Introducing Pragmatics in Use [2 ed.] 9781138481992, 9781138482005, 9780429342950

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Introducing Pragmatics in Use

Introducing Pragmatics in Use is a lively and accessible introduction to pragmatics which both covers theory and applies it to real spoken and written data. This textbook systematically draws upon a number of different language corpora and the corresponding software applications. Its primary focus is the application of a corpus methodology in order to examine core component areas such as deixis, politeness, speech acts, language variation and register. The main goal of the book is to contextualise pragmatics in the study of language through the analysis of different language contexts provided by spoken and written corpora. Substantially revised and updated, this second edition covers a wider range of topics, corpora and software packages. It consistently demonstrates the benefits of innovative analytical synergies and extends this to how corpus pragmatics can be further blended with, for example, conversation analysis or variational pragmatics. The second edition also offers a new chapter specifically dedicated to corpus pragmatics which proposes a framework for both form-to-function and function-to-form approaches. The book also addresses the – sometimes thorny – area of the integration of the teaching of pragmatics into the language classroom. All chapters in the second edition include a number of cohesive, step-by-step tasks that can be done in small groups in class or used as self-study resources. A wide range of illustrative language samples drawn from a number of Englishlanguage corpora, coupled with instructive tasks and annotated further reading sections, make this an ideal textbook for advanced undergraduate or postgraduate students of pragmatics, discourse analysis and corpus linguistics within applied languages/linguistics or TESOL programmes. Anne O’Keeffe is Senior Lecturer in Applied Linguistics, Department of English Language and Literature, Mary Immaculate College, University of Limerick, Ireland. Brian Clancy is Lecturer in Academic Writing and Research Methods, Academic Learning Centre, and Lecturer in Applied Linguistics, Department of English Language and Literature, Mary Immaculate College, University of Limerick, Ireland. Svenja Adolphs is Professor of English Language and Linguistics and Head of School at the School of English, University of Nottingham, UK.

Introducing Pragmatics in Use Second Edition

ANNE O’KEEFFE BRIAN CLANCY SVENJA ADOLPHS

Second edition published 2020 by Routledge 2 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN and by Routledge 52 Vanderbilt Avenue, New York, NY 10017 Routledge is an imprint of the Taylor & Francis Group, an informa business © 2020 Anne O’Keeffe, Brian Clancy, Svenja Adolphs The right of Anne O’Keeffe, Brian Clancy, Svenja Adolphs to be identified as authors of this work has been asserted by them in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. First edition published by Routledge 2011 British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data A catalog record has been requested for this book ISBN: 978-1-138-48199-2 (hbk) ISBN: 978-1-138-48200-5 (pbk) ISBN: 978-0-429-34295-0 (ebk) Typeset in Akzidenz Grotesk by Apex CoVantage, LLC Visit the eResources: www.routledge.com/9781138482005

Contents

List of figures List of tables Acknowledgements

viii xi xiv

Introduction 1.1 What is pragmatics? 1.2 Ways of studying pragmatics 1.3 The empirical turn within pragmatics 1.4 The main functions of software tools used in corpus pragmatics 1.5 The structure of this book 1.6 Further reading

5 17 19

Chapter 2

Researching pragmatics 2.1 Pragmatics research: from intuitive to empirical approaches 2.2 Methods for eliciting language data 2.3 Methods for recording language data 2.4 Conclusion 2.5 Further reading

21 21 26 34 44 45

Chapter 3

Corpus pragmatics 3.1 Introduction 3.2 Key considerations of corpus pragmatics research 3.3 Form-to-function research in corpus pragmatics 3.4 Function-to-form research using corpora 3.5 Conclusion 3.6 Further reading

47 47 48 51 56 67 68

Chapter 4

Reference 4.1 Introduction 4.2 Deixis

69 69 72

Chapter 1

1 1 2 3

vi

CONTENTS

4.3 4.4 4.5 4.6 4.7

The deictic centre Basic categories of deixis Reference in use: ‘that’ and speaker attitudes Conclusion Further reading

76 78 91 95 96

Chapter 5

Politeness 5.1 Linguistic politeness 5.2 The face-saving approach to politeness 5.3 Impoliteness 5.4 Discursive politeness 5.5 Conclusion 5.6 Further reading

98 98 103 114 119 122 123

Chapter 6

Speech acts 6.1 Introduction 6.2 Speech Act Theory 6.3 Identifying and analysing speech acts in a corpus 6.4 What is a speech act context? 6.5 Speech act classification in discourse analysis 6.6 Conclusion 6.7 Further reading

124 124 125 135 138 140 143 143

Chapter 7

Pragmatics and language variation 7.1 Pragmatics and language variation 7.2 Response tokens and variation 7.3 Pragmatic markers and variation 7.4 Vague language and variation 7.5 Speech acts and variation 7.6 Further reading

145 145 147 154 159 165 170

Chapter 8

Pragmatics and variation at the level of register 8.1 Pragmatics and variation at the level of register 8.2 Comparability at the level of turns 8.3 Other methods of comparing registers using a corpus 8.4 Conclusion 8.5 Further reading

173 173 174 184 193 194

Chapter 9

Pragmatics and language teaching 9.1 Introduction 9.2 Implicit versus explicit pragmatic instruction 9.3 Technology-based opportunities for pragmatic learning 9.4 Developing classroom materials

196 196 197 200 210

CONTENTS

9.5 Conclusion 9.6 Further reading

225 227

Appendix References Index

229 233 255

vii

Figures

1.1 A sample of concordance for have in the TED_en corpus sorted 1R (using Sketch Engine) 1.2 Top ten collocates of have in the TED_en corpus (using Sketch Engine), examining all word candidates three to the left and three to the right of we 1.3 Concordance sample of we + have as the node (sorted 1R) 1.4 Top ten most frequent words to the right of we + have in the TED_en corpus (using Sketch Engine) 2.1 Language inside as intuitive knowledge and language outside as empirical data 2.2 Researcher interference versus research control (adapted from Jucker, 2018: 23) 2.3 An example of a freer DCT (adapted from Beebe and Zhang Waring, 2004: 245) 2.4 Scenarios from DCT presented to American and Mandarin students in Liang and Han (2005) 2.5 A roleplay prompt 2.6 Example of broad transcription (and extract from a political science lecture from the LIBEL corpus) 2.7 Example of narrow transcription from the Hong Kong Corpus of Spoken English (HKCSE) (Cheng and Warren, 2007) 2.8 Web interface for BNCweb: Browse a File Function (search for file KCT line 7746) 2.9 Transcript of file KCT 7752 in BNCweb, marked up for , segments and overlapping talk 2.10 Detailed transcription provided by Rühlemann (2019: 94) 2.11 Sample interface from ELAN where image, sound and multi-modal transcript are aligned in tiers (ELAN How-to Guide, 2017: 15) 2.12 Data extract from a cookery instruction session from CLAS 2.13 Screenshot of a search for directives marked with the tag in CLAS using AntConc software (sorted 1R) 3.1 Form-to-function and function-to-form approaches in corpus pragmatics 3.2 Corpus data versus DCT elicited data across form and context (O’Keeffe, 2018: 593)

10 11 12 13 22 23 27 29 31 38 39 40 40 41 42 43 44 48 51

FIGURES

3.3 20 concordance lines of the node word sorry in the BNC2014, using #LancsBox (unsorted) 3.4 20 concordance lines of the node word so in the BNC2014, using #LancsBox (unsorted) 3.5 The four main approaches to form-to-function analysis using CL (based on Ädel and Reppen, 2008: 2–3) 3.6 An inventory of function-to-form approaches (adapted from O’Keeffe, 2018: 598–599) 3.7 An example of gratitude clustering across turns in the BNC2014 (using #LancsBox) 3.8 Collocate search settings for oops in the spoken component of COCA 4.1 Concordance lines for that bloke in the BNC Baby 4.2 Concordance lines for that fella in LCIE 5.1 Brown and Levinson’s (1987) strategies for performing FTAs 5.2 The semantic categorisation of in-group terms of address (adapted from Leech, 1999) 5.3 Distribution of hedges in LCIE (normalised per million words) (Farr et al., 2004) 6.1 20 randomly generated concordance lines for suggest in the BASE (sorted 1L) 6.2 Felicity conditions for requests (adapted from Levinson, 1983: 240) 6.3 Felicity conditions for promises 6.4 20 concordances lines for Can you…? in LCIE (sorted 1L) 6.5 20 concordance lines for Could you…? in LCIE (sorted 1L) 6.6 15 randomly chosen concordance lines for why don’t you…? in MICASE 6.7 15 random concordance lines for why don’t we…? in MICASE 7.1 20 random concordance lines for um in the Spoken BNC2014 7.2 20 random concordance lines for well in the Spoken BNC2014 7.3 Frequency of use of thanks, thank you and cheers in American English 1800–2008 7.4 Frequency of use of thanks, thank you and cheers in British English 1800–2008 8.1 Sample of concordance lines for as search item from LCIE (sorted 1R) 8.2 Concordance extracts of sort in the NHS Direct corpus (unsorted) 8.3 Sample concordance lines for maybe + we in C-MELT (unsorted) 8.4 Extract from concordance lines for sound of till in shop recordings from LCIE (sorted 1R) 8.5 Examples of concordance lines of inhales (unsorted) 9.1 Role card for Alex 9.2 Two examples of high-frequency imperatives in the MICUSP 9.3 Frequencies per 10,000 words of note in the MICUSP. The results for Physics, Philosophy, Mechanical Engineering, Economics and Linguistics are highlighted, as these were used in Neiderhiser et al. (2016) 9.4 Examples of elicited responses to a request task based on booking a study room in a university context (SPACE corpus) (taken from Jones et al., 2018: 145)

52 54 55 57 62 65 92 94 104 107 113 126 128 128 131 131 137 137 151 153 166 166 183 185 188 192 193 198 203

203

208

ix

x

FIGURES

9.5 An example of a B2 (Upper-Intermediate) level resource based on findings from research into the Trinity Lancaster Corpus (Gablasova et al., 2019) 9.6 Frequency results for approximately charted across genre and time in COCA 9.7 COCA interface search settings to explore approximately in ACADEMIC data 9.8 Profile of approximately in ACADEMIC data across disciplines 9.9 Frequency results for may and should across all disciplines in MICUSP 9.10 Extract from Beard (2008) 9.11 The first 20 results from the Business Letters Corpus search for would you 9.12 BNCweb query interface setting for search of That’s

209 215 215 216 218 219 221 225

Tables

1.1 A range of contextual variables that aid understanding language in use (adapted from Rühlemann, 2019: 6–7) 1.2 A broad summary of the main approaches to gathering and analysing data in pragmatics research 1.3 Top 20 most frequent words in the enTenTen15 corpus, The British National Corpus 1994 and the TED_en corpus 1.4 Ten most frequent two-word, three-word and four-word units in LCIE 1.5 Pragmatically specialised functions of MWUs based on O’Keeffe et al. (2007) 1.6 A list of the most frequent verbs that follow we + have + to in the TED_en corpus with examples 1.7 KEYWORD LIST 1: All of the keywords based on comparison of the Bashir–Diana Panorama interview with Spoken Media Corpus (arranged vertically in the grids in order of ‘keyness’) 1.8 KEYWORD LIST 2: A sample of the 92 keywords based on comparison of the Bashir–Diana Panorama interview with Spoken Academic Corpus (arranged vertically in the grids in order of ‘keyness’) 2.1 Terminological differences relating to roleplays (based on McDonough, 1986; Trosborg, 1995; Félix-Brasdefer, 2018) 2.2 Corpus design matrix for study of pragmatic markers 2.3 Typical codes used in a broad transcription of spoken corpora 3.1 Comparing form-to-function and function-to-form analyses routes to examine a research question 3.2 Comparing Schauer and Adolphs’ (2006) DCT results with two spoken corpora 4.1 Top 20 most frequent words in LCIE 4.2 Classification of referential items according to person, place or time reference 4.3 Frequency counts for the occurrences of we in COCA 4.4 Comparison of frequency of occurrence of yesterday, today and tomorrow with the lexicalised names for days of the week in LCIE (normalised per million words)

2 4 6 6 8 14

16

16 31 37 39 49 61 70 72 80

83

xii

TABLES

4.5 Frequency of occurrence of nouns (in alphabetical order) 1R of that in the BNC Baby and LCIE 4.6 Top 20 frequency results for that + noun (that _nn*) 5.1 Frequency counts per million words for the occurrence of please in Spoken BNC2014 and ICE-Ireland 5.2 15 strategies which Brown and Levinson list in order to avoid threatening positive face 5.3 Ten strategies which Brown and Levinson list in order to avoid threatening negative face 5.4 Culpeper’s (1996) impoliteness strategies 5.5 Negative vocatives that can be used in insults 5.6 Frequency counts for thank* in service encounters in LCIE 6.1 Distribution of speech acts in three speech situations in SPICE-Ireland (normalised per 10,000 words) 6.2 Frequency counts for why don’t you…? versus why don’t we…? in MICASE 6.3 Initiating acts (Tsui, 1994) 6.4 Requestives (Tsui, 1994: 104) 7.1 Levels of variation (Schneider and Barron, 2008: 20–21) 7.2 Frequency results for response tokens candidates in OANC (face-to-face) versus OANC (switchboard) corpora (normalised per million words) 7.3 Occurrences of um and well at turn-initial position in the OANC sub-corpora based on 100-item downsample for each 7.4 The turn-taking function of um and well in the OANC spoken sub-corpora based on 100-item downsample for each 7.5 Most frequent two-, three- and four-word clusters in BAWE 7.6 The most frequent two-, three- and four-word clusters in LCIE 7.7 The ten most frequent two-, three- and four-word chunks in BASE 7.8 Comparative frequencies of selected adjunctive VCMs in the LINT and BASE corpora (normalised per million words) 7.9 Frequency counts for the item* that type of thing in COCA 7.10 Comparative frequencies of selected disjunctive VCMs in the LINT and BASE corpora (normalised per million words) 7.11 Frequency counts for the item or whatever in COCA 7.12 Frequencies of thank, thanks and cheers in the Spoken BNC1994 versus the Spoken BNC2014 (normalised per million words) 7.13 Top ten collocates for thank in the Spoken BNC2014 7.14 Top ten collocates for thanks in the Spoken BNC2014 7.15 Top ten collocates for cheers in the Spoken BNC2014 8.1 Identifying characteristics of situational variation (based on Biber et al., 1999: 15-17) 8.2 Comparison of the top 20 most frequent words in the NHS Direct corpus and the Spoken BNC1994 8.3 Comparison of top 20 most frequent turn initial items in C-MELT and LINT 8.4 Keywords of NHS Direct corpus with LCIE as reference corpus 8.5 Keywords of C-MELT with LCIE as reference corpus

92 95 100 106 110 115 119 122 129 136 141 142 145 149 151 152 155 156 157 161 162 163 164 167 167 168 169 174 181 183 185 186

TABLES

8.6 Keywords, minus content items, of C-MELT with LCIE as a reference corpus 8.7 The ten most frequent three-word units in Sherlock Holmes corpus and Shakespeare corpus 8.8 The ten most frequent four-word units in the Jane Austen corpus 9.1 The most frequent imperative verbs in the MICUSP across the disciplines of physics, philosophy, economics, mechanical engineering and linguistics, in descending order (Neiderhiser et al., 2016) 9.2 Sample of A1 Beginners and A2 Elementary entries for future simple relating to pragmatic competence taken from the English Grammar Profile (O’Keeffe and Mark, 2017) 9.3 A sample of entries from the English Grammar Profile (EGP), illustrating the use of the affirmative form of the past simple, at A1, and tracking some of the pragmatic competence developments at B1 and B2 level 9.4 Formulaic address in different speaking and writing contexts 9.5 Ways in which we make what we say less direct (marked in bold) (based broadly on Carter and McCarthy, 2006) 9.6 A summary of hedging forms (based broadly on Carter and McCarthy, 2006) 9.7 Examples of the core functions of discourse markers in speaking

187 189 191

202

207

208 211 214 217 222

xiii

Acknowledgements

We wish to acknowledge the support and encouragement we received from Routledge in bringing the second edition of this book to fruition. In particular, we thank Louisa Semlyen (Senior Publisher) and our Editorial Assistant, Eleni Steck. We are also grateful to Hannah Rowe for her assistance at the initial stages of the project. We would also like to acknowledge the insightful blind reviews we received on how the first edition might be improved upon. One of the many helpful suggestions that came out of these reports was to add tasks, and this has become a defining feature of the second edition. Thanks also to the following friends and colleagues who have piloted tasks, given us feedback and advice on various chapters or have replied to emails seeking screenshots, permission to use data or resource screenshots, or who have chatted with us about ideas within this book: Cristina Becker Lopes Perna, Dana Gablasova, Geraldine Mark, Mike McCarthy, Tony McEnery, Pascual Pérez-Paredes, Ute Römer, Giovani Santos, Ana Terrazas-Calero, Elaine Vaughan, Martin Weisser, and the students on the Discourse and Pragmatics module of the MA in Applied Linguistics at Mary Immaculate College. Needless to say, the weaknesses of this book are ours rather than theirs! This book contains a lot of real data, as well as published results, from existing corpora, and we wish to acknowledge these sources: the British Academic Spoken English Corpus (BASE); the British Academic Written English Corpus (BAWE); the British National Corpus (BNC); the BNCweb; the BNC Baby; the Spoken BNC2014; the Business Letter Corpus; the Corpus of Contemporary American English (COCA); the Corpus of Historical American English (COHA); the English Web Corpus (enTenTen); the Hong Kong Corpus of Spoken English (HKCSE); the International Corpus of English: Ireland component (ICE-Ireland); the Limerick Corpus of Irish English (LCIE); the Limerick Corpus of Intimate Talk (LINT); the Limerick and Belfast Corpus of Academic Spoken English (LIBEL); the Cambridge and Nottingham Corpus of Discourse in English (CANCODE); the Cambridge Limerick and Shannon corpus (CLAS); the Corpus of Meetings of English Language Teachers (C-MELT) (very kindly lent to us by Elaine Vaughan); the Michigan Corpus of Academic Spoken English (MICASE); the Michigan Corpus of Upper Level Student Papers (MICUSP); the Nottingham Multi-Modal Corpus (NMMC) (funded by the UK Economic and Social Research Council (ESRC), grant numbers RES-149-25-0035 and RES-149-25-1067); the Nottingham Health Communication Corpus (NHS Direct component); the Open American National Corpus (OANC); the Speech Act Corpus of English (SPACE); SPICE-Ireland, the Santa Barbara Corpus of Spoken American English (SBCSAE), and, finally, the TED_en corpus.

ACKNOWLEDGEMENTS

Throughout the book, we draw upon screenshots of the main corpus tools. We acknowledge kind permission to reproduce these: AntConc; ELAN; #LancsBox; Sketch Engine and WordSmith Tools (Lexical Analysis Software Ltd) and web-based search interfaces for the Spoken BNC2014; the BNCWeb; Business Letters Corpus; Corpus of Contemporary American English (COCA); Google Ngram Viewer; the Michigan Corpus of Academic Spoken English (MICASE) and the Michigan Corpus of Upper Level Student Papers (MUCUSP). We acknowledge the research output drawn from the English Grammar Profile online resource (Cambridge University Press), which includes examples from the Cambridge Learner Corpus. We also reproduce, with kind permission, a screenshot sample from resources that have been developed using the Trinity Lancaster Corpus (Centre for Corpus Approaches to Social Science, Lancaster University/Trinity College London). Every effort has been made to contact copyright holders. If any have been inadvertently overlooked the publishers will be pleased to make the necessary arrangement at the first opportunity. Although he did not live to see this second edition, we will always be grateful to the late Ron Carter for his lasting inspiration. And to our partners Ger, Elaine and Nick, respectively, we say thank you for your patience, support and love, as always.

xv

CHAPTER 1

Introduction

1.1

WHAT IS PRAGMATICS?

Pragmatics is seen as a relatively young sub-field of linguistics and this is underscored when we see that the Journal of Pragmatics and Pragmatics were established in 1977 and 1991, respectively, and the International Pragmatics Association (IPrA), was founded in 1985. However, the lineage of pragmatic thought within linguistics and philosophy is much older. In order to define the span of what pragmatics has become, it is best to try to unravel the threads of its emergence. This route leads to different definitions but the process of arriving at an understanding of this definitional divergence is important in itself. Early foundational work which is centrally associated with pragmatics came from philosophers of language rather than from linguists (e.g. Morris, Austin, Grice and Searle). Importantly, pragmatics evolved out of a desire to better understand how we make meaning when we use language and a refusal to accept that it can be explained adequately through form and meaning alone. Also central to pragmatics is the quest to understand language as performance rather than as an internal language competence of the native speaker-hearer. Although early work was solely introspective (involving reflection and thought) rather than empirical, it still focused on the conditions of use and performance. A perusal of the history of pragmatics shows that two different approaches or schools of thought began to emerge early on, namely the Anglo-American tradition and the Continental European tradition (see Jucker (2012) for an overview). The former looks at language in more micro-detail, whereas the latter takes a more macro-view of language and its social contexts. The Anglo-American school of thought treats pragmatics as one of the core components within linguistics, along with semantics, syntax, morphology and phonology. Within this component view, pragmatics is concerned with the study of presuppositions, deixis, implicatures and speech acts. This focus is sometimes referred to as micropragmatics (Mey, 2001). This contrasts with the more macropragmatic position of Continental European pragmatics which takes a broader understanding of language in use, giving a different perspective on human communication (Mey, 2001). Continental European pragmatics is thus sometimes referred to as the perspective view and deals with a more extensive remit, including the social and cultural dimensions and conditions of language in use. The differing schools of thought and resultant perspectives, approaches

2

INTRODUCTION

and methods within pragmatics is not problematic. If anything, the vibrant scholarship from both a micro- and a macro-perspective on the nature, conditions and variables of language use adds to the breadth and depth of the field as a whole. Because this book involves looking at naturally occurring language use, especially through corpora, there is often crossover between micropragmatic items such as deixis or speech acts and how they manifest at a macro-level across social variables and conditions. While this book does not involve introspective approaches to research, it benefits greatly from the scholarship in this area in relation to core areas of pragmatics. Therefore, in defining pragmatics, we embrace the richness across both component and perspective positions. For us, the best definition of pragmatics remains a broad one which we cited in the first edition of this book, namely that of Fasold (1990: 119), who says that it is ‘the study of the use of context to make inferences about meaning’, where inferences refer to the deductions we make based on available evidence. In the following section we explore further the notion of context and how it can be studied.

