messo level contaains the classiccal organizatiion criteria off the main general funnctions in Piaaget´s knowleedge construcction. Figure 5 shows these functioons, together with w the main equilibrationn zones betweeen them. Figure 5. M Main knowledgge general fun nctions in the C CDKF

What foollows is a practical deffinition of acctivities as capacities c associated w with the analyssis of research h activities: Assimilaations: the cappacity to be ab ble to hear andd understand new n ideas and practicees. It is concom mitant with acccommodationn functions. Accomm modations: thee capacity and d the ability tto implement practical ideas in new and/or already known languages. Itt is concomittant with assimilationn functions.

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Empirical abstractions: the capacity to understand and integrate properties of empirical observables with new or old ideas. It is concomitant with inductive generalization functions. Inductive generalizations: the capacity and the ability to differentiate empirical realities and to put in practice new ideas and explain them in new and/or already known languages. It is concomitant with empirical abstraction functions. Reflexive abstractions: the capacity to understand empirical abstraction ideas and integrate them into new concepts. It is concomitant with completive generalization functions. Completive generalizations: the capacity and ability to differentiate types of logical comprehension and integrate them in new and/or already known languages. It is concomitant with reflexive abstraction functions. Regulations: the capacity to create a correction mechanism for maintaining a steady control of processes. They are mostly related to homeostatic behaviour. Compensations: the capacity to create a correction mechanism for rectifying control in processes. They are mostly related to changes in homeostatic behaviour. Reciprocal equilibrations through regulations and compensations: the capacity and ability to conjugate affirmations and negations, integrations and differentiations in various organization behaviours i.e., alpha beta and gamma, through a dialectical process. Assimilation/accommodation equilibrations through regulations and compensations: the capacity and ability to conjugate concomitant relations between internalization and exteriorization processes through a dialectical process. There is a “movement” from these meso operations, general integration processes between adaptation (ad) and organization subsystems (co); see figure 2. It goes from empirical relations in assimilations/accommodations to implication relations and logical relations. This construction implies different subsystem levels of organization through abstraction/generalization operations. This meso description of knowledge construction is, at the same time, a concomitant interaction between the understanding knowledge component, associated with an internalization general process (ip in figure 3), in correspondence with a second knowledge component oriented to an exteriorization general process (ep in figure 3) and devoted to different language constructions. The general internalization and integration process moves from empirical relations to implication relations and logical relations into

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different subsystem levels and organization through abstraction operations. This operation is subdivided by Piaget into two phases: one of empirical abstractions related to the knowledge process associated with empirical evidence perceived by our senses, and a second with reflexive abstraction processes which relate to more elaborate and symbolic knowledge operations. At this point, logical relations relate to implication relations, which flow in different neural paths through new empirical relations centres associated with the muscles. This chain of operations are generalization processes which in correspondence with abstraction processes enable language construction associated with the way the subject reacts or interacts with others. The first stage of generalization is a completive type associated with logical relations and the decision process, while the second generalization stage relates to implication relations and empirical relations. It is an inductive generalization process related to the accommodation process and relates to the mood of the subject’s responses in his/her interaction with others. This chain of relations is organized in terms of operations and processes within dynamic structures, which may or may not be in equilibrium. This depends on the subject’s attributes and on the way he/she responds to environmental conditioning; non-equilibrium conditions derive from the desires or needs generated inside the subject. In both cases, re-equilibrium emerges by the necessity to re-establish a noncritical disequilibrium but to operate in a dynamic shareable equilibrium. Epistemological operations of regulations maintain the levels of a dynamic equilibrium in a homeostatic stage by means of feedback mechanisms; when this stage of equilibrium is not enough to solve permanent irritations or perturbations, compensations enter into play. These operations are macro processes operating over meso processes. Interactions between abstractions, generalizations, regulations and compensations orient and modify the homeostatic mechanisms and find new equilibrium conditions by means of feedforward mechanisms. Compensations are operations that modify regulation conditions in subsystem characteristics in order to modify established limits and propose new directions for re-equilibration processes. They operate in terms of positive and negative compensations. Piaget even proposes the possibility of maximizing the equilibration process developed by the subject in its interaction with his/her environment with other objects and subjects.8 8