1.2

WAYS OF STUDYING PRAGMATICS

Within a broad definition of pragmatics, we are looking at language in use and at meaning in the making. As discussed above, core to this endeavour is trying to account for the variables of ‘context’ in understanding language in use. Rühlemann (2019) offers some useful parameters for understanding the contextual variables of language. His non-exhaustive list is summarised in Table 1.1. Table 1.1 A range of contextual variables that aid understanding language in use (adapted from Rühlemann, 2019: 6–7) Variable

Description

sequential context activity context

The utterance(s) that precede and follow an utterance; the utterance(s) that can be expected to follow an utterance. The recognisable activity that the speaker and the hearer are engaged in at the time of the utterance. The time and place when the utterance was made; the receiving, time and place of the utterance (for the listener or reader). The speaker’s bodily conduct into which the utterance is integrated (e.g. posture, direction of gaze, how close they are to the speaker, whether they move their head or hand when making an utterance, etc.). What the speaker intends to say in making an utterance, which often may not be apparent on the surface structure of the utterance. The speaker’s emotional involvement with the entity the utterance is about. The (possibly infinite) range of the speaker’s and the hearer’s knowledge. The power semantic or role relationship that holds between the speaker and the hearer.

spatiotemporal context multimodal context intentional context emotive context epistemic context social context

From Rühlemann’s (2019) list we can see that there is a broad matrix within which we interpret and make meaning, both as interlocutors (speaker and hearer) and as observers from the outside.

INTRODUCTION

TASK 1.1 CONTEXT AND LANGUAGE IN USE 1)

Consider the variables in Table 1.1 above. What new variables might be added to this list? Or, how might any of these be modified or subdivided? In relation to two languages that you are familiar with, discuss how some of these variables might differ across these languages and related cultures (e.g. in relation to the activity context).

2)

Language is shaped and reshaped by contextual variables. This is a key consideration when designing ways of researching pragmatics, especially in terms of either narrowing down or controlling some of these variables, or dealing with their complexity (e.g. power semantic, role, mode, etc.). We will return to this issue in greater detail in Chapters 2 and 3.

1.3

THE EMPIRICAL TURN WITHIN PRAGMATICS

While it is noted that the empirical turn came late to pragmatics (Taavitsainen and Jucker, 2015), the field is not without a range of methodological models for gathering data (as we will discuss in detail in Chapter 2). In order to examine language empirically, a valid and reliable method of obtaining the data is needed. The main approaches in pragmatics are: to elicit samples of the pragmatic phenomenon; to observe language and note how it is used in a given context; to interview speakers about how they might use language or about their opinions on language use, or to examine samples of recorded language that is stored electronically in a corpus. Jucker et al. (2018) divide these across the following types of empirical methodological approaches: • • •

Experimental pragmatics: e.g. using discourse completion tasks (DCTs), roleplays or interviews; Observational pragmatics: e.g. using ethnographic approaches, involving observation, field notes and the analysis of recordings; Corpus pragmatics: e.g. either through building a small corpus of language or using a large existing corpus.

We will take a detailed practical look at these methodological approaches in Chapter 2. This section serves as a general overview. Over the years, with the growth of studies using empirical data in pragmatics, it cannot but be noticed that a range of analytical frameworks can be used. We attempt to summarise these in Table 1.2 across six approaches: experimental, ethnographic, ethnomethodology/conversation analysis, discourse analysis, critical discourse analysis and corpus pragmatics. In reality, approaches to pragmatics research are rarely siloed. By drawing upon synergies in approaches, the researcher can find the optimum means of gathering and analysing data. This can, for example, mean that an ethnographic approach will use corpus tools to

3

The researcher is immersed in a community and makes observationbased field notes as well as video or sound recordings.

Very short recordings are made or identified for a very specific context (e.g. calls to a radio phone-in or emergency helpline).

Short recordings or texts from a specific context are gathered (e.g. a classroom). Individual recordings of (usually) public speech events or texts are gathered (e.g. a political speech, a newspaper article on Brexit, Tweets on a specific topic). Large corpora are accessed, usually online, or small corpora can be built through text curation or through recordings. These are transcribed and sometimes annotated (e.g. for all instances of a pragmatic phenomenon).

Ethnographic approach

Ethnomethodology and conversation analysis

Discourse analysis

Corpus pragmatics

Corpus tools are used to recall search items from the corpus. Pragmatic items may derive from word or multi-word unit frequency lists or from keyword analysis. Alternatively, pragmatic functions may be recalled if the data has been pragmatically annotated or if existing knowledge of speech act manifestations, such as illocutionary force identifying devices (IFIDs), are used as the basis for searches. Concordancing is used to look at these search items in a more contextualised way. There is often a need for close analysis of large amounts of concordance lines to manually categorise the function of a given form.

Usually, small samples of language are viewed from a critical perspective (e.g. the power semantics of the pronouns used in a text; the use of modality and stance in political interviews; vagueness or deixis in news reports, etc.).

The analytical focus is mostly on how speech acts manifest across variables such as speaker relationship, power semantic, L1 background which allow for pragmatic conclusions resulting from micro-analysis. Much of the interpretation of DCTs draws upon conversation analysis. The large sample of responses elicited using the prompt task are analysed for patterns of language use within or across turns, and this is often formulaic or routinised. Where relevant, turn organisation can be examined and compared across contextual variables. Observations, field notes and transcribed recordings are thematically analysed for an in-depth understanding of how language is used in a specific context. Language use in a community is analysed in an iterative way, where the researcher moves between hypothesising about how interactions take place based on observations and close analysis of the actual interactions. This leads to a ‘thick’ description of community activities (Marra and Lazzaro-Salazar, 2018: 359). Very detailed transcriptions of the turn-by-turn unfolding interactions are analysed so as to establish turn preference, order and canonical sequencing within given situations. This approach involves looking in micro-detail at short stretches of interaction (e.g. a call opening) and, from this, generalisations can be made about role, power or context as they emerge through the turntaking order and sequence. Spoken or written texts are analysed for pragmatic features (e.g. pragmatic markers) or discourse features (e.g. text organisation).

Prompts are used to elicit a pragmatic phenomenon (e.g. speech act) using a discourse completion task (DCT), roleplay or interview.

Experimental approach

Critical discourse analysis

How is language analysed?

How is language typically collected?

Approach

Table 1.2 A broad summary of the main approaches to gathering and analysing data in pragmatics research

4 INTRODUCTION

INTRODUCTION

enable large-scale annotation and analysis. A researcher who crowd-sources discourse completion test (DCT) responses using an online platform may find that corpus linguistics offers a useful tool for annotating the results and identifying formulaic use of language across a large sample. Within the same study, the researcher may find that conversation analysis best aids the interpretation of power asymmetry in the results from the DCT within a qualitative sample. Throughout this book, we take the perspective that corpus linguistics offers much to better our analysis of data in pragmatics. We are now at a stage where we talk about corpus pragmatics and this approach is evolving in terms of its definition (see Adolphs, 2008; Romero-Trillo, 2008; O’Keeffe et al., 2011; Rühlemann and Aijmer, 2015; Clancy and O’Keeffe, 2015). The main corpus tools can tell us the most frequent words or phrases in a corpus as well as the keywords when compared with another corpus (see below). These can then be examined in much more contextual detail using concordance searches. However, corpus tools will neither interpret from nor hypothesise about actual language use. Corpus software will identify strong patterns based on frequencies or other statistical measures and this will strongly indicate tendencies, but, for a broader understanding of language in use, other frameworks have been used. Let us briefly survey the main functions of corpus tools and how these relate to pragmatics. Within this overview, we will illustrate how some other approaches and frameworks shown in Table 1.2 interplay in corpus pragmatics.

1.4 THE MAIN FUNCTIONS OF SOFTWARE TOOLS USED IN CORPUS PRAGMATICS Word and multi-word frequency lists The frequency of a word or a phrase (multi-word unit) tells us about its profile and use. If a word or phrase recurs in a given context, it is usually indicative of a salient feature. For this reason, frequency lists are seen as a good starting point for the analysis of a corpus. As a first step into corpus data, a researcher will look at the word list results and this is often done by comparing it with another word list from a different corpus. When looking at a word list comparatively, the researcher is normally more concerned with the distribution at the top of the rank order list (i.e. the top most frequent words or phrases). The British National Corpus (BNC) (see Appendix) offers a benchmark for typical rank order, for example, the, of, an, to and a are the first five most frequent items (in that order). In order to discover instances of the pragmatically specialised use of language, we might take this set as our baseline and follow up on any differences that might occur, as we illustrate in Task 1.2.

TASK 1.2 COMPARING WORD FREQUENCY RESULTS Consider the word lists in Table 1.3. It shows actual (‘raw’) results for the top 20 most frequent words in three different corpora:1 the EnTenTen15 (internet texts); The BNC1994 (spoken and written) and the TED_en corpus (TED talks). Notice how the rank order of the first five items is very similar across the three corpora.

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INTRODUCTION Table 1.3 Top 20 most frequent words in the EnTenTen15 corpus, The British National Corpus 1994 and the TED_en corpus EnTenTen15

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20.

BNC1994

TED_en

Item

Freq

Item

Freq

Item

Freq

the and of to a in for is that on with it as are I this be by at from

936350691 524890456 486715646 428396439 329062259 323377556 182058823 178334830 143529237 122967806 119656593 101713396 101373405 89170986 88646595 87053543 83961228 80782924 78206830 75534320

the of and to a in that it is was for I on you with as be he at by

6054939 3049448 2624147 2599451 2175967 1945533 1120750 1054366 991771 883547 880805 872236 731234 668407 659976 655175 651542 641241 524061 513428

the and to of a that I in it you is we this so they was for are have what

139811 100004 82141 77277 70445 63294 55178 52061 51668 49459 44783 44704 34470 25350 22288 20934 19387 18777 18663 18162

Look at the order of the words from the sixth to the twentieth most frequent (these are shaded in Table 1.3). 1) 2) 3)

Circle the words that stand out as being different in their rank order of frequency. Taking the different types of corpora into consideration, speculate as to why these words you have circled might be more or less frequent than in the other lists. If you have access to these corpora, examine the words you have identified by looking at them in concordance lines. Check if your intuition is correct (see also the section on concordance lines and task 1.4 where we follow up on this).

Corpus software can also count phrases (combinations of words) that frequently recur; for example, Table 1.4 shows the top ten most frequent two-, three- and four-word units in the Limerick Corpus of Irish English (LCIE) (see Appendix). Table 1.4 Ten most frequent two-word, three-word and four-word units in LCIE Frequency rank 1 2

Two-word units you know in the

4406 3435

Three-word units I don’t know do you know

Four-word units 1212 769

you know what I know what I mean

230 215

INTRODUCTION

Table 1.4 Continued Frequency rank

Two-word units

3 4 5 6 7 8 9 10

of the do you I don’t I think It was I was going to on the

2354 2332 2200 2003 1939 1891 1849 1801

Three-word units a lot of you know what do you want I don’t think you know the you have to going to be yeah yeah yeah

Four-word units 522 379 373 338 323 308 307 297

do you know what I don’t know what do you want to are you going to you know the way I don’t know I thank you very much the end of the

208 134 121 103 103 91 91 85

This corpus software function has added much to our understanding of multi-word units (MWUs). The many terms that have evolved under the umbrella term multi-word units (MWUs) reflects the ongoing attempt to find the best methodology for both counting and accounting for the fact that some words seem to occur in units with other words. These terms often come with slightly differing definitions and include, inter alia: formulas, formulaic units, formulaic sequences, routines, fixed expressions, prefabricated patterns (prefabs), clusters, chunks, concgrams, strings, n-grams and lexical bundles/lexical phrases (see Greaves and Warren (2010) and Gray and Biber (2015) for coverage of differing terminology, methodologies and research findings). For the purposes of this book, we opt to use the umbrella term multi-word unit (MWU) unless we are discussing a particular study or relevant finding. Some key issues and findings from research to date include the following: •

• •

•

•

MWUs are very common and are defined differently across a number of studies. Terminology and definitions are tied up with important variations in retrieval methods (What constitutes a unit?; What is the frequency cut-off for inclusion?, etc.); MWUs can be examined as continuous (e.g. you know what I mean) or discontinuous (e.g. the * of * ) sequences; We can talk about the length of an MWU in terms of whether it is across two-, three-, for-, five- or six-word slots and, within these units, we can examine the fixedness or variability of the constituent components; MWUs vary in frequency across speech and writing. For example, Biber et al. (2004) found lexical bundles to be more frequent in speech than in writing. Other studies found that continuous units were more frequent in speech, whereas writing (especially academic registers) relies heavily on discontinuous units which act as frames (Biber, 2009); MWUs vary across registers and many units have become pragmatically specialised in terms of their discourse function (see Chapter 8).

The study of MWUs is important for pragmatic research because they are often associated with functions such as stance marking, focus, text organisation and referential meaning. O’Keeffe et al. (2007), for example, examined MWUs in the Cambridge and Nottingham Corpus of Discourse in English (CANCODE) (see Appendix), and found that many items had pragmatically specialised functions in spoken interactions, summarised in Table 1.5.

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INTRODUCTION Table 1.5 Pragmatically specialised functions of MWUs, based on O’Keeffe et al. (2007) Function

Example

Discourse marking Face and politeness (mitigation) Vagueness and approximation

you know; I mean; and then; but I mean; you know what I mean; at the end of the day do you think; do you want (me) (to); I don’t know if; what do you think; I was going to say a couple of; and things like that; or something like that; (and) that sort of thing; (and) all this/that sort of thing

Other items can be appear to be functionally less specialised but often these items relate to the world of the speaker or writer. That is, they are frames for referential meaning – to refer to the shared world of the interlocutors (see Biber et al., 2004; O’Keeffe et al., 2007; Biber, 2009; Greaves and Warren, 2010). We will explore referential frames in Task 1.3 (based on some selected results from O’Keeffe et al., 2007; Biber, 2009; Gray and Biber, 2015).

TASK 1.3 EXPLORING MULTI-WORD UNITS Examine the following high-frequency multi-word units (MWUs) based on existing research which operate as frames (* marks a slot that can be filled by various possible words): of the * of 1)

it was *

3)

in the *of

on the * of

Think of words that might go into the empty slot marked by * and then sort the phrases that you have generated into the following common referential categories. Try to come up with three examples for each category.

Referring to time

2)

at the * of *

Referring to place

Referring to somewhere in a text

Which other category might you add to finish categorising the phrases you have generated? Can you think of longer phrases that these items might frame across these three functions (e.g. It was getting late; In the beginning of the century, etc.)?

We will be exploring MWUs in terms of their pragmatic meaning and discourse function in a number of chapters in this book. Within a corpus pragmatic approach, what interests us most is how these units function pragmatically across different contexts of language use.

Concordance lines As discussed above, word frequency lists, when examined comparatively, can point to the possibility of a word having some specialised meaning or use in a particular context. This

INTRODUCTION

can sometimes lead to insights about pragmatically specialised uses when a form is further investigated. Therefore, it is essential that frequency analysis is complemented by a detailed consideration of the environment of a word through the use of concordance tools. A concordance, as defined by Sinclair (2003: 173), ‘is an index to the places in a text where particular words and phrases occur’. In a concordance, the search word you enter will appear in the middle of the search screen (see Figure 1.1). This word is referred to as the node (in Figure 1.1, have is the node). There are, however, some caveats concerning concordance lines. The first is that although they provide information on a node (the search word), they do not interpret it. It is the responsibility of the researcher to use the software to determine the patterns that are salient and to construct hypotheses as to why these patterns occur. Therefore, as Baker (2006: 89) states, ‘a concordance analysis is … only as good as its analyst’. We will now exemplify some of the typical phases that a researcher might undertake in the process of hypothesis formation, moving iteratively between word lists, concordances and patterns. In Task 1.2, when looking at words that seem to be at a higher or lower rank order across the three lists in the task, you may have noticed the word have. It is in the top 20 most frequent words from the TED_en corpus but it does not appear in the top 20 most frequent words in the other two corpora, EnTenTen15 and the BNC. This points to the possibility of being used in some specialised way in the TED talks data. When we create a concordance of have in the TED_en corpus and we sort it to the right of the node (i.e. organise the words immediately to the right of have in alphabetical order), we can check for any interesting patterns by scrolling down through the screens of results (see Figure 1.1). In scrolling through the screens we are trying to identify patterns, and the norm is to look for patterns both to the right and left of the node word through sorted searches. To further examine the patterns of have, we can use the ‘collocates’ function, which is normally available as part of a corpus tool (see more on collocates below). As Figure 1.2 illustrates, the software will instantly calculate the most statistically salient words that co-occur to the left and right of the node word have. Based on the results in Figure 1.2, any of the top collocates listed merit further investigation based on their statistical salience.2 By way of illustration, we will examine the first item we by looking at the patterns of we + have in a concordance (as illustrated in Figure 1.3). Next, we use the software to calculate the most frequent words immediately to the right of we + have (often referred to as 1R). The top ten results are shown in Figure 1.4. The results of this search in Figure 1.4 give us more possible routes of investigation. Let us follow the first line by examining to. The concordance lines of we + have + to will show us more patterns. In Task 1.4, we will explore the collocates of we + have + to. For a researcher, this process would be undertaken by close analysis of concordance lines. In Table 1.6 we have put together some concordance examples by way of illustration. Reflecting on the patterns in Table 1.6, we can hypothesise that we have to + [verb], used in TED talks, is gaining a pragmatically specialised use in a requestive context to make a call for action or a strong appeal. We note that speakers use we rather than you when addressing their audience so as to make the request inclusive and global. We may also speculate that this use is particularly associated with contexts of public discourse on the issue addressing global climate change.

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Figure 1.1 A sample of concordance for have in the TED_en corpus sorted 1R (using Sketch Engine)

INTRODUCTION

Figure 1.2 Top ten collocates of have in the TED_en corpus (using Sketch Engine), examining all word candidates three to the left and three to the right of we

There are many ways of examining and interpreting concordance line data and it is a process that is central to corpus pragmatics. Here we consider it in greater detail based on the seminal work of Sinclair (1996). Concordance output facilitates an inductive approach by helping the user notice patterns relating to how a lexical item or MWU is used in context. In order to describe the nature of individual units of meaning, Sinclair (1996) suggests four parameters that are important to the process of interpreting a concordance: collocation, colligation, semantic preference and semantic prosody: 1)

Collocation: refers to lexical patterning and the probability of two words co-occurring frequently next to or near each other: blonde hair, make an effort, do one’s duty, torrential rain, strictly forbidden, a major incident. Some collocate relationships are strong because the possibilities of other combinations are few. For example, make/express/ fulfil + wish are strong collocates because wish does not collocate with a wide range of verbs, whereas the adjective big + car, town, house are weak collocations because big can collocate with many words (Carter et al., 2011). Corpus software will help you calculate the strength of a relationship between two words (see Figures 1.2 and 1.4).

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Figure 1.3 Concordance sample of we + have as the node (sorted 1R)

INTRODUCTION

Figure 1.4 Top ten most frequent words to the right of we + have in the TED_en corpus (using Sketch Engine)

2)

3)

4)

Colligation: refers to the grammatical patterning of words and the likelihood of the co-occurrence of grammatical choices. By using a certain verb, for example, this may co-select a particular syntax. For example, we say I was discharged from the hospital rather than I was discharged out of the hospital. Even though from and out of both imply exiting from the building, only from colligates with discharge. When we refer to leaving a hotel, we use a different verb entirely and we use active voice and out of, as in I checked out of the hotel. The strength of a colligational pattern is also included by software in its collocates function (see again Figures 1.2 and 1.4 where a number of grammatical items are included). Semantic preference: refers to how collocates can, through usage, appear to have a preference for a particular semantic domain. For example, in his discussion of the expression ‘the naked eye’, Sinclair (1996) finds that most of the verbs and adjectives that collocate with this expression are related to the concept of ‘vision’. A search for the collocates of the naked eye using COCA shows visible, invisible, seen, see, appears, looks all within the top ten most frequent collocates to the left of the search phrase. Semantic prosodies: associations that arise from the collocates of a lexical item are not easily detected using introspection (Sinclair, 1987; Louw, 1993). Semantic prosodies have mainly been described in terms of their positive or negative polarity (Sinclair, 1991; Stubbs, 1995). For example, naked eye is often found in relation to objects that cannot be seen with the naked eye. Carter and McCarthy (1999) illustrate the negative prosody associated with the get passive in the corpus data they examined (e.g. get arrested, get sued, get nicked). Rühlemann (2010) notes the negative prosody of set in (e.g. boredom can easily set in).

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INTRODUCTION

TASK 1.4 CORPUS LINGUISTICS AND LANGUAGE PATTERNS Table 1.6 shows us the most frequent verbs that follow we + have + to in the TED_en corpus. Examine these verbs and their examples. 1) 2)

What hypotheses can you form about possible pragmatically specialised uses of we + have + to + [verb] in TED talks, based on Table 1.6? How might you follow up on these hypotheses using the TED_en corpus or another corpus?

Table 1.6 A list of the most frequent verbs that follow we + have + to in the TED_en corpus, with examples Word

Frequency

Example

1) 2) 3) 4) 5)

do make get be go

67 33 33 30 27

6)

have

25

7)

start

22

8)

deal

21

9)

change

20

solve

18

… we have to do something now. We have to change now. We have to make this happen. So we have to get used to the idea of eating insects. So we have to be disciplined and focus on things that are critical. And we have to go also beyond traditional diplomacy to the survival issue of our times, climate change. But we have to have these priority changes, we have to have infrastructure to go with this. … we have to start seeing it exactly as it is, with all of its problems, because it’s only by seeing it with all of its problems that we’ll be able to fix them and live in a world in which we can all be happily ever after. But I believe there’s a second climate crisis, which is as severe, which has the same origins, and that we have to deal with with the same urgency. We have to change the culture and the feelings that politicians and school board members and parents have about the way we accept and what we accept in our schools today. We have to solve the pollution, we have to solve the congestion.

10)

At this point, let us distinguish between collocation, colligation and multi-word units (MWUs) (detailed above); we note that collocation and colligation are concerned with the co-occurrence relationship of one word with another word rather than as a unit. Crucially, the researcher sets out to examine the collocational or colligational relationship of a given word in a more top-down manner. That is, they choose to examine it as we did here with the word have and its patterns. A researcher looking at MWUs takes a more open, bottom-up approach through corpus software searches for n-gram units within the parameters they set (e.g. a researcher might opt to find two-, three-, four-, five- or six-word units, with a minimum frequency cut-off of 20 per million, etc.) (see Greaves and Warren (2010) and Gray and Biber (2015) for useful background on this topic). Both top-down collocational and colligational analyses and bottom-up MWU approaches are important to corpus pragmatics

INTRODUCTION

and, in both cases, it is through concordance line analysis that we can analyse meaning, discourse function and ultimately pragmatic specialisation.

Keyword analysis Keywords can be described as words (or MWUs) which occur with unusual frequency in a text or a set of texts in a corpus when compared to another corpus. The corpus used for comparison is called the reference corpus. Keywords are identified on the basis of statistical comparisons of word frequency lists from the reference corpus and the corpus under investigation (referred to as the target or study corpus). The frequency of each item in the target corpus is compared with its equivalent in the reference corpus and the statistical significance or difference is calculated using chi-square or log-likelihood statistics (see Dunning, 1993). The choice of the reference corpus used as the basis for comparison in the calculation of keywords is important because it will affect the output of keywords (Gabrielatos (2018) offers detailed coverage of this). When generating keyword lists, it is best to try more than one reference corpus and to consider the differences in the results. In general terms, the closer the reference corpus is in terms of genre, the fewer keywords will result because fewer items will be unusually frequent. Conversely, the more distant a reference corpus is in terms of genre from the target corpus, the more words will have comparatively more unusual frequencies, and so more keywords will normally result from the comparison. These differences (as a result of using different reference data) are in themselves telling, as Task 1.5 illustrates.

TASK 1.5 COMPARING KEYWORD RESULTS Table 1.7 and 1.8 show two sets of keyword results. Both lists are generated from the same text but use different reference corpora. The target text was the well-known 1995 BBC 1 Panorama television interview by Martin Bashir with Diana, Princess of Wales.3 Review and compare the list and consider these questions: 1) 2) 3)

What are the main differences between these two lists? What might account for these differences? Which list is most useful and why?

Target corpus: Panorama interview 8,301 words Reference corpus 1 SPOKEN MEDIA: a corpus of 271,553 words comprising a range of transcripts from media interviews: 29 political interviews; 46 interviews on TV chat shows and radio involving known or public personae; and 17 interviews from radio phone-ins drawn from international English-speaking media sources, including from the UK, USA, Canada, Australia and Ireland (see O’Keeffe, 2006). Reference corpus 2 SPOKEN ACADEMIC: a 500,000-word corpus, The Limerick-Belfast Corpus of Academic Spoken English (LIBEL) (see Appendix).

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INTRODUCTION Table 1.7 KEYWORD LIST 1: All of the keywords based on comparison of the Bashir–Diana Panorama interview with Spoken Media Corpus (arranged vertically in the grids in order of ‘keyness’) did

husband

difficult

queen

your

was

had

William

Were

children

Wales

uh

royal

yourself

media

prince

monarchy

my

because

depression

marriage

bulimia

role

relationship

husband’s

Table 1.8 KEYWORD LIST 2: A sample of the 92 keywords based on comparison of the Bashir–Diana Panorama interview with Spoken Academic Corpus (arranged vertically in the grids in order of ‘keyness’) was

I’ve

I’d

because

people

think

I

it’s

marriage

monarchy

difficult

never

don’t

me

people’s

myself

public

wasn’t

husband

uh

bulimia

role

there’s

Mr.

my

yes

you’re

husband’s

yourself

princess

I’m

didn’t

queen

couldn’t

relationship

royal

did

had

William

divorce

feel

pressures

Wales

prince

were

that’s

loved

albeit

Some commentary on the keyword lists in Task 1.5 is based on O’Keeffe (2006, 2012) and Vaughan and O’Keeffe (2015). On one hand, the results in Table 1.8, based on the more ‘distant’ reference in terms of its genre, appear more wide-ranging (in all there are 92 keywords from this calculation) and capture more of the ‘aboutness’ of the target text (Phillips, 1989). We find common first- and second-person pronouns I, I’m, my, myself, yourself and me arising as keywords because they are not high frequency in academic lectures and thus arise as ‘unusually frequent’. We also see keyword results (Table 1.8) that reference the more private sphere of the ‘I–you’ domain, including husband–wife relationships, love, bulimia, marital breakdown, etc., all of which would not normally be talked about in the more referential world of academia. Meanwhile, in Table 1.7, we see that by using a reference corpus that was close in genre to the target text there were far fewer items. In other words, we can say that the results in Table 1.7 possibly represent more salient keywords because, despite the reference corpus being close to the target, these words are still used with unusual frequency by comparison. Therefore, working through concordances of this candidate list might be more productive (and more doable in scale). Gabrielatos (2018) notes that the size of the reference corpus is not as important as the representativeness of each corpus, and the principled selection of corpora to be compared. Finally, a comment on the challenges of spoken corpora. In Tables 1.7 and 1.8, we notice that the vocalisation uh appears as a keyword in both lists. This is most likely a function of the variation in the transcription of vocalisations in the reference corpus which comprises many media transcripts. Some transcribe the same or similar vocalisation as

INTRODUCTION

uhm, erm or ah, among others. This is an important point regarding the analysis of spoken corpora: if similar words or vocalisations are transcribed differently, this will have a bearing on keyword calculations (for more on transcription, see Chapter 2).

1.5

THE STRUCTURE OF THIS BOOK

This book is structured around nine chapters. These move from introductory matters in this chapter, including the history, origin and emergence of the field and an overview of the application of different analytical frameworks in empirical research. In this chapter we also cover the basic functions of corpus tools because it sets the scene for much of what we talk about in other chapters. Chapter 2 looks in detail at how pragmatics can be researched. This chapter showcases quite a large toolkit available to a researcher who is interested in gathering data for pragmatics research. It distinguishes between elicited, observed and recorded data, and guides the reader through the different instruments that can be used under these three broad headings. All methods have pluses and minuses and we try to present a balanced view. Although we clearly have a preference for using corpus data, we are keen to stress that other methods have a lot to offer in themselves and if used in conjunction with corpus tools (as we explore in detail in Chapter 3, see below). The main point to take away from Chapter 2 is that there is a need for methodological awareness. Some methods can be highly controlled so that the researcher can be very precise in the language that they elicit but this is at the expense of the degree to which the researcher compromises on the naturalness of the data. On the other hand, naturally occurring data can be elicited and recorded through note-taking or digital recording but the researcher has little control over the data that results and this can pose challenges for pragmatics research. What is interesting in Chapter 2 is the range of approaches that have emerged for gathering research data within the empirical turn in pragmatics, as we have already alluded to in this chapter. Chapter 3 focuses on corpus pragmatics, a recent coinage for the coming together of corpus linguistics and pragmatics. The chapter addresses the processes of doing corpus pragmatics research in a way that accommodates different approaches. Corpus pragmatics usually works from frequencies of forms to their pragmatic function in what is termed a form-to-function approach (this is exemplifed in this chapter through our analysis in the section on concordance lines, for instance). In this approach, the frequency lists and concordance lines ultimately lead us to a conclusion about the use of a form (e.g. we have to in TED talks; see above). The opposite approach is to begin with the function (e.g. a speech act), and to try to narrow down the range of possible forms used to perform this and to use these forms to find language instances in a corpus. For example, the words and phrases typically associated with a speech act (as a result of experimental research, such as illocutionary force identifying devices (IFIDs)) can be used to search a large corpus to retrieve examples. This approach is referred to as a function-to-form approach. In an ideal world, function-to-form approaches are facilitated by pragmatically annotated corpus data so that all instances of a given speech act or pragmatic phenomenon (such as a pragmatic marker) can simply be recalled. At the time of writing, pragmatic annotation is fast developing (see Weisser, 2015; Archer and Culpeper, 2018).

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INTRODUCTION

Chapter 4 furthers our exploration of key concepts within the study of pragmatics through its focus on reference. The chapter covers its general definition as well as going into analytical depth in terms of how deictic reference can be examined using corpus pragmatics. Deixis represents the intersection of grammar and pragmatics, and the chapter explores many of these grammatical items such as the personal pronouns you and I and the demonstratives this and that. This chapter showcases the potential of corpus pragmatics for examining the relationship between the context of the utterance and the referential practices therein. This relationship is shown to characterise the very nature of our pragmatic systems. In Chapter 5, we explore politeness theory through the lens of a number of different models. Within these paradigms, we examine some key features using corpus pragmatic techniques. For example, we explore Brown and Levinson’s (1987) concepts of positive politeness through a case study of vocatives, and negative politeness through a micro-study of hedging across different contexts of use. In this chapter, we also look at the concept of impoliteness in the context of naturally occurring data. Finally, we examine discursive politeness where we look beyond linguistic structures to include the individual’s interpretation of these structures as (im)polite in instances of ongoing verbal interaction. This brings to the fore the dynamic notion of relational work. Speech acts are the focus of Chapter 6, which examines the link between linguistic forms in the shape of speech acts and their function in context. We provide an overview of Speech Act Theory and discuss the main arguments and underlying assumptions on which this theory is based. This includes a discussion of direct and indirect speech acts, performatives and constatives, and the broad taxonomy of different speech act categories such as directives or commissives. The chapter also looks at the way in which context and co-text impact upon the analysis of speech acts in a discourse framework. Throughout this chapter, we explore ways of using corpus pragmatics in the form-to-function analysis of speech acts. This adds further context to issues discussed in both Chapters 2 and 3. Drawing upon a range of different corpora, Chapter 7 examines pragmatic variation within a language. As we note, the study of language variation has traditionally focused on phonological, lexical and syntactical levels, particularly taking an historic view. The systematic study of variation at a pragmatic level is a relatively recent development by comparison. This chapter also highlights the broadening of the variational focus from phonology, lexis and syntax to variation in social space. This is achieved through explorations of variation from a macro-social perspective (e.g. factors such as age, gender, ethnicity, social class, etc.), and from a micro-social perspective (e.g. more ‘local’ factors such as the degree of social distance between participants (strangers, friends, family) or power (an employee talking to her or his boss)). To contrast with the focus of Chapter 7 on variation within a language, we go a level deeper in Chapter 8 to examine variation in terms of register. In this chapter, we will explore the notion that specific registers involve the pragmatically specialised use of language. In doing so, we will draw upon naturally occurring language from a range of contexts, including casual conversation, healthcare communication, crime fiction, service encounters and Shakespearean drama. The chapter again employs a corpus pragmatic approach to the examination of features characteristic of these specific situations. This chapter also builds on Chapter 2 in relation to the synergies between conversation

INTRODUCTION

analysis (CA) and corpus linguistics, offering some useful examples of how CA can aid in the analysis of corpus data. The final chapter in our book, Chapter 9, looks at pragmatics and language teaching, and considers the degree to which it is teachable and learnable in the context of the ongoing debate in Second Language Acquisition (SLA) studies in relation to implicit and explicit learning. The chapter explores areas of pragmatics that can be addressed in the classroom, through both hands-on corpus tasks as well as through the curation of teacher-led activities and materials. The chapter includes a wider range of samples of classroom materials based around the teaching of politeness and spoken grammar, including pragmatic markers (discourse markers, response tokens, etc.), as well as vagueness and stance markers. Developments in learner corpus research in terms of how it can inform language teaching are showcased through learner corpus-based resources that are differentiated by level of proficiency. Throughout the chapter, there is an emphasis on modelling corpus tasks based on existing research findings, as it is argued that this offers a means for bringing focus to pragmatic competence within curriculum, syllabus and materials design. Each chapter in this book contains an annotated further reading section intended to guide the reader to texts that expand upon key topics discussed in each chapter. The book also includes, as this chapter has demonstrated, tasks which are embedded within key topics. Some of these tasks involve reader interaction with specific corpus interfaces and specially designed corpus software. Our goal is to show the reader how the interfaces and software can be used in corpus pragmatic research – should more information about the specifics of using these tools be required, there are some very helpful textbooks available (see e.g. O’Keeffe and McCarthy, 2010; Weisser, 2016a; Anderson and Corbett, 2017). We do not assume that a reader will undertake all of these activities, but we hope that they offer an instructive application of the core concepts that we are discussing.

1.6

FURTHER READING

Aijmer, K. and C. Rühlemann (eds), 2015. Corpus Pragmatics: A Handbook. Cambridge: Cambridge University Press. Because corpora came relatively late to pragmatics, this volume marks an important and significant stage in the establishment and coinage of ‘corpus pragmatics’ as a sub-field of pragmatics. In addition to the 16 chapters, the volume includes an important introduction to the volume by Aijmer and Rühlemann, which takes on a foundational role for the use of corpora in the empirical study of pragmatics. Clancy, B. and A. O’Keeffe, 2015. Pragmatics. In D. Biber and R. Reppen (eds), The Cambridge Handbook of English Corpus Linguistics. Cambridge: Cambridge University Press, pp. 235–251. This chapter showcases the potential of corpus pragmatics to bring insights through research into forms, their patterns and pragmatic functions in large corpora. It covers aspects of deixis, pragmatic markers, language and power; discourse organisation, and provides a case study on the use of a corpus to explore vocative forms and their functions.

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Jucker, A. H., 2012. Pragmatics in the history of linguistic thought. In K. Allan and K.M. Jaszczolt (eds), The Cambridge Handbook of Pragmatics. Cambridge: Cambridge University Press, pp. 495–512. This chapter offers a wide-ranging overview of the emergence of pragmatic thought and how it developed across two schools, the Anglo-American and Continental European traditions. By reading this chapter, a student of pragmatics will gain greater insight into why there are very different approaches within the field, ranging from introspective to empirical in terms of research method. Schneider, K.P. and A. Barron (eds), 2014. Pragmatics of Discourse. Berlin: Mouton de Gruyter. This edited volume brings together 21 chapters addressing approaches to the analysis of discourse pragmatics, including discourse markers, stance, speech act sequences as well as an overview of work across different contexts, including legal, medical, media and classroom discourse domains. In terms of approaches to discourse analysis within which pragmatics can be viewed, it includes work on conversation analysis, systemic-functional linguistics, genre analysis, critical discourse analysis, corpus linguistics and multimodal pragmatics.

NOTES 1 See Appendix for corpus details. 2 Figure 1.2 illustrates the log dice results as a measure of collocation candicacy based on 4895 co-occurrences of we with have from all the possible 44,704 candidates of we in the TED_ corpus. For more on statistics in corpus linguistics, see Brezina (2018) and Gries (2015), among others. 3 Broadcast in November 1995, the interview transcript is available at www.bbc.co.uk/ politics97/diana/panorama.html.

CHAPTER 2

Researching pragmatics

2.1 PRAGMATICS RESEARCH: FROM INTUITIVE TO EMPIRICAL APPROACHES While this chapter focuses on ways of collecting and analysing data in pragmatics research, we acknowledge that it does not represent the totality of research in the area of pragmatics as a whole. As discussed in Chapter 1, pragmatics has its origin in the philosophy of language and there remains an important ongoing debate on the core concepts of pragmatics; this also helps to drive and shape the frameworks that we apply within the empirical side of pragmatics research. Such intellectual endeavour is as important to pragmatics (and linguistics in general) as it is to philosophy. The non-empirical side of pragmatics research involves discussion, critique and philosophical debate, but it also draws upon intuitively derived instances of language use. Jucker (2018) reminds us that intuition was an important source of data for early philosophers of language and pragmaticists. For example, Austin and Searle relied on their intuition in their seminal work on speech acts: ‘[t]heir data consisted of their own intuition about the use of language’ (Jucker, 2018: 5). We note that the term intuitive knowledge better represents what philosophers of language bring to their theorising process. The term introspection is also sometimes used, though this is prone to confusion as it has different coinage in other fields (see Clark, 2018; Schneider, 2018). For instance, in experimental cognitive research, introspection can refer to thinkaloud protocols, verbal reports and other means of elicitation (Clark, 2018). Distinguishing between intuitive knowledge and introspection is useful in pragmatics, Jucker (2018) notes, because when we talk about theorising about language use we draw upon intuitive knowledge, whereas within elicitation practices (e.g. discourse completion tasks, roleplays), participants engage in introspection to come up with the language use they consider to be typical for a given situation. On the other hand, intuitive knowledge, within pragmatics research, refers to the knowledge a researcher brings to the task of investigating language. As we illustrated in Chapter 1, the iterative process of analysing language using corpus data constantly moves between results and intuition as the researcher follows up on hypotheses which frequency results trigger. Pragmatics offers a framework for understanding language. There are many means of arriving at a pragmatic understanding of language, ranging from the analysis of texts to philosophical debate, as discussed. Within the empirical side of pragmatics research, there are a number of methodologies in use to gather language data. In this chapter we will

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look at some of the main approaches. First of all, let us begin with a conclusion: there is no one right way to gather data in pragmatics research. Pragmatics, as a framework for the study of intended meaning in social context, has proved to be methodologically inclusive. When we consider language within pragmatics, we can do so through reflection or intuitive knowledge or we can examine language from outside by collecting and analysing it (within a range of data-collection instruments). This chapter focuses on the main options available to a researcher when gathering language data ‘from outside’ (see Figure 2.1). LANGUAGE INSIDE Language as intuive knowledge

Language as empirical data LANGUAGE OUTSIDE Figure 2.1 Language inside as intuitive knowledge and language outside as empirical data

Collecting language can take many forms. We can set up controlled tasks so as to expedite the gathering of data that is most relevant to our research question. For example, if we want to examine what speakers typically say in response to a compliment, we can design a discourse completion task or a roleplay which focuses solely on this situation. This task can ask participants to introspect on what they would typically say next (after the prompt provided). This type of task is high in terms of the control and precision which the researcher has over the data being collected but it is also high in terms of the degree of interference on the part of the researcher (Jucker, 2018). Alternatively, we could use data from a large general corpus of spoken language and find many instances where speakers give compliments, and, from these, instances of interlocutor responses could be recalled by manually sifting through examples. This type of approach gives the researcher far less control over the data elicitation process and is more challenging and more time-consuming (see Chapter 3), but this is offset by a low level of interference because the researcher did not mediate the interaction by means of a controlled task to elicit a compliment. This distinction between degree of control and degree of interference is very useful when it is plotted across different types of data. Let us consider this in terms of approaches to gathering spoken data based on a scale adapted from Jucker (2018: 23) in Figure 2.2. As we look in greater detail at some of the main methods of eliciting data in pragmatics research in this chapter, we constantly keep these dimensions of control and interference in mind.

Gathering language data The most basic way of gathering language data is by noting it down once you have heard it. This is referred to as attested data and it is not uncommon to see such examples in

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Figure 2.2 Researcher interference versus research control (adapted from Jucker, 2018: 23)

pragmatics. Attested data is language which the researcher has said, heard, written or read incidentally and then recorded (usually by noting it down). Such instances are similar to field notes that anyone interested in language may collect on a daily basis, as they observe uses of language around them. The method is used more systematically within ethnographic approaches to data gathering (see below). The word attest means to show something to be true, and when a researcher uses attested data, the reader trusts its veracity as part of our common code of research integrity. Attested data is usually used to illustrate and add to discussion on pragmatic phenomenon, especially speech acts. Rühlemann (2019: 33) offers this instance of attested data as a precise example in his discussion of politeness and indirect speech acts (see Chapter 6): (2.1) 1 2 3

((Husband opens the window before going to bed)) Wife: My hair is still wet. ((Husband closes the window)) (Author’s data) (Rühlemann, 2019: 33)

Normally, attested data is a short snippet (as in extract 2.1) and this aligns with a researcher’s ability to recall, with accuracy, only a short instance of language. Ad hoc attestation of language used in both broadcast and social media is much easier now because of audio- and text-capturing facilities, and therefore it is possible to retrieve recordings and texts of longer stretches of attested media discourse (O’Keeffe, 2012). In order to gather multiple instances of language data in a more systematic way, there are two main options beyond attestation. Each option has advantages and disadvantages in terms of degree of research control and interference, as discussed above (see Figure 2.2): 1)

Elicitation of language Tasks that elicit or ‘draw out’ language are designed to focus precisely on the language the researcher wishes to examine from a predetermined sample group of participants. Typical tasks include discourse completion tasks, roleplays and interviews, all of which are pre-designed with structured prompts (with varying degrees of control).

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2)

Recording of language Ideally, a researcher would like to use language that occurs naturally in a given context and to record it as it is happening in real time. Ethnographic methods allow for this through situational recording, noting of attested language and field notes made by the researcher who is embedded within a given context for an extended period. Language corpora also give the researcher access to large samples of spoken or written language which the researcher can search for a particular language item; researchers can also build their own corpora in a more tailored way which may also involve the researcher being present when the recordings are made.

TASK 2.1 DATA COLLECTION: APOLOGIES Imagine you are researching responses to apologies in spoken language. Reflecting on Figure 2.2, consider your options for gathering data for your study. 1)

2)

Give some specific details on an elicitation method (i.e. what type of task would you use?) and note your thoughts on the main advantages and disadvantages with this approach. Give specific details on a corpus approach to finding examples of responses to apologies (e.g. Which corpus would you use? Would you build one?). ELICITATION APPROACH

CORPUS APPROACH

Method Advantage Disadvantage

In this section we have seen that there are a number of ways of eliciting data and recording language, as Figure 2.2 illustrates. Each has strengths and weaknesses which we will consider in detail in Section 2.2, as we describe the main methodological tools. Let us first address issues of ethics, integrity and documentation management.

Ethics, integrity and documentation essential to empirical studies Before looking at methods, there are some important issues to consider relating to research ethics, integrity and data management. As is the norm, higher education institutions will have rigorous protocols in place to ensure ethical approval, research integrity, and data storage and usage. In the first instance, always seek advice from your institution on the procedures that are in place. You will normally need, at a minimum, to prepare the following types of documents for your study.

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Research briefing document This is a short document, written in plain English, explaining what your research is about. It will include information on how the data will be recorded, transcribed, stored and used. It is essential to explain to the participant how their data will be used and who will have access to it. The participant also needs to be assured that they have the right to withdraw from the research at any point. In addition, a guarantee of anonymity for participants must be provided by assuring them that their real names or references to any identifying information (e.g. name of a shop, town, school or business) will be changed or redacted during transcription. The briefing document needs to provide the name of the institution and contact details of the principal investigator or research supervisor whom the participant may contact should they wish to have further information in relation to the research.

Consent form A separate form is needed for consent from each participant. It must include the following: • •

•

•

•

The name of the project, as well as the department and institution; The purpose of the data collection (e.g. We are collecting spoken recordings from classrooms so as to better understand teacher discourse and teacher–student interactions); A clear statement of what the participant is agreeing to in terms of data. Reference can be made to any data laws that are relevant (e.g. The data will be stored and analysed in accordance with EU General Data Protection Regulations (GDPR); Your personal information will be stored securely in a database of the recordings but it will not be shared with a third party; All publications based on the recordings will be anonymised, and any identifying references to people, places or institutions will be redacted, etc.); A declaration, that is, a statement in the first person that the participant signs up to (e.g. I grant the [Researchers], University of X, the right to store record my speech or writing and to use the data from these within their research and publications; I understand that the recordings/texts will be transcribed and stored securely on a computer; I declare that I am over 18 years old; I declare that all of the information provided is full and correct; I give this consent freely); Write-on lines at the end of the consent form must include a separate line for (1) signature; (2) name (in block capitals); (3) date; (4) email address; (5) postal address.