In Piaget (1978), we find a deep analysis of the epigenetic processes that show how traditional perturbations from the environment to gen level can be reverted. Using an epistemological language with biological conceptualizations, the author

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The above descriptions show us three different levels, all of which interconnect in a complex network with different neural centres and with proper integration and differentiation functions oriented toward the perception, reflexivity and inference processes. The first level, i.e., the one associated with physical behaviour, operates with empirical relations associated with action schemes with assimilation and accommodation processes. Basic regulation and compensation operations are present. Piaget refers to this level as an alpha level integrated by sensory-motor subsystems. A second beta level operates mainly with implication relations associated with empirical abstractions and inductive generalizations processes; again, a beta level with subsystem operations associated with emotional and rational behaviours. The third level, the gamma level, is associated with rational behaviour and operates by means of logical and mathematical types of relations associated with reflexive abstractions and completive generalization processes. The continuity of these processes allowed Piaget to derive coherent inferences to explain “knowledge construction” from the first months of life to the first 15 years of experiences. After the construction of this stage, he claims, humans develop knowledge. The great correspondences between Piaget’s epistemological and system thinking in sociocybernetics must be highlighted. In both cases, system self-organization is oriented toward the coordination of inputoutput operations related to system process organizations and objectives. Those processes are equivalent to assimilation-accommodation operations merged with integrations and differentiations oriented toward concept and symbol constructions in correspondence with explanation processes. Both systems conduct and regulate system operations by means of feedback/regulation, and feed-forward/compensation mechanisms; both perspectives are equivalent to the main operations in first and second order cybernetics and correspond to the main operations in Piaget’s equilibration theory.

6.3. A micro perspective for CDKF In CDKS, the micro level perspective refers to the group of Piagetian elementary operations that precisely describe the mechanisms in the previously mentioned meso functions. As explained, their point of departure is action, and actions are constructed with three types of basic

explains how transformation processes take place from the gen to physiological levels.

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relations, a special case of interdependences. They are a complex group of logical and implication relations that establish a dynamic correspondence between two entities or neural conglomerates while seeking dynamic equilibration. The correspondences are interwoven in regulation and compensation alpha, beta, and gamma behaviour mechanisms that are oriented toward the coordination of relations, mutual enrichment between entities and conservation of total dynamic equilibrium. On this micro level, the main operations are built from assertions as statements and distinctions as negations. Considering these elementary operations, Piaget derives order, seriations and classifications, and with these, subsequent operations like combinations and permutations are made possible. As previously mentioned, all these basic and elementary operations – and functions – explain meso and macro processes in terms of empirical, implication and logical or mathematical relations. The main challenge in the model I now propose is to relate all three levels in a group of mechanisms integrated in a unit of analysis that lets us evaluate and assess knowledge construction processes.

6.4. CDKF zones and unit of analysis correspondences Our next step is to define the field of zones and forces of knowledge. Researchers’ activities will now be represented and evaluated. In figure 6, I present the main zones and paths and their relationship with the SiAs basic scheme for units of analysis.

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Figure 6. Thhe CDKS fieldd and the equivalent unit of annalysis represeentation

In zones of assimilatioons (as shown n in figure 6), accommodatiions (Ac), empirical aabstractions (Ae), ( inductiv ve generalizaations (Gi), reflexive abstractions (Ar) and com mpletive geneeralizations (G Gc), discursive phases, in which traaditional logic and rationaalization proceesses are app plied with stability, takke place. If contradictions c s appear, theyy are the result of an incorrectionn in the appliied theoreticaal conceptionn; forces are one way through hierrarchical criteria within neu ural networks.. Each neuron n operates as an integrration and diffferentiation node n and eachh relation is associated a 9 with a synappsis transform mation process that representts a specific meaning. m In zoness associated with w reciprocal equilibrationns (Ap and Re in figure 6) and assim milation/accom mmodation equ uilibrations (E Ea, Eb, Ec, Ed d, E1, E2, and E3), we see the occurrrence of dialecctical phases. A logic of imp plications within a diaalectical processs takes placee through a re--equilibrium process p If contradictionns appear, theey are the resu ult of dialectiical mechanism ms; these

9

The analoggy between phyysiological and epistemologic al terms is bassed on the classic analoggy established in artificial neurral network theoory (Amozurrutia, 2011).