Speaker information sheet This form will gather the demographic details about each participant. If a detail is not relevant in your study, do not ask for it. Typically, certain information is asked for: age range; gender; first and other language information; nationality and geographical origin. In corpus pragmatic or ethnographic studies especially, speaker roles and relationships will be required.

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By gathering consent forms and speaker information (metadata) and eliciting language data from participants in a research study, a researcher is taking on the responsibility of honouring a commitment to protecting (1) these data through secure storage, and (2) the identity of the participants. This needs to be a key consideration when physically storing these data in compliance with data protection laws and in line with the ethical procedures of your institution.

2.2

METHODS FOR ELICITING LANGUAGE DATA

Discourse completion tasks (DCTs) Discourse completion tasks (sometimes referred to as discourse completion tests) (DCTs) are essentially a type of language questionnaire which elicit or ‘draw out’ language, using a carefully designed prompt. The challenge for the researcher is to design the optimum task for a given research question. The researcher, therefore, seeks to design a very precise prompt to elicit what a participant thinks they would say in a certain situation.

TASK 2.2 DISCOURSE COMPLETION TASKS Below are two examples of discourse completion tasks (DCTs). 1) 2) 3)

Try completing both tasks. Consider how they differ from each other. Look at how you have responded to each task. What are the advantages and disadvantages of each based on this?

DCT 1 You are a university student. Your end-of-term assignment is one day late so far. You knock on your tutor’s door. What do you say?

DCT 2 (adapted from Tanck, 2002) You are applying for a position with a multinational company. The interview committee has requested that you have your professors send letters of recommendation directly to the company. When you call the interview committee to check the status of your application, you are told that one of the recommendation letters has not arrived. You are concerned because you asked your professor for the letter over a month ago. You stop by your professor’s office to find out what has happened.

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Professor: You:

Hi, [your name].

DCTs have been widely and successfully used in the study of speech acts (see Chapter 6) and speech events (e.g. asking the time). They are particularly favoured as a methodology in the study of second-language pragmatic competence (Blum-Kulka et al., 1989; Sasaki, 1998; Billmyer and Varghese, 2000; Ogiermann, 2018) (see Chapter 9). DCTs can be used in dialect studies where they focus on very specific structures (see Barron, 2005; Schneider and Barron, 2008a). DCTs can be written tasks (as in Task 2.2 above) or they can be presented orally (and recorded). Schneider (2018) notes that written DCTs have the advantage of allowing for the collection of samples of language from a large number of informants in a short time; for example, by administering a written DCT to a large lecture hall, or via email, social media or crowdsourcing platforms. The other advantage is that large-scale gathering of DCT data potentially offers the researcher rich metadata for comparative work (e.g. across gender, nationality, first language, age, etc.). The degree to which DCTs are controlled can vary. Consider the scenario in DCT 1 in Task 2.2. The informant has a choice, albeit rather limited, as to the speech act which they opt for. DCTs can be even more controlled when they are presented in a turn-based format. The example in DCT 2 in Task 2.2 illustrates how a scenario is set up and then a turn is provided. This is followed by ‘write-on lines’ (a blank turn) which the informant must complete, and so on. A further example is taken from Beebe and Zhang Waring (2004). Here the authors set out to investigate the pragmatic tone (Figure 2.3).

You go to a tourist bookstore where the books are kept behind a counter. You ask to see a book on display. The lady behind the counter says, ‘If you want to browse, go to a library.’ You would say:

You would feel like saying:

Figure 2.3 An example of a freer DCT (adapted from Beebe and Zhang Waring, 2004: 245)

An additional attraction of DCTs is their ‘discreteness’. The researcher has a lot of control over the language they want to elicit. The focus can be limited to a very specific context of use, as the examples of the above tasks illustrate. Boxer and Cohen (2004) note that DCTs are used particularly when:

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•

• •

Gathering examples of rarely occurring speech acts, speech events or listener responses (see Kasper and Dahl, 1991; Kasper and Rose, 1999; Schauer and Adolphs, 2006); Researching speech acts that readily occur but which are difficult to capture on recorded data (e.g. requests or complaints); Looking at speech acts comparatively and it may be difficult to find corresponding acts that readily occur in data from two languages.

As Schauer and Adolphs (2006: 120) put it, ‘the aim of discourse completion task research is to investigate a linguistic act within highly predefined parameters.’ The level of control in DCTs has come in for criticism over the years (see Beebe and Cummings, 1996; Schauer and Adolphs, 2006; Schneider, 2018). It is argued by some that DCTs cannot be used to appraise pragmatic competence in the study of foreign-language users because apart from providing too little context they cannot constrain discourse options without contaminating the response, for example, where the language of the task leads the informants to produce certain language (Yoon and Kellogg, 2002). In an effort to redress this, Yoon and Kellogg (2002) used a cartoon DCT so as to provide a pictorial context to constrain the response while allowing freedom to elaborate language. Not surprisingly, the criticism that DCT data lacks interactional and prosodic features (in the case of written DCTs) is frequently reported (see Ogiermann, 2018). Cultural considerations are also at play. Rose (1994) conducted a study of requests in Japanese and American English using both DCTs and questionnaires (see more on questionnaires below) and concluded that DCTs may not be culturally appropriate for Japan. Another fundamental criticism levelled at DCTs is that the language they elicit is ‘unnatural’ when compared to naturally occurring data. Quite a number of interesting studies have resulted from the quest to test whether this is the case (e.g. Hartford and Bardovi-Harlig, 1992; Beebe and Cummings, 1996; Bou Franch and Lorenzo-Dus, 2008; Maíz-Arévalo, 2015). Ogiermann (2018) offers a succinct overview of these studies and notes that, overall, they confirm that DCTs and naturally occurring data contain ‘similar semantic formulae’ (Ogiermann, 2018: 243). As we discuss in greater detail in Chapter 3, Schauer and Adolphs (2006), in a study of expressions of gratitude in DCT data compared with corpus data, illustrate that because DCT data is normally based around single utterances, the overall reality of a speech act is distorted because the typical extended turn negotiation and development is lacking. Some studies found the use of predictable formulaic language (Maíz-Arévalo, 2015; Ogiermann, 2018) while others reported that DCTs produce more direct (less polite) instances. However, Economidou-Kogetsidis’ (2013) study, which used real requests for information made to an airline reservation centre as the basis for a DCT scenario which were then administered to 86 people, concluded that DCT and naturally occurring data were similar in terms of both degree of directness and lexical modification across turns (see also Beebe and Cummings, 1996; Golato, 2003; Ogiermann, 2018). Speech acts related to conflict and disagreement are particularly elusive (essentially because informants are reluctant to be recorded in such situations) and DCTs have been used as a means of gathering these and many contrastive speech act studies have resulted. For instance, Liang and Han (2005) looked at disagreement strategies between American English and Mandarin Chinese. They based their study on five scenarios for

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disagreement within a college context. The scenarios vary in the power relationships, ranging from higher to lower status, including peer–peer interactions. Three of the scenarios are shown in Figure 2.4.

The English version of the discourse completion test Thank you very much for your time and help. Five scenarios are described below in which you are expected to disagree with the speaker on different occasions. How would you respond? Please write out what you are to SAY in real-life scenarios. Your Age:__ Gender: __Hometown: __ 1.

Your supervisor questions the originality of the term paper you submit. S/he says to you, ‘I’m sorry, but I don’t think these ideas are yours.’ However, they are yours. In response, you will say: ‘ ................’

2.

Your friend makes the following comment on your thesis: ‘I think you should supply more data to support your arguments. You know, your conclusion is a little bit weak.’ However, you think that there has been enough evidence and the problem is how to give a better explanation of the data. In response, you will say: ‘ ................’

3.

In a seminar class on the effect of modern technology, one of your classmates says, ‘The so-called modern technology is endangering the environment. It causes too much pollution.’ However, you believe such problems are only temporary and can be solved gradually. In response, you will say: ‘ ................’

Figure 2.4 Scenarios from DCT presented to American and Mandarin students (in Liang and Han, 2005)

Among other findings, Liang and Han (2005) tell us that Chinese students employ more politeness strategies when disagreeing with higher status interactants. Both the Chinese and the American students showed fewer politeness strategies when disagreeing with peers. As Ogiermann (2018: 247) concludes, DCTs have their value and their limitations, and as long as we are aware of what they can and cannot provide and of what other alternative methods we can use in their place, then ‘the DCT has its place in pragmatic research’.

Multiple-choice task (MCT) questionnaires DCTs can be designed as multiple-choice task (MCT) questionnaires that include scaled response tasks where participants assess situational contexts and speech acts according to certain variables. Respondents are not required to produce language. They are not put in

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the position of having to comprehend utterances in real time. However, Kasper and Roever (2005) point out that they do impose a certain cognitive load upon respondents. Essentially, they demand recognition while scaled response rating means respondents have to perform judgement tasks. Using MCT questionnaires has the advantage of being quick to administer and analyse compared to other elicitation methods. However, they have to be carefully designed to suit the individual research context. The design of multiple-choice questionnaires is particularly demanding (see Kasper and Roever, 2005). All of the response options must be plausible (unlike multiple-choice options in an assessment context where only one response is plausible and all others are implausible distractors). For advice on response design, see Schneider (2018).

TASK 2.3 MULTIPLE-CHOICE QUESTIONNAIRES 1) 2)

Think of an insult or other face-threatening situation and design a multiple-choice task questionnaire using the template below. Use a spoken corpus to search for each of the responses you have come up with. If the corpus data offers you more enhanced wording of your responses, revise them accordingly.

Your friend says, ‘……………………………………………………………………………………………’ Which of the following represents what you would say or do? A) ……………………………………………………………………………………… B) ……………………………………………………………………………………… C) ……………………………………………………………………………………… D) ……………………………………………………………………………………… E) ………………………………………………………………………………………

Schneider (2018) notes that from his direct experience, Asian students find DCTs very challenging because they struggle to come up with what to write and they find MCTs much more accessible as a task. By way of caveat, Kasper (2000) and Kasper and Roever (2005) note that multiple-choice questionnaires in pragmatics research have varying degrees of success depending on their purpose. Multiple-choice studies which probe situational routines and implicatures were found to have a satisfactory degree of consistency (see Kasper, 2008), while those studies which look at speech act realisation strategies ‘tend to achieve notoriously poor reliability scores’ (Kasper and Roever, 2005: 328).

Roleplays Roleplays are particularly common as a means of eliciting oral data in the study of cross-cultural and inter-language pragmatics, especially when comparing native (NS) and non-native speaker (NNS) language use in relation to the same task (NS – NS versus NNS – NNS) or

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within the same task (NSs – NNSs) (see Félix-Brasdefer (2018) and Schneider (2018) for detailed coverage). A roleplay usually involves a prompt which is given to speakers. These vary in terms of control. The participants can also be given contextual information, including a description of the situation and details about the status of each role (e.g. you are the employee/employer; student/teacher; friend/friend, etc.). Figure 2.5 is a typical roleplay prompt, based on Félix-Brasdefer (2018: 310). In this case, it is being used to elicit examples of refusals to invitations but does not provide much contextual or situational detail. There are many variations and variables in terms of enhancing the prompt and controlling the task (see Félix-Brasdefer, 2018). This will be discussed further below (see Task 2.4). The language generated in the roleplay can then be recorded and analysed.

A friend of yours is leaving to return to China after an academic year abroad. He has invited you to his farewell party. Unfortunately, you can’t make it. Figure 2.5 A roleplay prompt

The term roleplay can sometimes be used as a superordinate for a number of variations (see Table 2.1). Roleplay and role enactment involve taking on social roles (varying in how related or familiar they are to the participants), while simulated tasks assign discourse roles to participants who respond as themselves in these discourse roles. Table 2.1 Terminological differences relating to roleplays (based on McDonough, 1986; Félix-Brasdefer, 2018) Term

For the participant, this means

Roleplay

Taking on a role that is not yourself and responding to the situation that is prompted in that role (rather than as yourself). For example, you are a doctor; you are a professor; you are a train driver. Taking on a role designed to fit with your known experience and responding to a familiar situation within that role. For example, [someone who is a postgraduate student]: you are a postgraduate student and your assignment is late; [someone who is a waiter]: you are a waiter and you are late for work. Taking on a discourse role and responding as yourself to a situation. For example, (role: direction giver) you are stopped by someone looking for directions on the university campus. What would you say?

Role enactment

Simulation

Boxer and Cohen (2004: 17) point out that in certain contexts roleplay data are similar to spontaneous spoken data, ‘with the caveat that the researcher is able to set up a context for studying speaking’. Demeter (2007) sees roleplay as a method which brings the researcher closest to authentic data in the study of the production of speech acts. This is supported by Rosendale (1989), who used roleplays to elicit data for a study on the speech act of invitation. Based at a Romanian university, Demeter (2007) used roleplay as a means of data gathering for a study of apologies. One of the explicit aims of his study was to demonstrate that the use of roleplays is a valid and effective method of collecting data for the analysis of apologies. To support this, he compared data collected through roleplays with

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data collected via a DCT. His study involved 19 university students majoring in English. They were asked to roleplay an apology in six situations adapted from the US television show Friends which ran from 1994 to 2004. Some of these situations included the following: You did not have time to change before going to the wedding of your best friend, and therefore you are wearing sports clothes; You had promised your spouse that you would stop smoking. However, you started again, and your wife can tell that you were smoking again; You arrive late to your friend’s birthday dinner; You took your friend’s blue jeans without telling him or her. Now your friend has found out and you admit to taking them.

• • • •

Roleplays have also come in for criticism for being artificial, but Félix-Brasdefer (2018) notes that they are a powerful tool for the investigation of interactional aspects of communication (such as turn organisation, turn taking and overlap, etc.), as well as prosodic features and cues (such as intonations, tone and stress). In addition, they can allow for the exploration of macro-social dimensions (such as gender, age, ethnicity and socioeconomic status), within and across languages (see Márquez Reiter, 2000; Félix-Brasdefer, 2009; Cohen, 2012). Félix-Brasdefer (2018) offers extensive detail on roleplays as a methodological tool in pragmatics. Based on Félix-Brasdefer (2018), we summarise some the main broad types of roleplays: Closed roleplays: These are essentially oral discourse completion tasks and seek to elicit one-turn responses. The oral response to the prompt is recorded. Compared to written DCTs, these are argued to produce longer responses, as well as features, verbal and non-verbal, associated with spoken discourse, such as hesitation, backchannels, gestures, etc. that a written DCT will not capture (see Félix-Brasdefer (2018: 308) for examples). Open roleplays: An open roleplay is typified by being dyadic. Participants normally read the situational prompt and are then asked to roleplay how they would respond. The interaction is recorded for later analysis. The degree of detail provided in the prompt (degree of formality of setting, relationship and status of interlocutors) can have an impact on the quality and length of the data it produces (see Billmyer and Varghese, 2000; Félix-Brasdefer, 2010). A good approach is to pilot your prompt and then enhance it based on the pilot. Task 2.4 explores the piloting process based on Figure 2.5.

TASK 2.4 ROLEPLAYS 1) 2) 3) 4)

Pilot the following prompt by administering it to four different people. Note your observations on the language they use. Note any questions or confusion they have. Then, enhance the prompt based on this information. For example, what additional role or contextual information would you add?

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A friend of yours is leaving to return to China after an academic year abroad. He has invited you to his farewell party. Unfortunately, you can’t make it. What do you say?

Félix-Brasdefer (2018: 325ff.) offers extensive methodological and ethical advice which is essential reading if you would like to use this instrument.

Interviews Interviews have proved useful in pragmatics research. These interviews are sometimes sourced from other fields, such as sociolinguistics, and repurposed for pragmatics research goals (see Kasper, 2008; Schneider, 2007, 2018). For example, Schneider (2007) compared responses to thanks in closing sequences of interviews. The interviews were originally conducted in relation to attitudes to regional dialects in England. Others have used interviews to elicit first-order conceptualisations of politeness, rudeness or speech acts. For example, interviewees could be asked directly for their definitions of small talk, banter and gossip, or to share their understanding of insults, threats, and so on (see Schneider, 2018). Interviews have also been used in pragmatics research to elicit interviewee examples of particular speech acts. For example, an interviewee could be asked to detail the last time they received a compliment or an insult. This information can be used as the basis for designing DCTs, MCTs or roleplays, as we explore in Task 2.5.

TASK 2.5 INTERVIEWS Ask someone about the last time they experienced one of the following and use the details as the basis for a DCT or roleplay prompt: • • • • • • •

received a compliment made an apology refused an invitation congratulated someone made a complaint insulted someone apologised for a mistake they had made at work

Barron (2003) and Woodfield (2012) offer interesting examples of how interviews can be used in conjunction with a roleplay or DCT task to gain more follow-up insight into why informants said something within a task. For example, informants may be asked, ‘What was going through your mind when you said this?; What made you

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decide to say this at this point?’, etc. The additional data from the interviews thus allows the researcher to gain another angle of insight into the language which was originally elicited in the task. Interviews can be structured around specific question prompts, or semi-structured where they are based around a broad prompt or goal on the part of the researcher. Structured interviews use a set list of question prompts across all interviews, and this facilitates consistency and rigour in terms of analysis (because all informants are asked the same questions). Researchers in semi-structured interviews are more flexible. They set out with a list of questions to ask (essentially a checklist of topics or prompts) but there is scope for the interviewer to adapt to the interviewee’s responses by exploring themes that arise in the responses (Adato, 2008; Marra and Lazzaro-Salazar, 2018). Interviews can be conducted in one-to-one formats or in groups depending on whether the researcher wishes to gain individual insights or macro-perceptions. For instance, if we want to gain insight into the general perception of conflict on telephone calls to a helpline, we could set up a group interview in a semi-structured format, using some sample calls as prompts for discussion. A researcher seeking more micro-information about how conflict is perceived or dealt with by individuals would opt for one-to-one interviews and then aggregate the responses from a number of informants. The recordings of the interview are usually transcribed and used for analysis through qualitative analysis. Especially when working with semi-structured interviews, researchers can avail themselves of software that facilitates thematic tagging. For example, NVivo software is commonly used for this purpose. The researcher reads the transcript and adds any codes that are relevant to their analysis as they arise in the informants’ speech. If we were interested in what informants say about softening what they say (hedging), for instance, this can be highlighted and coded with the software using a thematic code (e.g. hedging). When the researcher wishes to look at all of the occurrences of hedging in the interview data, these can be recalled instantly using the software. Thematic codes work as labels and can save the researcher a lot of time.

2.3

METHODS FOR RECORDING LANGUAGE DATA

Ethnographic approaches Here we look at recording language as it happens in context and then transcribing it for analysis. We focus mainly on corpus pragmatic methods, but, first, we examine ethnographic methods. Although we discuss them separately here, there is potentially an overlap between these two approaches in that an ethnographic study, where the researcher is recording data and taking field notes, may also use corpus linguistic tools to help retrieve language items within a transcript (see Chapter 1). To gain ethnographic insight into language use, a researcher can call upon a number of approaches. The most common of these is to observe a group as its members interact, aided by observation notes and field notes. Such notes can also aid in the interpretation of recorded data at a later stage. For example, Lazzaro-Salazar (2013) recorded interactions in a hospital workspace. Keeping field notes of the layout of the room and where

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participants and objects (e.g. desks, whiteboard, lab devices) were positioned in a diagram aided her in the interpretation of her recordings later (see also, Marra and Lazzaro-Salazar, 2018). Within ethnographic research, the researcher can be a participant observer. This brings its own challenges in terms of observer’s paradox, a term coined by Labov (1972) to refer to the contradiction inherent in linguistics research that seeks to observe talk systematically in terms of what it is like when it is not being observed and yet the only way of doing this is through observation. As a participant observer, the researcher usually becomes part of a group for an extended period and keeps field notes based on experiences, routines and practices. For example, Plester (2015) explored humour in the workplace and this involved spending time working within a number of organisations for several months. During this period, she experienced a movement from being an outsider to an insider who understood in-group humour. Grainger et al. (2015) offer an interesting case study of a combined approach to gathering data which is largely ethnography. Their aim was to look at how hospitality was managed in Arabic and in English. Their data comprise four interactions, two in Arabic and two in English. The data from the Arabic interactions are recorded while the English data are observed by a researcher participant who noted down the interaction soon after it occurred. This is called an oral report (Gumperz, 1982) of a conversation and its merit is that it allows for the capturing of data that would otherwise be difficult to obtain (Grainger et al., 2015). The researchers narrowed their focus to offer-refusal sequences and were able to make observations about how these were managed differently across the two languages, in the context of offering hospitality. The Arabic pattern involved much reoffering and refusal (of food and beverages), whereas the English data involved little reoffering after a refusal of the first offer. Observations were made, for example, that an offer of another beverage by a British host can be a signal that it is time to leave someone’s house. Methodologically, this study shows the value of a mixed approach to gathering speech act data.

Corpus data As discussed in Chapter 1, many large-scale corpora are freely available through online interfaces and these have been used for corpus pragmatic research (see Chapter 3). Here, we consider the building of small ‘home-made’ corpora, as these can be very valuable for pragmatics research because the researcher has access to, and understanding of, all of the contextual details and, because of its manageable size, it can be scrutinised qualitatively and quantitatively. Small corpora can also function as case studies which can give indicative results that can be scaled up into larger studies. For example, a researcher who wanted to look at the use of pragmatic markers within a defined context (e.g. using a small corpus of one television soap opera within one variety of a language) could then scale up to a large-scale corpus of soap operas for comparison. Here, we focus on spoken corpora. Written corpora also have merit in corpus pragmatics and many of the points raised here are also relevant to their construction. As they do not require transcription, they are quicker and usually cheaper to build (for more on building written corpora see Nelson, 2010; Andersen, 2018).

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How to build a spoken corpus Like any research instrument, a corpus must begin with careful consideration of its design as well as ethical considerations (discussed above). Then, as we will discuss below, certain decisions need to be in regard to the type of transcription to use and whether to annotate the data for the pragmatic phenomena of interest.

Step 1: Design matrix Begin with the ideal design for collecting data. In other words, create a sampling framework to meet the needs of the research question, noting the variables such as gender, age, speaker relationship, role and/or identity that are important to the study and decide how much data is needed (and can plausibly be collected) across these variables. It is important to be practical in the corpus design. It must both answer the research question yet be on a scale that will not cost an inordinate amount of time or money (for example, the option to outsource transcription comes with additional costs). On average, one hour of talk will normally generate between 12,000 and 15,000 words (there is a lot of variation depending on the type of talk (e.g. a recording of two people chatting while undertaking a collaborative task will comprise far fewer words than a lecture)). Another consideration at the design phase is the time it will take to transcribe the data. It takes 10 to 20 hours to transcribe one hour of talk (depending on the level of detail of your transcription; see below).