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forces are correspondences between function dynamics through different mechanisms within neural networks. In Piaget`s equilibrium theory (Piaget, 2005), the dialectical process is central to reciprocal and assimilation/accommodation equilibrations (Piaget, 2008). The fulcrum of this process can be summarized as “two systems, until then separate and distinct but not opposite to each other, [that] merge into a new whole whose properties exceed and sometimes much those of the original” (Piaget, 1978, 187). The main mechanisms in these merging processes are interdependences, circularity constructions and relativization constructions. Interdependences are relationships with dependences from both sides, implying that one element depends on the other and vice versa. Circularities do not refer to homeostatic behaviour but rather a transition process between two circular behaviours, that is, a spiral transformation. Relativization implies a change of axiological code that transforms the main relation behaviour. With these operations, Piaget explains the main paths for knowledge construction10 by going through the three equilibrium phases mentioned previously – the alpha, beta and gamma behaviours. An application of these zone equilibrium processes in research activities can be found in Rolando García’s use of Piaget’s equilibration for the analysis of scientific development (Piaget and García, 1982). García (2000) proposes a “third version of equilibration theory” in which the phases of knowledge construction of a child, i.e., from birth to 15 years of age, are similar to the development of scientific knowledge over the course of 2000 years. Based on this analogy, I propose a similar procedure to explain knowledge transformation in Labcomplex project researchers. By now, hopefully it will be clear that the general organization of the CDKF model is organized from a systemic mode of thinking. As previously mentioned, the SiAs category and variable structure derives from Piaget’s and von Foerster’s ideas and gathers system capacities from the most relevant characteristics of their theories. The main node in the SiAs unit of analysis is represented in figure 1 as (3), and constitutes the conjugation of two tetrahedral structures. The first integrates information from three variables into a single category, and the second differentiates the meaning of this category into three different forms of representation. The first tetrahedral structure represents a node in a network dedicated to assimilation and abstraction processes. The second 10

Rolando García has proposed an alternative strategy to explain how these three mechanisms operate in science (Piaget and García, 1982). He refers to intra, inter and trans-objectual mechanisms equivalent to alpha, beta and gamma Piaget behaviours.

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tetrahedral structure represents a node in a network dedicated to generalization and accommodation processes. Interaction and coordination of these two networks occur transversally with a third network, dedicated to the adaptive subsystem process. This last network organizes the selection of observable valuation factors, weighted factors in the integration process, and adjective selections in differentiation processes.11 The organization of zones, forces and flows of knowledge in the CDKF converges in the SiAs unit of analysis. The main ideas that let us define nuances in variables and category definitions are condensed in the next figure. Figure 7. Variable and category identification in units of analysis

The three main categories represent the alpha, beta, and gamma behaviour subsystems; each node of variables includes the discursive phase component in each behaviour level, and the central variable in each category shows the different transition mechanisms for the dialectical 11

A more detailed description may be read in Amozurrutia, 2011.

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phase in each behaviour subsystem. For this SiAs application, the definitions of variables and categories are as follows: x Assimilation capacity (variable As): nine nuances related to the willingness and openness to new ways of perceiving objects, properties and attributes, and to understand empirical concepts. x Alpha-Beta equilibration (variable Al): nine nuances related to recording the ability to integrate objects, properties, attributes, and empirical concepts into new concepts (Ea), the willingness and openness to apply common sense languages (Re), and the ability to establish correspondences in interdefinitions between formal languages in disciplines and common-sense languages (E1). x Accommodation capacity (variable Ac): nine nuances related to the ability to apply ideas within clear concept evaluations in a common-sense language. x Alpha behavior component (category AA): twenty-five nuances related to the level of self-attributes and empiric concepts construction for self and others valuation. x Empiric abstraction capacity (variable Ae): nine nuances related to recording the ability to understand and integrate objects, properties, attributes, and empirical concepts into new concepts associated with a discipline. x Alpha-Beta-Gamma equilibration (variable Be): nine nuances related to recording the ability to integrate disciplinary concepts into categories of the same discipline and in a meta-language (Eb). This includes the ability to establish correspondences in interdefinitions between formal languages in disciplines and metalanguages (E2), and the ability to make distinctions between empirical ideas from a disciplinary language and specific valuations in subjects and objects within a common-sense language (Ed). x Inductive generalization capacity (variable Gi): nine nuances related to establishing relations between one or more disciplinary languages and common-sense language in practical problems. x Beta behavior component (category BB): twenty-five nuances related to the level of emotional and rational subsystem construction associated with dialectical correspondences with the empirical abstraction concepts and inductive generalizations by means of a disciplinary language.

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x Reflexive abstraction capacity (variable Ar): nine nuances related to the integration of new concepts associated with a discipline within meta-languages and more general abstractions. x Beta-Gamma equilibration (variable Ga): twenty-five nuances related to the ability to establish correspondences between general abstractions with meta-languages (E3), within dialectical mechanisms related with disciplinary language construction (Ec), and in relation to transversal differentiations with empirical abstractions and completive generalizations (Ap). x Completive generalization capacity (variable Gc): nine nuances related to establishing relations between one or more meta-languages for disciplinary languages related to empirical abstractions. x Gamma behavior component (category CC): twenty-five nuances related to the level of rational subsystem integration as relative totalities, associated with dialectical correspondences with reflexive abstraction concepts and completive generalizations by means of meta-languages and their relationship with discipline languages in terms of schema representations and written and spoken languages. x Knowledge development (macro-category DC): twenty-five nuances related to general equilibrium behavior and knowledge construction. The general description of the unit of analysis in the CDKF model, figures 6 and 8, shows the knowledge areas and functions associated with the themes from which I derived the questions for researchers and made the first approximation of the analysis of the answers: x “The central play of the unit of analysis”, which implies understanding a theoretical construction related to their own research problem (zones “Re” and “Ap” in figure 6 and “Z1” in figure 8). x “The different possibilities of interest in system graphical and text representations”, that is, related to practical accommodation of new information through traditional graphs (zones E2 > Gi > Ed > Ac in figure 6 and Z2 in figure 8). x “Your predisposition in dialogical reflection participation with the tutor and within an affective and critical reflection with other researchers in an academic seminar context”, that is, related to a permanent reflection between internalization and exteriorization processes (Ip and Ep in figure 4), and equivalent to their already assimilated knowledge equilibrium (“Ae” and “Ar” in figure 6),

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with the social, epistemological, and systemic languages in “Gc” and “Gi” (zones “E2” and “E3” in figure 6 and “Z3” in figure 8). The second group of questions were specific to system thinking and interaction with the strategy of SiAs system concepts and its expected results: x “How do you confront the process of transforming data to observables?”, is an activity in multi-equilibration zone “Re” but requires the empirical synchronization between “As, Ae, Gi” and “Ac” through “Re” in figure 6 and “Z4” in figure 8. x “How do you remember the process in the first approximation of unit of analysis?” is the reorganization of multiple interactions in the “Ap” and “Re” paths, which imply abstraction and generalization dialectical mechanisms as a whole in the organization stratum (“co” in figure 3), considered as a series of the researchers own transformation process and “Z5” in figure 8. x “How do you remember your conception of interphase, differentiation, and integration subsystem functions, evaluation factors, observables, and knowledge database?” is a similar process in the organization stratum but now on the adaptive stratum (“ad” in figure 3 and “Z6” in figure 8). x “How do you experience the system adaptation capacity related to discussion and conversation with other researchers?” corresponds to the interphase between the organization and adaptation strata, but with the emotional component in “E3”, “E2” and “E1” equilibrium zones in figure 6 and “Z7” in figure 8.

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Figure 8. M Main knowledge zones asso ociated with thhe relevant th hemes for researchers

Figure 9 shows a reeference scheeme for the construction of these phases, withh basic and ideeal paths for knowledge k connstruction.