TASK 2.6 DESIGNING A SPOKEN CORPUS Consider the following research scenario: You want to build a corpus to address your research question. You have a timeline of seven months for the project. All of the work will be done by you. First, consider the research question below and then review the design matrix for the collection of your data in Table 2.2. Research question: Do pragmatic markers differ across age and gender in Canadian English? 1)

2)

Do you think the design matrix adequately meets the needs of the research question? Is there going to be enough data to explore the research question properly? How might you tweak the research question and/or the design matrix so as to ensure that the data will be suitable and to the right scale to answer the research question and to ensure that the project will be completed within the timescale?

RESEARCHING PRAGMATICS Table 2.2 Corpus design matrix for the study of pragmatic markers Variable

Age range 1

Age range 2

Age range 3

20–25

30–35

40–45

Gender (number)

Four participants (two male, two female)

Four participants (two male, two female)

Four participants (two male, two female)

Conversation format

Two dyads:

Two dyads:

Two dyads:

Female–female Male–male

Female–female Male–male

Female–female Male–male

Setting(s) of recordings

Chatting in the home of Chatting in the home of Chatting in the home of one of the participants one of the participants one of the participants

Relationship Minimum/ maximum length of each recording Estimated number 12,000+ words of words Language variety Recording type

Friends chatting 30 minutes per dyad (3 hours in total) 12,000+ words

12,000+ words

Canadian English Audio recordings only.

The term representativeness is key in corpus design (see Biber, 1993; Hunston, 2002; Reppen, 2010). Essentially it refers to whether the corpus of data represents what it claims to represent in a balanced and considered way. Any chance collection of data will not make a valid corpus. The design matrix shown in Table 2.2 is designed to look at a single phenomenon, pragmatic markers, across age and gender. A small dataset such as this cannot claim to be representative enough to make generalisations about language use. However, a carefully designed small corpus has an important place in pragmatics research, as it offers a case study and the results may spawn a much bigger study, perhaps using a very large corpus of data. The results will also offer insights into trends in the use of forms across age and (perhaps) gender within the variety of English of the data. Results from a very small sample may lead to contradictions when tested on a larger scale. As we will discuss in Chapter 3, small-scale micro-analyses such as this can be beneficial in informing larger scale research and so they are always worthwhile if the design matrix is carefully considered, its limitations are understood and the researcher is able to carefully control the variables in the design matrix (see also Vaughan and Clancy, 2013).

Step 2: Transcription of spoken data When transcribing data there are a number of decisions to make, and these will be guided by the research aims. A broad transcription is the quickest option (see Figure 2.6). This may suit many research studies because the broad transcription can then be read through and instances of a particular item being studied can be marked or annotated with a code. This code can then be used by the corpus software to find all instances and analysis can

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then take place across variables. We will return to annotation below. A broad transcription is exemplified in Figure 2.6.











Okay? So if ye just take three minutes or four minutes and talk to the people around you there and come up with a few things that make us different. three minutes of group work . Okay. Did you come up with things? Finished talking? Yeah? Okay so. What you come up with? Religion. Do you have to have an ethnic do you have to does religion? No it’s not necessary but+ Okay so. So we’ll just put religion over here one second. We can keep it on the final list. Okay. Another one? . I think that for ethnic difference have a a set of customs and symbols and a well-defined location and has to be considerably different from another ethnic group as well. So that’s it. Right. What what did you say? You said? Culture and you said a set of customs. Yeah that’s sort of the same difference. Okay? So and you said? Language. Okay well we’ll start with these. So a set of customs and traditions. Now I’ll leave it up to you to argue the point. Is religion a separate point from customs and traditions? What do you think? Yes and no. No. Religion is a is of amm like customs and rituals and kind of practice that has to do with being kind of a higher power. Amm and so that would really be amm traditional and .

Figure 2.6 Example of broad transcription (and extract from a political science lecture from the LIBEL corpus)

Notice the use of angle brackets: < >. These can be used as a single item to mark a speaker, for example, or extra-linguistic information such as , . Corpus software can ignore anything within these brackets when conducting, for example, frequency counts. Alternatively, software can be instructed to find all instances of a certain tag. These are called XML tags that you can use to mark up a transcript into useful segments in pragmatics research, as we will discuss further below. The opens the marking and the closes it. Other codes are often used to mark truncated words (e.g. the equal sign, Fo= or the plus sign to mark where a turn is interrupted and (sometimes) resumed). In this book, we generally use broad transcriptions in our featured extracts. Table 2.3 shows the basic codes often included in broad transcription and these will serve as a guide for this book.

RESEARCHING PRAGMATICS Table 2.3 Typical codes used in a broad transcription of spoken corpora Example of code

What it means

Speakers: every time there is a new speaker, a number is given to it in order of ‘appearance’. The first person to speak in a recording is , the second , and so on. Background noises and extra-linguistic information: it is useful to note background noises and extra-linguistic information, such as ‘dog barks’, ‘door opens’ or ‘sound of cash register’ in the transcript, as these may have relevance to the interaction. Speaker interruptions: when a speaker is interrupted, + marks where their utterance ends. If they resume what they were saying, this can also be marked with +. Incomplete word: incomplete words can be marked with =. Unintelligible word(s): when you cannot make out what has been said, can be used. If you can figure out the number of syllables then this can be noted; for example, a two-syllable unintelligible word could be transcribed as .

….

+

=

On the other hand, a narrow transcription goes into great detail. For example, it might mark prosodic features, as in the example from the Hong Kong Corpus of Spoken English in Figure 2.7. Narrow transcription goes into great depth to capture as many aspects of the spoken language as possible; it offers rich detail to the researcher but is very time-consuming.

A:

{ = do you [ STILL ] have the BOARding < PASS > }

B:

{ ? < ER > } { ? < ER > } { ? < LET > me } { \ [ LET ] me < SEE > } { \ the [ ^ BOARding ] < PASS > } { \ no i am < NOT > } (.) { ? i am not < TAking > }

A:

{ \ oh you < MEAN > } { \/ the [ CHECK ] in STAFF collect the boarding CARD < alREAdy > }

B:

{ \ < YEAH > } * { \ < _ YEAH > }

Figure 2.7 Example of narrow transcription from the Hong Kong Corpus of Spoken English (HKCSE) (Cheng and Warren, 2007)

Transcription codes from Cheng and Warren (2007): • • •

Tone group boundaries are marked with ‘{ }’ brackets; The referring and proclaiming tones are shown using combinations of forward and back slashes: rise ‘/’, fall-rise ‘\/’, fall ‘\’, and rise-fall ‘/\’; Level tones are marked ‘=’ and unclassifiable tones ‘?’;

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Prominence is shown by means of UPPER-CASE letters; Key is marked with ‘[ ]’ brackets, high key and low key are indicated with ‘^’ and ‘_’ respectively, while mid key is not marked (i.e. it is the default); Termination is marked with ‘< >’ brackets with high, mid and low termination using the same forms of notation as for key choices; Points in the discourse where simultaneous talk occurs are marked with a single * in the utterance of the current speaker, and ** in the utterance of the ‘interrupter’.

• • • •

Conversation analysis (CA) has led the way in terms of offering a refined transcription system for spoken language. Rühlemann (2019) offers a useful transcription model based largely around CA. Below is an extract from the freely available BNCweb corpus which comes with sound files (see Appendix). Rühlemann first checks the extracts for accuracy and re-transcribes them using the more detailed CA-based conventions. Task 2.7 is based on a transcript from the BNCWeb presented in Rühlemann (2019: 94).

TASK 2.7 TRANSCRIPTION AND THE BNCWEB CORPUS 1)

Set up a BNCweb user account and use the ‘browse a text’ function to find file number KCT line 7746 (see how this is entered in Figure 2.8).

Figure 2.8 Web interface for BNCweb: Browse a file function (search for file KCT line 7746)

2)

Once the file transcript pops up, listen to the recording of the actual extract (focus in particular on the lines 7746 to 7751). Then compare the broad transcription (Figure 2.9) with the narrower version offered by Rühlemann (2019: 94), based on conversation analysis, in Figure 2.10.

Figure 2.9 Transcript of file KCT 7752 in BNCweb, marked up for , segments and overlapping talk

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3)

Note the advantages and disadvantages of the approaches to transcription in Figures 2.9 and 2.10.

[ ] overlapping speech; ( ) unclear; (.) or (number) short pauses; ° ° soft voice; bold loud voice; ↑ sharp rise in pitch; capital letter – heavily stressed sound, - truncated word Figure 2.10 Detailed transcription provided by Rühlemann (2019: 94)1

When one listens to the recording of this extract one can hear the visceral nature of the interaction, especially when the speakers use the word hate. The broad transcription fails to capture this entirely, whereas the CA-based re-transcription administered by Rühlemann (2019) adds so much more for the analyst. However, we stress that the researcher must make a decision on transcription conventions in a way that is efficient for the needs of a given project’s timescale and budget. So far we have looked at the transcription of only the audio mode of conversation. Although it has long been recognised that conversational interaction is multimodal (Crystal, 1969; Kendon, 1986; Arndt and Janney, 1987), the challenge of transcribing more than the audio component has not yet been fully addressed. The multimodal nature of conversation means that simultaneously, from moment-to-moment, as we speak, we are gesturing, we are gazing in a particular alignment, we are moving our heads, we are changing our facial expressions and our posture, to name but some of the micro-components of the overall ‘bundle’ (Crystal, 1969: 90). Capturing the real-time alignment of the vocal and kinesic modalities is something from which corpus linguists have largely shied away. Work within CL that addresses the challenges of multimodality is ongoing (Knight et al., 2009; Thompson, 2010; Lücking et al., 2013; Diemer et al., 2016; Kok, 2017; Rühlemann, 2019). Much of the work focuses on technical prototyping, for example, establishing the optimum means of aligning video images with the transcription (using timestamps) or designing models for measuring and capturing head nods and gestures (Knight et al., 2009). Rühlemann (2019) offers an interesting pilot study based on the Storytelling Interaction Corpus (SITCO). Looking at one 29.5-minute recording as a case study where three young adults, Sandra, Rico and Lio, are interacting, the data is first transcribed with the aid of the freeware ELAN (Wittenburg et al., 2006). ELAN is a tool

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which facilitates multimodal transcription in a tiered manner. For example, Figure 2.11 shows an illustration from the How-to Guide for ELAN2 where the visual image is aligned to the segment of video, the audio sound stream, plus its transcription and gestures (among other items) can be added onto these segments as another tier. All this information is aligned and ultimately retrievable. Rühlemann’s (2019) pilot case study from the SITCO data offers a detailed insight into the transcription and annotation process. Ultimately, by analysing the pace (duration), direction and alignment of one of the participant’s gazes to her interlocutors as she tells a story, Rühlemann noted that the pace at which she changes gaze direction from one addressee to the other becomes faster ‘from the beginning of the story through to its high point’ (Rühlemann, 2019: 186). He finds a correlation between the rate of change in gaze direction and the development of the narrative from background narrative details to its climax and proposes this as hypotheses that could be tested on a larger dataset. Forthcoming work on the SITCO corpus (which will be made freely available) will examine this and many other hypotheses in relation to storytelling (Rühlemann, forthcoming).

Pragmatic annotation As mentioned above, angle brackets can prove very useful in transcription because we can add extra information, such as background noise or ,

Figure 2.11 Sample interface from ELAN where image, sound and multimodal transcript are aligned in tiers (ELAN How-to Guide, 2017: 15)

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or we can make features more integral to the discourse, such as , pauses and their length, and so on. Angle brackets can also be used to mark up or annotate segments of a transcript where the researcher wishes to note pragmatic phenomena. The < > symbols can wrap a segment of an interaction within a code and, as Archer and Culpeper (2018: 497) aptly explain, these are ‘stitch-on’ and ‘stitch-off’ tags; for example, if one wanted to mark all instances of directive speech acts, one could put at where it begins and where it ends (see Task 2.8).

TASK 2.8 PRAGMATIC ANNOTATION Consider the extract in Figure 2.12, from a recording of a cookery instruction, led by a chef trainer as part of a degree programme in hotel management, taken from the Cambridge Limerick and Shannon Corpus (CLAS), a one-million spoken word corpus collected in the context of a university-level hotel management degree programme.3 1) 2)

How might you annotate the use of directives with angle bracket tags? Are there any other pragmatic items that you might like to annotate? If so, what tag would you use?

Now guys, it’s not Jess’s responsibility to make yer sauce. Ye should be doing it, so Jess, you go back over and look after your bench. That’s how these boys are going to learn by making mistakes. Now you can grate some cheese, a small bit of no don’t use that, this cheese here is the wrong one, okay. You see this here?

Yeah. Cloves can be put in a small bowl and left inside in your fridge, the water thrown away and the skins into the bin, okay. You need to clean as you go along, guys, and keep it tidy, it’s how you work. So fifty grams of cheese grated using the small side of the grater. Keep that knife down by your side when you’re walking with it. Figure 2.12 Data extract from a cookery instruction session from CLAS4

Once you have transcribed your data and possibly annotated it for the pragmatic feature that you are interested in, you can then use corpus software to analyse it. The basic functions of corpus software have been covered in detail in Chapter 1 and we will return to ways of analysing pragmatic items in a corpus in Chapter 3. At the time of writing there are various software applications available, some free and some subject to a licence fee. These include freeware AntConc (Anthony, 2019) and #LancsBox (Brezina et al., 2015), and Sketch Engine (Kilgarriff et al., 2004) and Wordsmith (Scott, 2017), which are normally subject to a licence fee.

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By way of an example of the usefulness of annotating data for pragmatic items, let us return to the extract in Figure 2.12. We have added tags for directives , vocatives and pragmatic markers and saved the file in ‘plain text’ format. Using AntConc software, we then entered a search for all directives, as Figure 2.13 illustrates. This search generates all directives in this extract, and even in this tiny dataset we can see patterns that may lead to hypotheses about how pragmatic items cluster. By clicking on the tag, we can examine the source file to access more context.

Figure 2.13 Screenshot of a search for directives marked with the tag in CLAS using AntConc software (sorted 1R)

We will return to pragmatic tagging in Chapter 3 (for more detailed coverage, see Archer and Culpeper, 2018; Weisser, 2018). The benefits of using a corpus in the study of pragmatic are many, as we hope to further illustrate in this book. However, we also acknowledge that there are challenges and that not all aspects of pragmatics lend themselves to being studied in a corpus. We will discuss this in greater detail in Chapter 3.

2.4

CONCLUSION

Research in the area of pragmatics is clearly multifaceted, and this reflects the many directions and applications of the field. In this chapter, we have covered a diverse range of approaches and methods. All these studies have in common the aim of understanding language use in context. There is no one right method in the study of pragmatics. All the

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approaches that we have covered in this chapter are viable ways of collecting empirical data for the study of pragmatics. A researcher should keep an open mind about the possibility of using more than one approach to gathering and analysing data in pragmatics research. The key guideline for any empirical study in pragmatics is that it is carefully designed and that in writing up research there should be very clear details on the methodological design and processes, as this will be insightful for the field in general.

2.5

FURTHER READING

Adolphs, S., 2008. Corpus and Context: Investigating Pragmatic Functions in Spoken Discourse. Amsterdam: John Benjamins. This book explores the relationship between corpus linguistics and pragmatics. In particular, it discusses possible frameworks for analysing units of language beyond the single word. This involves a close analysis of contextual variables in relation to lexico-grammatical and discoursal patterns that emerge from the corpus data, as well as a wider discussion of the role of context in spoken corpus research. Jucker, A.H., K.P. Schneider and W. Bublitz (eds), 2018. Methods in Pragmatics. Berlin: Mouton de Gruyter. This edited volume is an invaluable resource for research methods in the empirical study of pragmatics. It is divided across introspective, experimental, observational and corpus pragmatics research. Some of the many papers that will be of use include the following: • • • • • •

Anderson, G. (2018) Corpus construction (pp. 467–494). Félix-Brasdefer, J.C. (2018) Role plays (pp. 305–331). Jucker, A.H. (2018) Data in pragmatic research (pp. 3–36). Marra, M. and M. Lazzaro-Salazar (2018) Ethnographic methods in pragmatics (pp. 343–366). Ogiermann, E. (2018) Discourse completion tasks (pp. 229–183). Schneider, K.P. (2018) Methods and ethics of data collection (pp. 37–93).

Romero-Trillo, J. (ed.), 2008. Pragmatics and Corpus Linguistics: A Mutualistic Entente. Berlin: Mouton de Gruyter. This volume curates a range of chapters that explore pragmatics using corpus linguistics. These include areas such as cross-cultural pragmatics in service encounters; hesitation in learner discourse; and listenership in multimodal corpora. Most of all, this book seeks to bring pragmatics and corpus linguistics closer by showcasing both disciplinary synergy and methodological potential. Rühlemann, C., 2010. What can a corpus tell us about pragmatics? In A. O’Keeffe and M. McCarthy (eds), The Routledge Handbook of Corpus Linguistics (1st edn). Abingdon: Routledge, pp. 288–301 [and Rühlemann, C., forthcoming. What can a corpus tell us about pragmatics? In A. O’Keeffe and M. McCarthy (eds), The Routledge Handbook of Corpus Linguistics (2nd edn). Abingdon: Routledge]. This chapter gives good coverage of the limitations of corpus linguistics in relation to the study of pragmatics while at the same time providing a solid grounding in what a corpus

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can address in pragmatics-related research. It provides examples of how a corpus can be used to look at turn organisation, semantic prosody, discourse markers and speech act expressions. It also addresses the importance of multimodal corpora to the future of corpus pragmatics research. Rühlemann, C., 2019. Corpus Linguistics for Pragmatics. London: Routledge. This book offers a very practical introduction to how corpus linguistics can be used in the study of core areas of pragmatics, including speech acts, deixis, pragmatic markers, evaluation and conversational structure. In addition, the book showcases the building, annotation and use of the SITCO, a pilot multimodal corpus. In this book, an adaptation of conversation analysis transcription is applied to enhance the existing transcription of the BNCweb. This offers a useful guide for those interested in using a narrow transcription. Rühlemann’s sample extracts (of narrow transcription) can be compared with the original broad transcript, which are linked to the sound files.

NOTES 1 Rühlemann (2019: 12–13) provides a full transcription system. 2 ELAN How-to Guide, 2017. Available from https://tla.mpi.nl/wp-content/uploads/ 2017/01/How-to-pages_9.pdf. 3 See Healy and Onderdonk-Horan (2012) and Appendix. 4 Note the use of ye in the extract in Figure 2.12. This is a common form in Irish English to refer to the second-person plural.

CHAPTER 3

Corpus pragmatics

3.1

INTRODUCTION

As discussed in Chapter 1, corpus pragmatics (CP) refers to the use of corpus linguistics (CL) in the study of pragmatics. It is a relatively new concept compared to the integration of CL in other areas. Indeed, much of the potential of corpora for the study of pragmatics has not even been realised. The reason for this under-performance is largely due to the fact that CL treats language data in a bottom-up inductive manner, beginning with form rather than with function (unless a corpus have been pragmatically annotated) (Rühlemann and Aijmer, 2015; Aijmer, 2018; O’Keeffe, 2018). For example, a researcher wishing to look at language items that mark vagueness in a corpus will begin by making a list of the forms (words and phrases) that are associated with this function. They cannot normally begin with the function and look up ‘vague language’ to retrieve all instances in the corpus (unless the data has been systematically annotated for vague language). The norm, therefore, for CL is to begin by looking at form frequency results and then to map these to functions, as exemplified in Chapter 1. This approach continues to serve CP well and a range of pragmatic phenomena have come under its research gaze, as we refer to throughout this book, such as response tokens, pragmatic markers, vocatives, and so on. Bednarek’s (2008) work explores language and emotion. Clancy and McCarthy (2015) find ways to systematically investigate turn co-construction in conversation and Clancy (2018) examines conflict episodes in family discourse. These are but a few of the many examples of fruitful CP studies that work from form-to-function. However, this approach poses more challenges when examining speech acts in a corpus. As Aijmer (2018) notes, it falls down in terms of its ability to recall all instances of a particular function. Given that the study of how language functions is at the core of empirical work in pragmatics, there is a need to think carefully about how CP can accommodate both a form-to-function and a function-to-form approach to language corpora. The aim of this chapter is to set out protocols for both processes (form-to-function and function-to-form) so as to enhance CP as a methodology.

TASK 3.1 CONCEPTUALISING CORPUS PRAGMATICS Corpus pragmatics brings together the fields of corpus linguistics and pragmatics. In the context of this statement, consider the following:

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1) 2) 3)

List the key methodologies that come to mind in relation to (a) corpus linguistics and (b) pragmatics. Looking at this list, discuss how you think there might be links or synergies between these methodologies (i.e. can any of these be used in combination?). Discuss whether any methodologies on your list are challenging to use in a combined way.

As discussed above, pragmatics research has traditionally (and successfully) worked in the opposite direction to CL, from function-to-form. It begins with a research question about a pragmatic function and seeks to find the typical forms (or exponents) associated with it. Figure 3.1 summarises the converse methodological processes in form-to-function and function-to-form approaches in pragmatics research.

Figure 3.1 Form-to-function and function-to-form approaches in corpus pragmatics

Lurking within a corpus are so many speech acts and other pragmatic phenomena, but the challenge is to retrieve them in a systematic way. Therefore, as part of the coinage of corpus pragmatics, more consideration must be given to how best to use CL for pragmatics research. The challenge for the emerging model of CP research is to avoid assuming that form-to-function processes are the only option and to find ways of addressing the challenges to function-to-form approaches. In this chapter, we aim to address this issue of balance and how it can be achieved, even with very large corpora, especially in the study of speech acts.

3.2 KEY CONSIDERATIONS OF CORPUS PRAGMATICS RESEARCH Process and protocol in corpus pragmatics First of all, we need to acknowledge that pragmatics already has established means of collecting empirical (elicited) data through discourse completion tasks (DCTs) and roleplays,

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and so on, as discussed in detail in Chapter 2. These have served the field well, especially in the context of the study of contrastive second-language pragmatic competence (BlumKulka et al., 1989; Sasaki, 1998; Billmyer and Varghese, 2000). Bringing a CL methodology to pragmatics is not without its challenges. Building on Figure 3.1, let us consider a more contextualised example of form-to-function and function-to-form analyses within the context of a sample research question. Imagine that we want to examine invitations so as to address the research question: What are the illocutionary force indicating devices (IFIDs) used in invitations in American English? Table 3.1 illustrates how form-to-function and function-to-form approaches would take us on different prototypical routes to answer this research question. Table 3.1 Comparing form-to-function and function-to-form analyses routes to examine a research question Form-to-function

Function-to-Form

Research question

What are the illocutionary force indicating devices (IFIDs) used in invitations in American English?