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Figure 9. Initial and basic knowledge path (A), simplified knowledge path (B) and complete and dense knowledge path (C)

In the first scheme, (A), the energy is an input system information as the first perceptions from the action schemes are partially assimilated and accommodated in a dialectical phase that takes several months in a child. Throughout his/her life, these general functions will be present, as in B) and C) in that figure. In the case of a researcher, the assimilation/accommodation functions are few but important. One of them is present in the attributes and object/subject in relation with variables definition and in the association of implicit attributes in observables, with nuances in one of the 27 variables. The second scheme, (B), shows the path from a perception associated to an input information process to a brief reflexivity process and an immediate system response. It represents superficial knowledge, with a simple and not-rational response to the perceived information. The third path, in scheme (C), is a more elaborate system or subject reflexivity process as it supposes more dialectical zones in equilibrium to give a more rational inference.

7. Case study analysis In section 2, I described the five research project characteristics and the two sets of questions researchers were posed. The questionnaires used in two research development phases and their answers in ASCII text files were gathered in a database; each sentence was associated with one of the

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nuances in variables, by means of labels in the sentences and simultaneously associated with units of analysis (see table 2). From these labels, SiAs extracted and established correspondences with the 81 total variable nuances, evaluating the contributions according to a “significance value” in terms of valuation factors, normalized between zero and one.12 Finally, the sum of contributions in each variable was represented in a graph or map. In figure 10, the total number of contributions and the sum of their significance value are shown; these subzones represent how each researcher is present on the CDKF. Each answer contains from two to ten lines of text and supports from one to three labels. The first line in the next table refers to paragraph 27, question number three (r3) in the second phase of the “li” project. The first label, “al3”, identified by “#”, refers to “textual evidence of a low (3) alpha equilibration zone (al)”. Five lines below, evidence of a more significant (5) alpha (al) equilibration zone can be found. In figure 11, there are five bar graphs with general valuations for each researcher. We see that “er” has the highest global valuation (0.85) and both “em” and “fc” the lowest (0.67); although the latter researchers have the same value, we find marked differences between them, mainly with regard to the self-reflectivity paths: “em” has a higher adaptation or alpha level (0.9) than “fc” (0.6), which tells us that the first researcher required an intense effort to assimilate, accommodate, and apply systemic thinking concepts. Although they show a similar beta level, or emotional component, in their constructions (“em” = 0.66 and “fc” = 0.63), they have opposite alpha and gamma contributions (“em” with 0.9 and 0.46, and “fc” with 0.60 and 0.78). In this case, “em” shows a better-developed adaptive disposition than “fc” but is less adept in mastering abstract concepts, not only in system thinking but in their own field, i.e., cultural legislation for “em” and music composition for “fc”. These differences are also evident in the beta equilibrium contribution in which “em” shows lower values than “fc”, as seen in figure 12.

12 The method and procedure used in SiAs is further explained in Amozurrutia (2011).

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Figure 10. Total number of answers (a) and valuations (b) in CDKF

Other important distinctions are in the paths showed by “er” and “li”. The first is much older than the second, and both showed similar availability to understand and participate in system thinking development. The younger researcher, (li), shows a more distributed participation in understanding new concepts, i.e., in systems and or in their own problem, health risk (2.9 and 3 points in figure 12) than “er´s” understanding of new

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concepts, which are related to cultural policy, only with one point of evidence. But at the same time, a denser and higher challenge in reequilibrium paths of beta level in system development is in “er” (10 points in six different forms of challenges or re-equilibrium paths) than the 7 points in four challenge paths in “li”. Figure 11: Evaluations of unit of analysis variables and categories for the five researchers

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Figure 12 only represents the main re-equilibration activities of researchers throughout the projects’ development. As a synchronic representation, the graphs condense the research information from the two phases or questionnaires, global higher values (“er = 21.4 and “li” = 17.2) derive from a more dedicated and challenge participation. Low values in “mc” derive from a fragmented participation in the project, although it has the second highest value in the alpha level, that of understanding new concepts. This researcher is more than fifteen years older than the youngest (li), and showed profound interest in understanding systemic concepts.