Step 1

Identify a suitable corpus dataset. Generate frequency lists for single words and multi-word units.

Step 2

Step 3

Step 4

Sift through the frequencybased results to identify candidates of forms that may be operating as invitations. Analyse the forms identified in step 2 qualitatively (through concordances) and eliminate those that do not function in invitations. Note metadata, if available, about the context in which the forms are used (e.g. age, gender, discourse role, register, etc.). Generate findings based on the forms used in invitations and their variables of use in the metadata.

Informed by existing literature, design an elicitation task (a DCT or roleplay) to ascertain examples of invitations. The task will pre-define variables such as the power relationship of the interlocutors, and the other contextual variables of the interaction (genders, roles, situation, and so on). Administer the elicitation task to a test group of participants.

Analyse results to establish the forms that are used by participants in the elicitation task. Generate a list of forms.

Generate findings on the link between forms and the predefined variables of use within the task (e.g. power, role, setting etc.).

At a basic concordance level, Rühlemann and Aijmer (2015) point out that the traditional vertical reading of corpus data (typically in concordances) needs to be balanced with the more horizontal reading of the contextual details to fully understand pragmatic phenomena (see also Rühlemann and Clancy, 2018). However, this vertical and horizontal balance presupposes that one begins by searching a form and that one then works towards the contextualised analysis of its function(s) (i.e. form-to-function). What if one takes a

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starting point from the more traditional function-to-form orientation of pragmatics analysis? Can this methodological route be accommodated in corpus pragmatics? Given the importance of continuing the functional investigation of language in use, there is a need to consider how and whether this work can be done using CP. Lutzky and Kehoe (2017a: 38) problematise this in relation to the study of speech acts in large corpora. Speech acts, they note, cannot be identified automatically due to the fact that: 1) 2)

forms may be produced in a potentially infinite number of ways; forms which are prototypically associated with a specific speech act (e.g. sorry) may also be attested with other functions (e.g. a sorry state).

As a result, according to Lutzky and Kehoe (2017a: 38), corpus studies of speech acts, and related phenomena, tend to be conducted using smaller manually annotated corpora and tend to ‘resort to manual forms of analysis, or to adopt eclectic approaches, focusing for instance on specific speech act verbs’. Let us now return to a topic that has been discussed in Chapter 2 in relation to research methods, namely the issue of balancing between breadth and depth of scope. Here we examine this topic in relation to CP in comparison to traditional data elicitation approaches.

Breadth of forms versus contextual depth For good reason, as Flöck and Geluykens (2015) note, DCTs have a long tradition as the main method of investigating speech acts, as they have proved successful in eliciting responses to given situational prompts using a methodology that moves from functionto-form (see Chapter 2). By using a DCT, ambiguity of context is avoided because the functional scope of the instrument can pre-define the variables of the study and, therefore, control the context and conditions very carefully (e.g. the gender, age, social and interpersonal relationship, and so on, of the speakers, as discussed in Chapter 2). A DCT, for instance, can be streamlined to gather apologies in the context of a student apologising to a college professor for being late to class. It could say that you have never met the professor before and that this is not the first time you have been late with an assignment. This gives a contextual concentration and richness that provides a narrowed range of the forms used in this specific context, with confined conditions. Some argue that the concentration, or narrowness, of DCT data is also its weakness (see Schauer and Adolphs, 2006; Flöck and Geluykens, 2015), and that it is in stark contrast to using a corpus where a much broader range of forms in context are accessible in a much larger sample of naturally occurring data. However, despite the abundance of data in a corpus, it is often at the expense of being far removed from the context (unless the data has actually been collected by the researcher). Despite the availability of detailed metadata on each recording in a spoken corpus, for example, it may not be readily accessible on the corpus interface or it may not be fully complete. As O’Keeffe (2018) notes, what results is a trade-off between the breadth of forms that corpus data can offer a researcher and the details of the contextual conditions within which these forms occurred. In contrast, by using a DCT, one can narrowly define the context and its conditions. However, this is at the expense of the breadth and frequency of form, as Figure 3.2 illustrates. Moving forward within a model for CP, we need to acknowledge the quest to find a way of attaining the best of both approaches. This means finding a means of optimising breadth

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Figure 3.2 Corpus data versus DCT elicited data across form and context (O’Keeffe, 2018: 593)

and frequency of form while simultaneously retrieving and recording the richness of the contextual conditions within which forms were originally uttered. This is a challenging goal but there are models which we can build on, as we discuss below. In essence, we need to keep an openness towards the merits of both form-to-function and function-to-form approaches to any research question in CP. This may mean a greater workload for the researcher and it certainly means addressing how we annotate corpora so as to enhance them for pragmatic research. At this point in the chapter, we will consider both approaches separately in more detail beginning with form-to-function approaches to CP. Then we will look at the emerging body of CP work which is taking a function-to-form approach and bring together ideas to address the challenges in relation to using CP, in a balanced way, with large corpora.

3.3 FORM-TO-FUNCTION RESEARCH IN CORPUS PRAGMATICS Through its inductive process, a form-to-function approach in CP ensures that the forms can be studied with great precision with regard to frequency, distribution, position and collocation with different functions (Aijmer, 2018). However, with the abundance of naturally occurring language data in a corpus comes a downside for pragmatics research, namely functional diversity and ambiguity. In other words, while CL aligns well with the core principle of pragmatics (that meaning is not a stable counterpart of linguistic form), this is also its weakness when using a form-to-function approach. Let us consider a brief example by looking at the speech act of apology in Task 3.2. In a form-to-function approach, we could look up the direct speech act by searching for a prototypical illocutionary force indicating device (IFID) for apologising, such as sorry, in a corpus. Task 3.2 illustrates some of the complexities of this approach.

TASK 3.2 A FORM-TO-FUNCTION APPROACH TO SORRY Examine the 20 concordance lines of the word sorry in the BNC2014, using #LancsBox (see Figure 3.3). 1) 2)

How many of these instances of sorry are functioning as apologies? To what degree of certainty can you draw your conclusions in each case?

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Figure 3.3 20 concordance lines of the node word sorry in the BNC2014, using #LancsBox (unsorted)

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Task 3.2 illustrates some of the challenges we face when trying to conduct form-tofunction analysis using an IFID in the case of a speech act because we assume a direct and absolute correlation between the form and its function as an apology. An IFID can prove unreliable as a means of recalling all, and only, instances of a speech act. Similar issues arise with other pragmatic phenomena (e.g. if we look up all instances of so, you know, right and okay in a study on pragmatic markers, we will be faced with the same ambiguity), as Figure 3.4 illustrates. In order to analyse speech acts and other pragmatic phenomena in a corpus, there is a need for a systematic approach which may mean finding ‘robust workarounds’. First, let us take the four approaches to corpus-based form-to-function investigations put forward by Ädel and Reppen (2008: 2–3) (Figure 3.5) and then explore their application to a functionto-form approach in Section 3.4. As Ädel and Reppen (2008) point out, these approaches often overlap and there is iteration within any of these strategies. Nonetheless, they are useful to consider as core investigative strategies in form-to-function CP analysis.

One-to-one searching This strategy works when there is total recall from the search item. In other words, all of the hits are relevant. Nothing goes to waste! For example, if we wanted to investigate the use of noun phrases in part-of-speech (POS) tagged corpus, we can generate a full recall of all noun phrases. However, in CP research, we can only get full recall if a corpus is pragmatically tagged (see Chapter 2 and below). Even IFIDs that seem to lack ambiguity such as Thank you still need manual checking to ensure that no uses were intended sarcastically, for example.

Sampling For the purposes of CP, this would involve using IFIDs as candidates which will help with sampling. By entering search items such as I’m sorry, I apologise and Excuse me, a large sample of potential instances of the apologies can be generated. Underlying this approach is a carefully designed sampling framework. This, then, provides a principled sample to work with. For example: Search items: I’m sorry; I apologise; Excuse me Data: Corpus of Contemporary American English Sections: Spoken Sample size: 500 texts This search will generate three batches of 500 instances per search item. These concordances can be saved to an excel file and, by random elimination, can be reduced to a 100line sample per search item. These three samples will then need to be read manually to eliminate any non-apologies. This may necessitate going back into the corpus data to see expanded contexts. Other examples of sampling in CP are Curry and Chambers (2017), who used the question mark as a means of recalling questions in their study of French academic discourse,

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Figure 3.4 20 concordance lines of the node word so in the BNC2014, using #LancsBox (unsorted)

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One-to-one searching

Sampling

Siing

Frequency-based lisng Figure 3.5 The four main approaches to form-to-function analysis using CL (based on Ädel and Reppen, 2008: 2–3)

Clancy and McCarthy’s (2015) use of speaker tags (, , etc.) to search for turn-opening if and when in order to explore their involvement in co-constructed utterances, or Vaughan (2008), who used extra-linguistic information in the corpus transcripts to recall instances of humour (e.g. laughs; laughter).

Sifting If you engage in sampling, as illustrated above, you will most likely need to sift through the sample in order to isolate the forms/instances that are not relevant. Given that one cannot guarantee 100 per cent recall in form-to-function corpus pragmatics, sifting will be a core part of the process. For example, Clancy (2018) studies the pragmatic phenomenon of conflict in family discourse through a process of identifying linguistic items that were shown in the previous literature to preface conflict episodes, such as I think, I mean, well and you know. Due to the polysemous nature of many of these items, it was necessary to sift through concordance lines for each item in order to determine how frequently they were directly associated with the prefacing of family argument episodes. The sifting process facilitated the identification of the most frequently used item in the prefacing of conflict episodes in his data (the positive counterargument strategy yes/yeah but).

Frequency-based listing This is the most typical corpus-based approach where you take a bottom-up approach and begin by looking at the frequencies of forms in your corpus and work from there in terms of their patterns and meanings (see Chapter 1). Many frequency-based studies of corpus data arrive at pragmatic conclusions to explain differences in frequencies, distributions and patterns across contexts of use. Walsh et al. (2008) adopted this approach in their study of vague language in academic discourse by conducting a multi-word unit

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word list which was then functionally analysed using concordance lines so as to categorise functionally. Similarly, Rühlemann and Clancy (2018) examined the frequency of as if followed by singular personal pronouns, as if I was/were, as if she was/were and as if he was/were, in the COCA corpus and coded them for both syntagmatic (subject complement, manner adverbial, etc.) and pragmatic (degree of factuality) factors through the use of concordance lines. Finally, Vaughan et al. (2017) used frequency-based listing to explore the differences in the function and distribution of vague category markers (VCMs; see Chapter 7) in the Limerick Corpus of Irish English and the Cambridge and Nottingham Corpus of Discourse in English.

3.4

FUNCTION-TO-FORM RESEARCH USING CORPORA

If you take a function-to-form approach within corpus pragmatics, this means that the starting point is a search for a particular speech act (apology, request, complaint, etc.) or pragmatic phenomenon (e.g. pragmatic markers, vague language, etc.) rather than starting with a search that yields forms and their frequencies. Herein lie the challenges: first, how can you get a high degree of recall (results from your search) if you take this route? And second, where and how do you start? Consider this in Task 3.3.

TASK 3.3 GETTING STARTED ON FUNCTION-TO-FORM RESEARCH You want to use a spoken corpus to examine thanking. 1) 2) 3) 4)

Think of possible search items. On what basis did you select search items? How do you know these are the right search items? Try out for these items in a spoken corpus and reflect on your choices. Design an elicitation task that you could use to create a list of search items for thanking.

In this section, building a parallel to the form-to-function processes outlined by Ädel and Reppen (2008; see also Section 3.3), we explore a possible inventory of corpus-based function-to-form approaches. These are summarised in Figure 3.6, and they are based on an aggregation of existing work of those taking a function-to-form approach within corpus pragmatics.

One-to-one searching The emergence of corpus tools and annotation systems that facilitate pragmatically annotated corpora means that we are now able to conduct one-to-one pragmatic function

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One-to-one searching

Sampling, searching and siing

Using exisng research findings as ‘seeds’

Soluons for larger corpora Figure 3.6 An inventory of function-to-form approaches (adapted from O’Keeffe, 2018: 598–599)

searches to recall all of the instances of a given pragmatic function or phenomenon (see Kallen and Kirk, 2012; Archer and Culpeper, 2018; Weisser, 2015, 2018). Crucially, this type of research can only be undertaken if the corpus has been annotated for pragmatic features. Ideally, a pragmatically annotated corpus, when searched for a speech act or pragmatic feature (e.g. pragmatic markers), results in the automatic retrieval of all instances of that feature. As Weisser (2015) notes, the early work on pragmatically enriched corpora was in the area of computer science going back to the 1990s, mostly with the goal of modelling conversational agents. Within the field of linguistics, the body of pragmatically annotated corpora is growing (see Rühlemann and Aijmer, 2015; Weisser, 2015), including, inter alia: • • • • •

speech acts (Stiles, 1992; Garcia, 2007; Kallen and Kirk, 2012); pragmatic markers (Kallen and Kirk, 2012); quotatives (Kallen and Kirk, 2012; Rühlemann and O’Donnell, 2012); participation role (Rühlemann and O’Donnell, 2012); politeness (Danescu-Niculescu-Mizil et al., 2013).

There has been an openness and debate about the challenges of annotation, and this has brought many advances, as evidenced through ongoing debates about approaches to annotation schemes (see Archer and Culpeper, 2018; Weisser, 2015, 2018). The mismatch, and often ambiguity, between form and function (as in the example of sorry) means that the automatic assignment of tags will sometimes lack precision, and laborious manual checking is necessary, as noted by Rühlemann and Aijmer (2015). Of interest is the SPICE-Ireland corpus because it offers an example of a spoken corpus which has been pragmatically annotated (Kallen and Kirk, 2012; see also Chapter 6). All 15 spoken text categories in the corpus were annotated pragmatically using an annotation scheme comprising five components: the speech act status of each utterance in the corpus, based on Searle’s (1976) categories of illocutionary acts, tone movements, discourse markers, utterance tags and

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quotatives (see Kirk, 2016: 306). The annotation surrounds the span of an utterance which contains a speech act (i.e. with a code in angle brackets before the utterance, concluding with a backslash (Kirk, 2016: 302): ... for ‘representatives’; ... for ‘directives’; ... for ‘commissives’; ... for ‘expressives’; ... for ‘declaratives’. Weisser details his semi-automated process of speech act identification using the dialogue annotation and research tool (DART) (see e.g. Weisser, 2015, 2018). This tool, through carefully determined multiple syntactic structure features and mode (e.g. modals, adverbials, conditionals, etc.) and complex computational tagging, can identify speech acts in task-oriented dialogues from the Trains and Trainline corpora (see Weisser, 2015). Weisser shows that the tool was able to generate a high number of accurately labelled speech acts within this very defined context. As Weisser scales up this tool for wider application as a semi-automated system called TART (DART’s ‘big brother’), Weisser (2018: 50) calls for greater detail in terms of metadata, and he notes that finding a way of encoding participants’ relative status in a spoken interaction would be a welcome advance. Weisser’s work is very important in the context of the evolving field of corpus pragmatics, but, as Kirk and Andersen (2016: 294–295) note, there are many challenges to pragmatic annotation, not least of all the fact that when real spoken language is transcribed, it is reduced into a pragmatically bereft form. Kirk (2016: 300) notes that transcriptions record ‘the locutionary act of producing forms and constructions, but “what is heard” (i.e. the illocutionary force or intent, and its processing as the perlocutionary effect) is only extrapolable from the transcription’. These deficiencies make it even more challenging to superimpose pragmatic annotation onto existing corpora of spoken language especially (see also the work of Musgrave et al. (2014), who proposed developing strategies to integrate annotation schemes that exist for different corpora).

TASK 3.4 CONCEPTUALISING CORPUS PRAGMATICS Examine extract 3.1 taken from the Spoken BNC1994 from the beginning of a class. The teacher is recapping on the tasks the class has been set and then there is an interruption because there are some latecomers. 1) 2)

Read the extract and note any queries or confusion that arise for you in the absence of the original sound recording. Review your list (from above) and consider how these issues might affect how you interpret this extract pragmatically.

[E.g. How could lines 5, 6 and 7 be interpreted pragmatically in different ways depending on facial expression, intonation and gesture? Could they be interpreted sarcastically? Humourously? Ironically?]

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(3.1) [Context: = teacher; = student.] 1

2 3

4 5 6 7

Oh did they? I must just jump up and down on Mrs anon when I see her at lunch time. Emma, is Emma here today? Oh she’s with Mrs she? I see now we’ve got lots to do this morning, you’re going to need to ignore what’s going on behind me, ah, it’s not happening, right, as I said to you at the very beginning of September I’m the star, so you pay attention to me. That was the correct thing to do, very well though, you saw the look and you decided. On the board this morning we’re going to have a bash at thinking about some targets, we’re going to have a bash think about, how you think you’ve done so far? One of the two tasks that I’ve set you since we met in September, what are the two big tasks that we’ve concentrated on? One should be in your file already and it should be finished and the other one you’re going to give to me today. Our passport and our diary Your passports and your graphs. There the two big pieces of work that we’ve done together so far, in a minute I’m going to give you a printed sheet

We had to do, do jobs unclear so you owe me ten minutes and normally when you come into my room you say I’m sorry I’m late. I’m sorry I’m late You don’t look as if you mean it, sit down please because my lesson started ten minutes ago there’s one over there . Now in a minute I’m going to give you a printed sheet and it’s going to ask you how well you think you’re doing. Have you been able to complete the survey on belief, have you been able to get it done by a deadline. What does the word deadline mean? Let’s have hands up, what does the word deadline mean? (Spoken BNC1994: File F7R)

Key pragmatic information is usually lacking in a conventional transcription. The reader has to re-encode the illocutionary force or intent (the speech act status), the perlocutionary effect, the upholding or breaching of the Gricean cooperative principle, the politeness strategy invoked, the attitude of a speaker to the message of the utterance being made (pragmatic stance) or to the hearer of that utterance (face negotiation), and so to its potential impact. From the extract in Task 3.4 above, without the audio and sound file, we cannot appraise these factors in relation to lines 5 to 7. In other words, we cannot access the intended meaning, and, as Kirk and Andersen (2016) note, much of what speakers utter is determined by a speaker’s attitude towards what they are saying and towards the person(s) to whom they are saying it. When working with small and more contextualised recordings, often where the researcher has in-depth (and often insider) understanding of the data, etc., a number of researchers have manually coded their data pragmatically. This closeness of the researcher to the data and its context helps make the annotation more accurate but needs to be

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offset by checks by someone who is not so close to the data. Milà-Garcia (2018) looked at agreement and disagreement in spoken Catalan (among family and friends) and she manually annotated her data for this purpose. Once the data was annotated and independently checked, this facilitated total recall of all stretches of discourse which involved either an agreement or a disagreement. These could then be analysed more closely in context (see Garcia McAllister, 2015, below). In summary, one-to-one functional pragmatic searches are possible if you have a pragmatically annotated corpus, but offsetting this solution for function-to-form research are the limitations that: (1) it can be time-consuming and labour intensive; and (2) due to the inherently fuzzy and discursive nature of speech acts, decisions of interpretation are dependent on the annotator’s interpretation within the bounds of his or her understanding of the contextual conditions of the speech event and will require inter-rater validation. The ideal scenario is to arrive at the point where we have robust pragmatic annotation tools. As discussed, these developments are underway in spite of the challenges of ambiguity and accuracy.

Sampling, searching and sifting in a function-to-form approach Although it has been shown that it is possible to work through the entirety of small corpora and manually annotate them, others have found ways of making large corpora scalable for function-to-form analysis and this begins with sampling. This means that the researcher can reduce the amount of data in a principled way, so as to have a more manageable amount for close manual scrutiny (e.g. the researcher can manually sift through the sample to find all instances of a particular pragmatic phenomenon) (see Chapter 7 for examples of this). Garcia McAllister (2015) offers an interesting example of such a process in her research which sought to examine the use of the speech act category of directives in the TOEFL 2000 Spoken and Written Academic Language Corpus (T2K-SWAL). From the main corpus, she drew down a sample of about six hours of talk from the spoken component and identified conversation samples within certain parameters (e.g. those with two interlocutors with English as their first language which had a high degree of interactivity). The 42,797word sample with which she worked comprised: service encounters (39.3%), office hours (32.3%) and study groups (28.3%). She manually sifted through this by reading the transcripts and listening to the audio recordings to identify, code and annotate all instances of directive speech acts. She developed a coding system to assign further linguistic and contextual information to each utterance she had identified as relevant to her study. Ultimately, this process provided her with a listing of each utterance and its corresponding variables and descriptors which in turn allowed her to examine the role of each situational context in predicting the type of speech act used. For example, service encounters were found to be characterised by a high frequency of requests for information, services and payment, suggestions, and putting interlocutors on hold. Reflecting on the process and methodology, Garcia McAllister notes that the most difficult part was identifying speech acts in corpora and annotating them: ‘It took many hours of listening to audiotapes and reading transcripts to code all of the utterances analyzed in this study’ (Garcia McAllister, 2015: 45). Offsetting the labour-intensive nature of this process is the contextual richness of her results in relation to a speech act in spoken academic contexts.

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Using existing research findings as ‘seeds’ for function-toform research Another very plausible option for function-to-form corpus pragmatics is to build on the findings of existing elicitation research (e.g. DCTs, roleplays; see Chapter 2). These findings act as the seeds for corpus searches. Schauer and Adolphs (2006) offer insight into the value of this approach as they provide comparative findings in terms of looking at the same research question using aspects of both a function-to-form and a form-to-function approach. They focused on the speech act of expressing gratitude and took the DCT output from 8 scenarios involving 16 native speakers as their starting point for corpus searches. A total of nine forms emerged from the elicitation task: Thanks, Cheers, Ta, Thank you, Thanks a lot, Thanks very much, Thank you so much, Nice one and Cheers sweetie, and these were then used as search items using the five-million-word Cambridge and Nottingham Corpus of Discourse in English (CANCODE) (see Appendix). Apart from Cheers sweetie, all the forms from the DCT were found in the corpus, though to differing degrees (in terms of frequencies). The three most frequent items that appeared in the DCT were Thanks, Cheers and Thank you, and these forms were also the most frequent (though in reverse order) in the corpus data where Thank you was by far the most frequently used form.

TASK 3.5 COMPARING CORPUS RESULTS I Using two spoken corpora, search for the forms listed in Table 3.2. Remember to use normalized results.1 1) 2)

Compare your results (you could also compare them with those in Chapter 7). Reflect on the usefulness of this approach and design another study where a pragmatic phenomenon could be explored in a corpus based on an elicitation task. It could be based on the results of an existing study (see Chapter 2 for ideas on elicitation tasks and existing studies).

Table 3.2 Comparing Schauer and Adolphs’ (2006) DCT results with two spoken corpora Form

Frequency in Corpus 1 (PMW)

Thanks Cheers Ta Thank you Thanks a lot Thanks very much Thank you so much Nice one Cheers sweetie

Task 3.6 offers a follow-up from Task 3.5.

Frequency in Corpus 2 (PMW)

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TASK 3.6 COMPARING CORPUS RESULTS II 1) 2)

Examine some of the corpus results from Task 3.5 in the concordance lines, with expanded contexts. What do you notice about turn-taking and expressions of gratitude? Reflect on this approach to function-to-form research. What are the merits? What are the challenges?

Of note, Schauer and Adolphs (2006) cite an important difference between corpus data and their DCT output, namely the length of the turn in which gratitude is being expressed. The DCT data is so focused and controlled within the task that it usually generates single utterances rather than stretches of interaction. On the other hand, the corpus data gives a broader contextual picture of the stretch of discourse where the act of expressing gratitude occurs. Schauer and Adolphs (2006) refer to gratitude clusters where, for example, thank you, the most frequent form in the CANCODE data, clustered with other expressions of gratitude. This was not evident in the DCT results. Figure 3.7 shows an extract from the Spoken BNC2014 which illustrates a gratitude cluster. The search item thanks mate was entered into #LancBox and then a random concordance line was clicked leading to this extract. While it is not clear what the thanking relates to, it is interesting to observe how the thanking spreads across many speaker turns.

Figure 3.7 An example of gratitude clustering across turns in the BNC2014 (using #LancsBox)

In summary, and by way of caveat, Schauer and Adolphs’ (2006) finding that the elicited DCT data can distort the overall reality of speech acts which are typically negotiated and developed over a number of turns in a dynamic discourse event confirms other studies, including Bodman and Eisenstein (1988), Hartford and Bardovi-Harlig (1992) and Yuan (2001). Beebe and Cummings’ (1996) study on refusals found that DCTs contained fewer semantic formulae and negotiating strategies and were overall less complex and more direct. However, Flöck and Geluykens (2015), in their study of directives, found DCT data to be more indirect and to contain more downgrading modifiers than real spoken data to which they were compared. However, in their review of eight comparative studies, Flöck and Geluykens (2015) found that the findings were far from convergent. As Taavitsainen and

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Jucker (2015: 17) note, speech act analyses will need to focus more consistently on the interaction between participants and on how speech act values are jointly negotiated and established in the interaction, moving from a one-dimensional focus on single utterances and their meaning to negotiated meaning within the dynamics of real-time interaction. This is a salient point when using or curating elicited task data as seeds in CP.

Solutions for larger corpora Using illocutionary force indicating devices (IFIDs) As discussed elsewhere, illocutionary force indicating devices (IFIDs) offer a useful ‘way in’ to function-to-form analyses. An insightful example of their application on a large corpus is found in Deutschmann’s (2003) study of apologies in the Spoken BNC1994. Using the data comprising a total of 4705 speakers, he narrowed down his sample to only those dialogues produced by speakers whose age and gender were available in the metadata. This left him with a sub-corpus of 5,139,082 words produced by over 1700 speakers. In order to examine explicit apologies, he used IFIDs containing variants of the lemmas afraid, apologise, apology, excuse, forgive, pardon, regret and sorry. He established a database of all the corpus hits generated by this search process and manually sifted through these results to identify the utterances which functioned as explicit expressions of apologies. Once he had ‘cleaned’ the results of all non-apologies, he then analysed the remaining occurrences in the context of the conversation where it was originally uttered so as to classify it functionally and pragmatically. In this process he added speaker metadata, such as gender, age, social class and the person being addressed, to his database for each apology, along with other contextual variables, such as the conversational setting (formality level), conversation type and the number of participants in the given interaction. This work was no doubt labour-intensive but what resulted was a powerful dataset. With this level of meta-detail, Deutschmann was able to generate some very detailed results on how, when and by whom apologies were performed. The scale of Deutschmann’s study allows for robust socio-pragmatic correlations between apologies and outcome variables, such as gender, age, social class, formality level, group size and genre. For instance, he was able to assert that: • •

Younger speakers apologised far more often than older speakers; Speakers from middle-class backgrounds apologised more than their working-class counterparts.

Deutschmann’s findings regarding power relations and social distance showed that the more powerful the speaker, the higher their rate of apology, and conversely, the lower the power of the speaker, the lower the rate of apology. As Woodman (2005: 316) notes, one of Deutschmann’s most novel findings was the correlation between group size and apologies. That is, the more participants in an interaction, the higher the rate of apology. This meant, therefore, that genres such as meetings, classroom contexts and job interviews had more frequent rates of apologies than genres associated with smaller sizes, for example, medical consultations and historical interviews (see Deutschmann, 2003: 161).

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Lutzky and Kehoe (2017a, 2017b) are examples of studies which have built on the work of Deutschmann (2003). They both explore apologies in the diachronically structured 630-million-word Birmingham Blog Corpus (BBC), which spans the years 2000 to 2010. In Lutzky and Kehoe (2017a), for example, they begin with Deutschmann’s eight-core apology IFIDs (see above) and their goal is to arrive at a collocational profile of these items so that they can be used for automatic attestation of apologies within their very large corpus. Lutzky and Kehoe (2017a) begin with a sub-corpus of 95 million words of blogs, plus 86 million words of readers’ comments. Using the apology IFIDs and their lemmas (e.g. pardon/pardons/pardoned/pardoning), they generate all occurrences in the data without distinguishing between apology and non-apology at this stage. Their initial results included many non-apology items, such as I’m afraid if I open it. Their next step was to conduct a detailed word frequency profile of the collocates of each of their initial search items. They set cut-off parameters for collocates: (1) they had to occur within the top 100 most frequent times; and, (2) they had to be within a span of four words to the left or right of the IFID. For example, the collocates of the IFID apologise included items that occurred next to the search word, such as profusely, as well as collocates that were up to four words to the left or right of it, for example, inconvenience or advance. They used a z-score to rank the significance of collocational pairings relative to collocate frequency and corpus size. For instance, they give the example of profusely: this has the highest z-score, even though its raw frequency is relatively low. Although profusely is a relatively rare word (occurring 348 times in the dataset), 30 per cent of all of its occurrences are as a collocate of apologise and thus it has a high z-score. By building a profile of the collocates of all of the IFIDs in this manner, Lutzky and Kehoe (2017a) were then able to aggregate the collocates across all the IFIDs to identify the ‘shared collocates’ (see Lutzky and Kehoe, 2017a: 46–47). This showed some interesting patterns; for example, the pronoun I was a shared collocate of seven of the eight IFIDs (it was not a collocate of apology within the parameters of the study), while ignorance only collocated with pardon, excuse and forgive. Interestingly, the reason for apologising within this genre (blogs) was reflected in this list of shared collocates, such as spelling, typos, poor, quality and English. In addition, Lutzky and Kehoe (2017a) identified the items which were strong collocates with a given IFID but which did not appear within the top 100 most frequent collocates of any other IFID. Among their findings in this set of results were the strikingly colloquial items that uniquely collocated with sorry, such as oops, aww, hugs, sucks, hon/hun (short for the endearment honey). They further investigated oops in Lutzky and Kehoe (2017b) and asserted that it could be added to the list of IFIDs for apologies in blogs. Lutzky and Kehoe (2017a, 2017b) offer a fascinating insight into innovative ways of investigating speech act phenomena in very large corpora. By profiling the similarities and differences in the collocational patterns of several IFIDs, they (2017a: 54) show that ‘functional overlaps’ and ‘divergences can be revealed, which can in turn be used to increase the incidence of relevant examples in the search output’. This ultimately means arriving at greater precision in the automated retrieval of speech acts in large corpora. The authors strongly advocate the place and merits of manual analysis, but they note, ‘our methodological

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approach allowed us to streamline the search for the fairly routinized speech act of apology in our blog data’ (2017a: 54). Task 3.7 tries out one of the findings from Lutzky and Kehoe (2017b) that Oops might be added to the list of IFIDs for apologies in blogs. Here we try out Oops in the spoken component of the Corpus of Contemporary American English (COCA) (see Appendix).

TASK 3.7 OOPS Using the spoken component of COCA, enter a collocation search for Oops using the settings in Figure 3.8, and reflect on whether there is a case for using Oops as an illocutionary force indicating device (IFID) for apologies outside of blogs.

Figure 3.8 Collocate search settings for oops in the spoken component of COCA

Another approach to using large corpora is to start with a small micro-analysis within a specific genre. Kohnen (2008) offers an example of this in his diachronic work on directives in religious texts. The first step involved manually sifting through a representative genre sample (in this case sermons) to identify a search inventory for directives. The pilot micro-analysis was scaled up to a broader representation of the genre (e.g. also looking at prayers, church letters, etc.). From this he was able to recall directives and their distribution in larger multigenre corpora. Through an iterative process, he further refined the inventory and tested their frequency and distribution in a principled way. Jucker and Taavitsainen (2013) observe, however, that while Kohnen’s method provides reliable results for the patterns that are most frequent and most conventionalised, it is far less reliable for rare and creative patterns because it relies on the availability of a sufficient amount of relevant data spread across the period of investigation. For Kohnen (2008), however, this approach worked well because there was a consistent sample of sermons, and related texts, over time.

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Using searches of typical lexical or grammatical features associated with a speech act Taavitsainen and Jucker (2008) sought to examine compliments in three historical corpora. Faced with the challenge of how to retrieve these, they used as their work around adjectives that express positive evaluations, that is, search items such as beautiful, nice, great, lovely, and multi-word units, such as really nice, really great, well done, like/love your, what a, you look/’re looking.

TASK 3.8 COMPLIMENTS 1)

2) 3)

Take any four of the items identified by Taavitsainen and Jucker (2008) (see above) and use them to search the spoken component of the COCA to find at least one compliment from each search. Which of the four items appears to be most successful in recalling compliments? Based on your results, reflect on the usefulness of this approach to retrieving compliments.

Reflecting on their process, Jucker and Taavitsainen (2013: 107) note that while it did provide relevant hits, it also returned a lot of passages that were not relevant to the research focus. The scale of their research, in terms of breadth of sources and span of time, meant that they were able to make a number of interesting statements about compliments in an historical context. For example, in Early Modern and Late Modern English, compliments were found to be gendered. Both male and female authors were found to use compliments in their writing, but female characters received praise for their look(s) and often turned these down as flattery. On the other hand, in the case of males receiving compliments, they accepted them by bowing. They note that this aligned with social norms of the time. In addition, they noted that while most compliments were related to physical appearance and possessions, only a few instances of compliments were about food, and they speculate that perhaps this is due to most protagonists being upper class, and in accordance with social norms of the time the menial task of preparing food was something done by servants.

Using metacommunicative expressions Using what they term metacommunicative expression analysis, Jucker and Taavitsainen (2014) developed a systematic approach to the analysis of compliments in both the Corpus of Historical American English (COHA) and the Corpus of Contemporary American English (COCA) (Jucker and Taavitsainen, 2014: 258; see also Taavitsainen and Jucker, 2008). The approach involved using the search term compliment to retrieve performative, descriptive and discursive instances of the act. This method was a useful starting point even though the term was mostly not used as a compliment. This is because by looking at how compliment was used in the data, the researchers were able to negotiate the contextual parameters of the act. In this historical socio-pragmatic detective work, they first narrowed their sample

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across a spread of five sub-corpora of selected decades within the sample period. These were sampled based on the number of instances of compliment. Subsequently, coders used the extended contexts of the node occurrence to categorise and code compliments for variables, such as type, complimenter, complimentee, object of the compliment, compliment response, as well as logging the genre in which it occurred. They distinguished between personal compliments and ceremonious compliments, and found that in the historical data more than 90 per cent were personal compliments. Within that profile, they noted a steady decline in the use of ceremonious compliments over time. Their analysis offers details on the distribution of the gender of the complimenter and complimentee, and compares that with the contemporary data sample from the COCA. For example, it showed that males were in the role of complimenter between 70 and 85 per cent of the time in the historical data, while, in the COCA sample, this fell to 67.1 per cent. In terms of the gender of the complimentee role there was a balance, apart from the earliest dataset (1820/1830), where males also received the majority of the compliments. The object of the compliment showed a consistent pattern across the centuries where most compliments were given on people’s personality/friendship and on their ability/performance. In looking at how compliments are responded to in contemporary American English, it has been shown that they are normally accepted (see Chen, 1993). Jucker and Taavitsainen (2014) were keen to test this historically through their coding of the response to the compliment within their dataset. They found that ‘acceptance of compliments remained more or less stable for the first four periods under investigation [1820/1830, 1870, 1900] but it is clearly higher in the most recent period [1990/2000], in which it has reached more than 70 per cent’ (Jucker and Taavitsainen, 2014: 273). They speculate that this significant rise in acceptance may be connected with social and cultural changes, or perhaps with a change in literary styles. Reflecting on their use of metacommunicative expression analysis as their methodology, Jucker and Taavitsainen (2014) note that it has both strengths and weaknesses. While it allows for the systematic analysis of a specific speech act in large corpora both synchronically and diachronically, which would be inaccessible to other methods of investigation, the method mostly retrieves accounts of a particular speech act rather than the actual speech acts, and statistical results based on such accounts may be misleading. Nonetheless, it does indicate some very interesting lines of investigation in other large corpora with the potential to apply this approach to other pragmatic areas.

3.5

CONCLUSION

In this chapter, we have argued that if corpus linguistics and pragmatics are to come together fully in the form of CP, it is imperative that we do not shy away from the challenges of developing a method that can accommodate both form-to-function and function-to-form approaches. For corpus linguistics, form-to-function is the default approach and for pragmatics researchers traditionally, it is the reverse. For CP to be truly useful in the hands of all pragmatics researchers, it must be methodologically inclusive. The main challenge is to keep striving for pragmatically annotated corpora and, in doing so, to enhance and develop tools for automating this process. This still remains the Holy Grail but we are moving closer to the treasure.

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3.6

FURTHER READING

Aijmer, K. 2018. ‘Corpus pragmatics: From form to function’. In A.H. Jucker, K.P. Schneider and W. Bublitz (eds), Methods in Pragmatics. Berlin: Mouton de Gruyter, pp. 555–585. O’Keeffe, A. 2018. ‘Corpus-based function-to-form approaches’. In A.H. Jucker, K.P. Schneider and W. Bublitz (eds), Methods in Pragmatics. Berlin: Mouton de Gruyter, pp. 587–618. Both Aijmer’s and O’Keeffe’s chapters offer useful methodological perspectives and processes for corpus pragmatics for both form-to-function and function-to-form approaches. For the development of holistic CP processes, it is important to accommodate a model that includes the methodological processes exemplified across the span of these chapters. Garcia McAllister, P. 2015. ‘Speech acts: A synchronic perspective’. In K. Aijmer and C. Rühlemann (eds), Corpus Pragmatics: A Handbook. Cambridge: Cambridge University Press, pp. 29–51. This chapter provides a useful example of a study where a large corpus was used to examine a speech act (in this case directives) by means of careful, meticulous and principled sampling and analytical processes. The research is honest about the challenges and scale of this approach. It offers a possible model for replication using different corpus data. Lutzky, U. and A. Kehoe. 2017a. ‘“I apologise for my poor blogging”: Searching for apologies in the Birmingham Blog Corpus.’ Corpus Pragmatics, 1, 37–56. Lutzky, U. and A. Kehoe. 2017b. ‘“Oops, I didn’t mean to be so flippant”. A corpus pragmatic analysis of apologies in blog data.’ Journal of Pragmatics, 116, 27–36. Both of these papers are of interest to anyone interested in using CP in the context of exploring speech acts in large corpora. They both draw upon blog data and offer interesting work arounds in terms of using IFIDs to aid speech act recall in a function-to-form approach. While both papers look at apologies, they will be of use for those interested in replicating a study on a different speech act or dataset. Schauer, G.A. and S. Adolphs. 2006. ‘Expressions of gratitude in corpus and DCT data: Vocabulary, formulaic sequences and pedagogy.’ System, 34(1), 119–134. This paper looks at the similarities and differences between data drawn from DCTs and a corpus. The authors focus on expressions of gratitude, using both DCTs and corpus data from the five-million-word spoken corpus CANCODE. They compare their results with a view to pedagogic applications. The paper is also useful to researchers because it offers insights into the advantages and disadvantages of both approaches.

NOTE 1 Corpus software may calculate per million-word results for you automatically. To manually calculate PMW amounts, simply divide the frequency result for the search item by the total number of words in the corpus and multiply this amount by one million.

CHAPTER 4

Reference

4.1

INTRODUCTION

Reference is one of the core concerns of the field of pragmatics. Among the myriad reasons for this is its pervasiveness in both spoken and written language (Biber et al., 1999; Carter and McCarthy, 2006). In general, reference is concerned with the complexities involved in identifying people, places, times or ideas in a shared textual or non-textual/ situational environment. Many of the most frequent linguistic items used to facilitate reference, in English at least, are so-called ‘semantically empty’ items such as I, it, this, that, here, there or then. The study of reference is concerned with how we attribute meaning to items such as these through the use of a shared environment. Take, for example, extract 4.1 from the COCA corpus. (4.1)



And in additional to the facts of what is happening in New Jersey and the threat that they’re feeling, this is all as police [here] are on high alert ahead of the New York City Marathon. [That] kicks off tomorrow at eight thirty. And the mayor said that the bigger the presence of security, the better. And [that]’s especially better for the crowds and the runners. Some of the runners who are running this year, they said that they also were here during 9/11. Some of them have also run in the Boston Marathon when that bombing went off. So some people are uneasy, but others say this is the spirit of the city. We are resilient, and [they] said [they] will not let fear win. Craig, Sheinelle. Resilient indeed. Morgan Radford in Lower Manhattan. Morgan, thank you. (COCA Corpus Spoken Section: Today Show)

In extract 4.1, when we consider the words in square brackets, for example, we can see that the that in that kicks off refers to the New York City Marathon. Similarly, the that in that’s especially better refers to the presence of security. Finally, they in they said they will not let fear win refers to the runners in the marathon, some of whom have also run the Boston marathon. In all these cases, we ‘get meaning for’ the items in square brackets

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by looking (backwards) within the textual environment itself. However, when we compare the underlined words, the meaning comes from a different shared environment. The textual environment cannot provide us with meaning for the time references tomorrow and this year. In order to give these time references meaning, we have to know what day and year it is while we are watching the Today Show broadcast. This information comes from outside the text, from the wider physical, social and cultural context in which the text is situated. Referential items such as those in extract 4.1, and the linguistic processes we use to determine their meaning, are the core focus of this chapter. From a corpus perspective, referential items are ubiquitous, especially so on spoken language frequency lists. In order to illustrate this phenomenon in English, we have generated a frequency list for the top 20 most frequent words in the Limerick Corpus of Irish English (LCIE), represented in Table 4.1. We have marked the items that can be associated with reference, some of which we have already encountered in extract 4.1, in bold. Table 4.1 Top 20 most frequent words in LCIE Rank order

Word

Frequency per million words

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

the I and you to it a that of yeah in was is like know he on they have there

35,171 24,321 23,707 23,011 20,140 18,276 17,753 14,868 13,948 13,689 13,401 10,419 10,006 8667 8052 7365 7281 7264 6831 6628

First, the list contains a number of core referential items in the form of pronouns. Central to the English language system of reference, the first- and second-person pronouns I and you are in positions 2 and 4 respectively. The list also contains other pronouns that form part of the referential system – it (position 6) and the third person pronouns he and they (positions 16 and 18 respectively). Rühlemann (2007: 74) describes the prominence of these pronouns as a ‘striking finding’ which clearly demonstrates the emphasis that should be placed on their importance to the system of reference. Second, we can move beyond these core referential items and identify a number of forms on the frequency list with the potential to function as part of a reference system, but which are

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not always used referentially, a point which we will further elaborate on as this chapter progresses. Among these items are the definite article the (position 1), that (position 8), which can function referentially as a demonstrative determiner or pronoun, and there (position 20), which has the potential to function as a spatial adverb. Finally, if we factor in the role of verb tense in time reference, we can include was (position 12), is (position 13) and have (position 19). All in all, we are looking at 11 of the most frequent items in the spoken language, represented by LCIE, having a role, often of a core nature, to play in reference. It should be noted that these frequency results are not unique to LCIE. An examination of many English spoken corpus frequency lists, and some written, reveals a similar patterning, and, when coupled with, for example, the results from the frequency of two, three and four multi-word units (see Chapters 1, 7 and 8), clearly demonstrate the prominence of pragmatic items in our everyday interaction with one another. In order to explore these items in more detail, we need to more carefully consider their referential role in speech and writing, and that necessitates an examination of their treatment in the field of pragmatics more generally.

TASK 4.1 CLASSIFYING REFERENTIAL ITEMS Consider extract 4.2 from Jane Austen’s novel Emma. Items that refer to people, space and time have been marked with square brackets. 1)

2)

Build a table, such as that illustrated in Table 4.2, to classify these items in terms of their reference to person, place or time, and consider how this reference is accomplished linguistically, for example, through the use of pronouns, determiners, adverbs, etc. Consider whether the meanings of the items on your list are determined from the text itself (textual meaning) or from our knowledge of what is ‘outside’ the text (situational meaning). The first two instances have been done for you.

(4.2) [Shortly afterwards] Miss Bates, [passing] [near] the window, [descried] Mr. Knightley on horse-back [not far off.] ‘Mr. Knightley [I] [declare]! [I] [must] [speak] to [him] if possible, just to [thank] [him]. [I] [will] not [open] the window [here]; [it] [would] [give] [you] all cold; but [I] [can] [go] into [my] mother’s room [you] [know]. [I] [dare] [say] [he] [will] [come] [in] when [he] [knows] who [is] [here]. Quite delightful to [have] [you] all [meet] so! [Our] little room so [honoured]!’ [She] [was] in the adjoining chamber while [she] still [spoke], and [opening] the casement [there], immediately [called] Mr. Knightley’s attention, and every syllable of [their] conversation [was] as distinctly [heard] by [the others], as if [it] [had] [passed] within the same apartment. ‘How [d’] [ye] [do]? How [d’] [ye] [do]? Very well, [I] [thank] [you]. So [obliged] to [you] for the carriage [last night]. [We] [were] just in time; [my] mother just ready for [us]. [Pray] [come] in; [do] [come] in. [You] [will] [find] some friends [here].’