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Figure 12. Breakdown of equilibration subsystems (alpha, beta, and gamma) variable values for each researcher

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A global perspective of each researcher can be seen in figure 13. Researchers “em, fc and li” show a profile increasing from alpha to beta to gamma phases, which represents a knowledge progression throughout the research project. “mc” presents a discontinuity process derived from the fragmented participation in that period, and “er” shows a more consistent beta and gamma development, confirming the maturity of their research activity.

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Figure 13. Global equilibration evaluation for each researcher

The diachronic representation of researchers’ re-equilibrium or dialectical phases can be seen in figure 14. I present the two or three moments described in “er’s” answers: each dialectic zone in the CDKF field shows three subzones associated with a higher and complete dialectical re-equilibration process, middle and low or difficult dialectical re-equilibration process, i.e., that of changing from one level of knowledge to another, either with richer or poorer knowledge content. Discursive zones, i.e., those associated with logic behaviour – that of integration or differentiation level in assimilation, accommodation, abstractions, and generalization Piaget discursive processes – show nine nuances or level of significance subdivisions from the more desirable knowledge development to the most insignificant process.

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Figure 14. Path trajectories in DCKF of researcher “er”

The paths shown in figure 14, i.e., dotted lines derived from two or three identification labels in paragraphs on the text, show evidence of the researchers’ reflections on knowledge. Each line derived from one sentence, paragraph, or answer produced by the researcher; in this case, most of the paths go from a “lower” to a “higher” level of knowledge. An approximation of these paths along a temporal axis representation, in figure 15, show us the development/construction process of knowledge in the research activity.

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Figure 15. P Path trajectoriies in time thro ough CDKF oof researcher “er” “

8. Final reemarks o Piaget´s maain equilibriu um theory In this cchapter I presented some of concepts, orrganized andd structured under u a systeem thinking approach. a These allow wed me to formulate a constructioon and dev velopment knowledge ffield – CDKF F – model forr the analysis of research activity. a I applied it too some of thee LabCOMpleex research prrojects. The case study graphs show w differences in epistemolo ogical mechannisms and quaalities for explaining ddifferences annd similitudees and transfoormations alo ong these research actiivities. The orgganization of Piaget’s disscursive and dialectical phases p in knowledge cconstruction coalesces c arou und an analyticcal unit enablled by the analysis of aanswers from the researcherrs, in two diffferent momentts of their projects, thrrough the SiA As system. The T questions may be imp proved in

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order to know more significant challenges. The questionnaires should consider open interviews so as to obtain more natural answers. The analysis itself had a strong emphasis on sociocybernetic second order reflexivity and system thinking, with special attention to distributed intelligence and dialogical communication on the research process, from a Cibercultur@ approach. Our goal is to provide a more coherent explanation of how to represent the dynamics of complex system construction and cognitive research transformation processes to enhance second order reflexivity in research projects. In future works, we will apply the CDKF model to other discourses and activities associated with specific social problems in order to test the knowledge process on observed actors.13 This will allow us to explain new networks of causalities strongly attached to problem actions and activities, and to derive deeper and more accurate answers to research questions.

Works Cited Almaguer-Kalixto, P. (2010). Cibercultur@ and Environmental Knowledge: An Empirical Approach to Sociocybernetics. XVII World Sociology Congress of the International Sociology Association, Gothenburg, Sweden. —. (2011). Cibercultur@ and Action Research Strategies to Deal with Complex Environmental Controversies: A Case of Waste Disposal Management. 10th International Conference in Sociocybernetics. University of Economics, Cracovia, Polonia. Almaguer, P., Amozurrutia, J. A., González, L., Maass, M., & Meza M. (2012). Sociocibernética, Cibercultur@ y Sociedad. México: CEIICHUNAM. Amozurrutia, J. A. (2007). Pensamiento sistémico y organización matricial orientados a la construcción de sistemas sociales: retos y herramientas ante la complejidad. In C. Marcuello (Ed.), Sociocibernética: lineamientos para un paradigma. Madrid: Editorial Institución Fernando el Católico.

13

It will be challenging to consider contrasting evidence with other research projects, whether or not related with sociocybernetics and Cibcercultur@ strategies for social analysis. More powerful contrasting cases may be done for CDKS application in discourse analysis related to the knowledge component in it (van Dijk, 2003).

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