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Person

Shortly afterwards passing

Place

Time

Textual meaning

 



Situational meaning

 (task adapted from Biber et al., 1999: 231–232)

Reference is broadly divided into two main types: exophoric and endophoric. When a linguistic item is described as exophoric, it means that it refers to something outside the text or discourse but is understandable from the context. For example, in extract 4.2, the meaning of near in near the window and not far off in descried Mr. Knightley not far off can only be determined if we know exactly where the window and Mr Knightley are located in relation to Miss Bates. Endophoric reference, on the other hand, is reference to people, places, times or situations within the text or discourse. Therefore, endophoric reference is understandable from the co-text. Endophoric reference is concerned with anaphoric reference and cataphoric reference. Looking back at extract 4.2 again, we can determine from the text that the I in, for example, I will not open the window here, refers backwards, or anaphorically, within the text itself to Miss Bates and, similarly, we can determine that the him in just to thank him refers to Mr Knightley. Finally, in relation to cataphoric, or forward-pointing reference, we can determine from the text that will find in You will find some friends here points forward in the text to the group of people Mr Knightly will meet when he enters the room.

4.2

DEIXIS

The main focus of this chapter, deixis, falls under the domain of exophoric reference. Derived from the Greek word for ‘pointing’ or ‘indicating’ (deiktikos ‘apt for pointing with the finger’), deixis enables interlocutors to refer to entities in context, thereby allowing them to identify people and things in relation to the space in which they are operating at the moment at which they are speaking. Table 4.1 has briefly introduced a number of items that encode deixis, for example, the first and second person pronouns I and you; the demonstrative use of that; adverbs of space such as there; and other grammatical features such as tense markers. These items that encode deixis are commonly referred to as deictics (marked in bold in extract 4.3). (4.3) [Context: Recording takes place in the home between intimates. Speakers are numbered according to their appearance in the extract.] well the various cross-channel ferries have been cancelled for today into tomorrow because of this storm oh right yeah (Spoken BNC2014: Text S263)

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The meaning of deictic items today and tomorrow can only be retrieved from the context of the situation. Therefore, we have no way of knowing the time reference for today or, indeed, for tomorrow unless we were present when the words were spoken.1

TASK 4.2 DEIXIS AND THIS STORM Consider extract 4.3; discuss how this storm operates with deictic reference in this stretch of discourse. This storm can be considered deictic as, although we can infer from the co-text that it might be accompanied by strong winds, given that states that various cross-channel ferries have been cancelled, we have no idea how strong the winds are or the nature of the storm itself unless we experience it first-hand. Similarly, in terms of space, unless we have a shared knowledge of the area being discussed, we have no idea as to the place signified by the repeated use of down there in extract 4.4. (4.4) [Context: Recording takes place in the home between intimates. Speakers are numbered according to their appearance in the extract. The participants are discussing speed limits on rural roads.]











it should be that should be the rule country roads why do forty they have though? why have they got well well they go up to sixty up there god you can’t do it this road they you you can do and people you know that big sharp corner down there? mm they come down there there’s the youngsters especially mm yeah they come down there and think that they can get round that big old sharp corner and they go off into the left and they go off yeah you there’s there’s no end of problems yeah (Spoken BNC2014: Text S38P)

The choice of the demonstrative determiner that over the definite article the in the expression that big (old) sharp corner (extract 4.4) indicates that knowledge of the

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referent is shared between the interlocutors (see Strauss, 2002). The choice of that may also indicate that the interlocutors have a shared opinion about the referent – in this case, the opinion is likely to have negative connotations and may be connected to the category of empathetic deixis (see Section 4.4). In both extracts 4.3 and 4.4, it is unlikely that the referents are necessarily accompanied by a gesture, and therefore appear to be cases of symbolic deixis. Where a referent is accompanied by a gesture, primarily some sort of pointing movement but might also be a nod or an eye movement, it is often referred to as gestural deixis. It is likely that ’s first use of that much in extract 4.5 is accompanied by a gesture of some sort to indicate how big a piece of skirting board is required. (4.5) [Context: Recording takes place in the home between intimates. Speakers are numbered according to their appearance in the extract.] so you I mean you didn’t buy the skirting board did you? So how much skirting board no you need do you still need? yeah you need to I need about that much well you need a full length for the under that window don’t you? yeah that’s about that big isn’t it? well no bit long yeah you’ll have to put a tape on it no it’s about that much (Spoken BNC2014: Text S263) Extract 4.5 also presents us with an opportunity to discuss the distinction between exophoric reference and endophoric reference. In order to interpret a deictic referent correctly, the conversational participants have to ‘look’ beyond the words that are actually used and instead find meaning through referencing the shared, immediate situational context or a shared knowledge context (be it personal or cultural). On the other hand, endophoric referents, whether anaphoric and cataphoric, are generally located in either the preceding (anaphora) or the forthcoming text (cataphora). Returning to extract 4.5, we can see that after ’s first use of that much, remarks, you need a full length for under the window. agrees with this assertion and then uses that big and that much again in subsequent turns. ’s use of a full length raises the question as to whether the subsequent use of that big and that much are deictic or anaphoric in nature. It could be argued that that big and that much by now refer to a full length of skirting board as indicated by . However, it could, we feel, equally be argued that they are deictic in nature with consistently indexing, probably with accompanying gestures, the space invoked through the use of the first that much.

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Referential categories Deixis is often considered independently from anaphora and cataphora; however, just how independent they are from one another is a subject of debate (see Lyons, 1977; Levinson, 1983; Wales, 1996; Marmaridou, 2000; Rühlemann, 2007). Indeed, Lyons (1977: 676) maintains that a term can be used both deictically and anaphorically. Take the example I was born in New York and have lived there ever since. In this example, adapted from Levinson (1983: 67), there simultaneously refers backwards to New York but also contrasts with here in the space deictic dimension, locating the utterance outside of New York. Similarly, in Halliday and Hasan’s (1976: 3) example Wash and core six cooking apples. Put them into a fireproof dish, them does not refer to the six cooking apples per se but rather to the washed and cored apples, a reference which is constructed on the basis of background contextual knowledge of the genre of recipes (see Wales, 1996). Rühlemann (2007: 63) maintains that ‘another difficulty in drawing the line between deixis and anaphora derives from the fact that deictic items may well be used in institutionalised expressions in which only faint, if any, traces of the deictic origins persist’. He cites examples such as the vague expression this and that and the discourse marker there you go. Anaphora and deixis are therefore closely related and the lines between them frequently blurred. The final category of reference that requires a brief mention is what Halliday and Hasan (1976) refer to as non-phoric. One of the most commonly cited occurrences of non-phoric reference is in relation to the use of this in conversational narrative; for example, a story typically begins with There was this man…2. This man, claim Halliday and Hasan (1976), does not occur previously in the narrative (anaphoric), is not subsequently introduced (cataphoric), nor does he exist with the context of the situation itself (exophoric). The proximal demonstrative this is used to refer to a person that exists in the imagination of the interlocutors. This phenomenon has been variously referred to as deixis am phantasma (Bühler, 1934: 121–140) and deictic projection (Lyons, 1977). Strauss (2002: 138) maintains non-phoric that ‘signals shared information’ but of a different kind (see section on discourse deixis, p. 82). In the following extract (4.6), the use of that (marked in bold) is classified non-phoric because it has not been used to refer to an entity in the surrounding speech situation and also because the speaker believes that the hearer knows that referent and the shared information.

(4.6) [Context: The conversation takes place in the home between intimates. Speakers are numbered according to their appearance in the extract. = mother; = son (age 24); = father; = son (age 14).] Where did you go on Saturday night after that Conor? We didn’t go anywhere. Didn’t you ? Home .

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Home. Nosey. (LCIE) In this extract, when mentions that, she believes that has sufficient shared knowledge in order to assign reference. Here that refers to a bar in which met and the previous Saturday. This shared knowledge between and is confirmed when he responds We didn’t go anywhere rather than ask for any clarification about the referent. The intimate context-type of this extract enables the speakers to invoke non-phoric reference due to the high level of shared knowledge that exists in these intimate speech situations.

4.3

THE DEICTIC CENTRE

The deictic centre, or origo (a term coined by Bühler, 1934), refers to a perceived egocentric organisation of the deictic system. Traditionally, this centre is typically organised around an ‘I–here–now’ axis where ‘the speaker casts himself in the role of the ego and relates everything to his viewpoint’ (Lyons, 1977: 638). Therefore, in relation to the centre (or anchor point) for the three major categories of deixis – person, place and time (see Section 4.4) – the centre for person deixis is the speaker (the ‘I’), the centre for place deixis is where the speaker produces the utterance (the ‘here’) and the centre for time deixis is the time at which the utterance is produced (the ‘now’). The deictic centre is associated with the current speaker; therefore, when the speaker changes so too does the centre. In extract 4.7, in which four female friends are getting ready for a night out, the use of the personal pronouns I and you demonstrates this deictic centre switch. (4.7) [Context: Friends chatting in shared accommodation. Speakers are numbered according to their appearance in the extract.]





What top are you wearing? The lemon one. I don’t have a jacket. You have a jacket the denim one. I have a jacket cos it matches. Do you remember one night out in Dublin I brought no jacket? I do. And I got very cold. (LCIE)

and use I in their speaker turns, indicating their acknowledgement that they are now at the deictic centre of the conversation. In addition to this, the personal pronoun you moves between several different referents. In ’s first turn, she uses you to refer to . In her second turn, she uses you to refer to . also uses you to refer to

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in Do you rememberone night out in Dublin I brought no jacket? This acknowledgement that the deictic centre has shifted from one speaker to the next (hence Jesperson’s (1965) use of the term shifters to refer to deictic expressions) clearly demonstrates one of the primary reasons for the frequency of the pronouns I and you in spoken language in general. This constant movement of centre from participant to participant can cause problems for both first- and second-language acquisition. Although the English-language system of person deixis can present difficulties, it is also a fact that many other languages have more complicated systems. In some languages there are three second-person pronouns you (singular, plural and formal) – du, ihr and Sie in German, for example. These are used as a formal way to address someone. Therefore, in addition to functioning as person deixis, they also function as social deixis (see Section 4.4).

The non-egocentric deictic centre The notion of an egocentric origo has not gone unchallenged (see e.g. Lyons, 1977; Hanks, 1992; Jones, 1995). According to Jones (1995), theories in favour of the egocentricity of deixis fail to take into account that communication is a social act. He claims that it is inaccurate to call the speaker in conversation the ‘central person’ just as it would be to call either the husband or wife the ‘central person’ in a marriage – ‘it takes two to tango and two to communicate’ (1995: 37). This notion of a non-egocentric origo can be seen in a father’s interaction with his young son in extract 4.8 while they are sitting at the breakfast table. (4.8) [Context: Conversation takes place in the family home. Speakers are numbered according to their appearance in the extract. = father; son 1; son 2; = mother.]





Are you goin with daddy? Yeah. Who’s funeral’s on now mammy? Eat the breakfast so and we go. Jim Smith’s. Are you goin with daddy in the motor car? Oh sorry. I’m goin with daddy. (TravCorp)3

In this extract the father clearly aligns his own identity with that of his baby, and this is achieved in a number of ways (marked in bold in the extract). First, his utterance Are you goin with daddy?, repeated twice, connects you with daddy, thus establishing a shift from a lexical realisation of self for the father to the perspective of his child. The everyday identity the father carries with him is the I; however, to his son he is daddy and his self-reference of this is evident. Second, in the utterance Eat the breakfast so and we go, the father combines his and his son’s perspective into one and the same using an inclusive we (see Section 4.4). Wales (1996: 56) offers a number of possible reasons for parents’ use of kin titles like

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daddy when talking to infants. She suggests that parents use them because they ‘recognise the problematic “shifting” nature of speaker/addressee roles, of I and you reference’. This recognition of the difficulty for children with I/you reference is acknowledged by the parents switching the origo from themselves to their children through their use of you. This seems to highlight the flexibility of the deictic centre – an utterance is necessarily centred in the sense that some speaker’s viewpoint is inevitably assumed; however, whose viewpoint, the speaker’s or a co-participant’s, is a matter of flexibility. In extract 4.8, the father’s utterances reflect the close connection he feels with his son constituted by his use of deictic expressions (see also Tannen, 2007). Although the examples used to illustrate this section are person deictic in nature, the deictic centre is also associated with place and time deixis, and it is to these categories of deixis that our attention now turns.

4.4

BASIC CATEGORIES OF DEIXIS

Deixis is traditionally subdivided into a number of categories; person, place and time deixis are the most common of these categories. Two additional categories, discourse and social deixis, are also present in some of the most influential work done in the area (cf. Lyons, 1977; Levinson, 1983; Fillmore, 1997). There is also a sixth deictic category referred to as empathetic deixis (see Lyons, 1977).

Person deixis Person deixis is concerned with ‘the identity of the interlocutors in a communication situation’ (Fillmore, 1997: 61). Personal pronouns such as I and you are the most obvious and most frequent manifestations of person deixis. Table 4.1 demonstrates that five personal pronouns – I, you, it, he and they – occur in the top 20 most frequent words in LCIE which is consistent with many other corpora of spontaneous, face-to-face casual conversation. Similar findings have also been recorded by Biber et al. (1999) working with the LSWE Corpus, O’Keeffe et al. (2007) working with the CANCODE and CIC corpora, and Rühlemann (2007) working with the BNC. This is in contrast with written corpora. For example, frequency lists based on the written component of the BNC show he in 14th position, I in 17th and you in 21st (Leech et al., 2001b). Regarding the distribution of these pronouns, Biber et al. (1999: 333) have shown that the pronouns I and you are far more common in casual conversation than in other registers, such as academic prose. Rühlemann (2007: 66–69) posits four reasons for the preferred use of I and you in casual conversation; (1) I is prone to repetition (I is repeated at a frequency of about 200 times per million words in conversation (see Biber et al., 1999: 334)); (2) I and you have a high frequency of collocation, especially with verbs of thinking, for example, I think and you know; (3) discourse is typically presented in a direct mode, where, for example, a non-present speaker’s words are represented as if he or she were actually present, and (4) conversation is co-constructed, with speakers taking turns, and each new turn requires the reconstruction of the new speaker’s deictic system.

REFERENCE

One of the most interesting personal pronouns in the English language system of reference is the first-person plural pronoun we. At a basic level, we can be both inclusive (I the speaker + you the addressee(s) in the immediate context) or exclusive (I the speaker + other(s) not present in the immediate context). Extract 4.9 features a family putting up their Christmas tree. The extract contains a number of instances of the use of inclusive we (marked in bold) and exclusive we (marked in bold and underlined). (4.9) [Context: Family putting up a Christmas tree. Speakers are numbered according to their appearance in the extract. = father; = son (age 14); = daughter (age 22); = mother.]





Do we need more around there? Yeah a bit more. All right? Yip. We might need another bit now but hang on a second and I’ll press it down. We have them outside too the eighty mini bulbs. Is that what they are? Eighty mini bulbs. Yeah we’ve them too. We don’t need those til tomorrow. Are we not putting it up til tomorrow dad no? (LCIE)

The first two instances of we (Do we need more around there? and We might need another bit now…) are examples of inclusive we given that the speaker in both instances is referring to themselves and the other participants assisting them with the task of putting up the tree, namely the other members of the family. Similarly, We don’t need those til tomorrow and Are we not putting it up til tomorrow dad no? refer to the participants in the immediate context. However, ’s assertion We have them outside too the eighty mini bulbs and Yeah we’ve them too are examples of exclusive we. Both we and outside refer to ’s place of work; we referring to her membership of the staff of the organization and outside referring to the location of the workplace, perhaps in contrast to the ‘inside’ context of the family home. is referring to context outside the immediate conversation and relying on the common ground between the interlocutors to enable them to assign the correct interpretation to the deictic item. Vaughan and Clancy (2013) point out that the broad framework of inclusive and exclusive we can be successfully applied to family discourse but needs more elaboration in relation to the workplace context (see also Fortanet, 2004; Vaughan, 2007; Handford, 2014). In the workplace, in addition to identifying in-groups and out-groups, we is also required to ‘perform more complex functions in relation to politeness’ (Vaughan and Clancy, 2013: 69). Rühlemann (2007: 71) notes that we is more frequent in context-governed discourse (such as pedagogic, professional or transactional discourse) because ‘maintaining group identity is one of the underlying principle concerns’. In the context of media discourse, O’Keeffe (2006: 98–99) maintains that we, our and us ‘are central to the process of establishing and maintaining a sense of commonality and inclusion in

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everyday casual conversation between people who have a real common bond’. In media discourse, therefore, speakers can use we in order to immediately create an in-group identity.

TASK 4.3 FREQUENCY DISTRIBUTION OF WE IN COCA Table 4.3 shows the frequency results for we in the overall COCA corpus in addition to its frequency in the spoken, fiction, magazine, newspaper and academic sub-genres (generated using the ‘Chart’ function on the COCA interface). As can be seen, we occurs almost 4500 times per million words in the corpus overall. 1) 2)

Note your observations about the frequencies of we across COCA genres. How might the frequency differences be explained?

Table 4.3 Frequency counts for the occurrences of we in COCA

Place deixis Sometimes called spatial or locational deixis, place deixis is primarily concerned with the location of people or objects relative to the deictic centre. As has been demonstrated, the deictic centre frequently has the speaker as centre; therefore these locations are often relative to the speaker’s position. Notions of place deixis are commonly expressed using demonstratives (this, that, these, those), deictic adverbs of place (here, there) or verbs of motion (come, go, bring, take). However, locations can also be specified relative to other objects using prepositions of place, such as above, below, left, right, behind or from.

TASK 4.4 IDENTIFYING PLACE DEICTICS Identify the linguistic item(s) that represent spatial/locational deixis in extract 4.10. (4.10) [Context: = female (age 34); = female (age 33).]

oh wow look at that it’s quite big actually

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what your allotment or the plan? yeah a bit well both it’s not to scale erm so the gate would be here okay and then is it all fenced off then? so there’s a fence round the outside is there? yeah oh that’s very London erm well yeah there’s a gate with a padlock is there? and but that’s cos so the allotments are all dotted around er this estate so there’s m-mine is here there’s one behind mm and then there’s two next to us so okay so (.) erm the gate’s here (Spoken BNC2014: S2TP)

In many languages there exists a fundamental distinction between proximal (or relatively close to the speaker) and distal (non-proximal, sometimes relatively close to the addressee) deictic expressions of place (Diessel, 1999; Levinson, 2004). For example, here and there are crucially tied to the deictic field of the speaker, and the addressee(s) determines the spatial coordinates of the utterance in order to assign meaning. The extent to which context is involved in determining the reference of here is evident in the interaction in extract 4.11 between participants in a biochemistry study group in the MICASE corpus. (4.11) [Context: Biochemistry study group. All speakers are senior undergraduate students. = female; = female; = male. Speakers numbered according to the original transcripts.]





do I have to know these enzymes like, explicitly, really? you do have to know the enzymes. like all of ’em, for, every cycle? or anything I’d be pretty su- y- you, I’m pretty subut wouldn’t she like kinda [ for the] tell you like, in this reaction, [ like you y-] from here to here we use this enzyme yeah she’s not gonna ask you to draw it out or anything. (MICASE: Transcript SGR175SU123)

In this extract the participants are discussing whether or not it is important to know the names of certain enzymes. uses here to here to point to a specific part of a chemical formula that appears to be written down somewhere in the shared immediate context. We have, of course, already encountered the phenomenon of place deixis previously in this chapter in extract 4.4 when we looked at ’s repeated use of down there.

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Time deixis According to Huang (2007: 144), time deixis ‘is concerned with the encoding of temporal points and spans relative to the time at which the utterance is produced’. In other words, in order to correctly interpret a time deictic, it needs to be considered in relation to the time at which the communicative act takes place. To do this correctly, we need to distinguish between coding time (CT), the moment of the utterance, and receiving time (RT), the moment of reception. Coding time is usually located around the speaker, whereas receiving time is located around the addressee. Usually, because the majority of conversation is face-to-face in nature, CT and RT are considered to be identical. However, there are situations where CT and RT are different, and this can lead to a situation where the utterance becomes unanchored (see Fillmore, 1997: 60). For example, Fillmore suggests a ‘worst case scenario’ for an ‘unanchored’ sentence: finding a message in a bottle which says Meet me here at noon tomorrow with a stick about this big. Notions of time deixis are expressed using both simple adverbs of time, such as now, then, today, tomorrow, yesterday, and complex adverbs of time, such as this month, next year or last week. Similar to place deixis, time deixis also distinguishes between a proximal time now (time ‘around now’ including the CT) and a distal time then (time ‘not now’).

TASK 4.5 IDENTIFYING TIME DEICTICS Identify the linguistic item(s) that represent time deixis in extract 4.12. (4.12) That points to a complex evolutionary story. Two cognitive scientists at Lund University in Sweden, Can Kabadayi and Mathias Osvath, conducted a series of experiments with five captive, hand-raised ravens. Obviously, that’s not a lot of ravens, and hand-raised ravens do not behave like wild ravens. But when it comes to figuring out the outer bounds of cognitive abilities for a species, those aren’t the most important problems to worry about. Testing more ravens, and wild ravens, comes later. Jelly bean now, or burger tomorrow? First, the ravens had to be given an experience they could plan for. They learned how to operate a puzzle box that opened to yield a reward, but the box could only be opened with a specific tool. The next day, they were shown the puzzle, loaded with food, but no tool. Only an hour later they were shown a tray of objects, including the tool, and given the opportunity to choose just one thing. Fifteen minutes later, the puzzle came. (COCA Magazine Section: Ars Technica (publication date 17 July 2014)) Corpus linguistic methods can be used to substantiate the assertion that today, tomorrow and yesterday are preferred in spoken discourse over lexicalised names of days like Monday, Tuesday, etc. (see Levinson, 1983; Fillmore, 1997; Grundy, 2008). Table 4.4 illustrates the frequency of occurrence of the time deictics today, yesterday and tomorrow compared to the occurrences of the seven days of the week in LCIE.

REFERENCE Table 4.4 Comparison of the frequency of occurrence of yesterday, today and tomorrow with the lexicalised names for days of the week in LCIE (normalised per million words) Time deictic today yesterday tomorrow

Total

Frequency per million words 549 389 296

1234

Day of the week

Frequency per million words

Monday Tuesday Wednesday Thursday Friday Saturday Sunday Total

111 100 85 106 172 202 169 945

Table 4.4 demonstrates that the three time deictics today, yesterday and tomorrow occur more frequently than the lexicalised names of the days of the week. The time deictics occur 1234 times per million words, whereas the days of the week have a frequency of 945 occurrences per million words. The days of the weekend, Saturday and Sunday, account for 39 per cent of occurrences of the lexicalised days of the week (if Friday were to be included, that figure rises to 57 per cent). Interestingly, today is the most frequent time deictic, accounting for 44 per cent of the occurrences of these adverbs of time, and this, coupled with the high frequency of occurrences of the personal pronoun I in Table 4.1, adds further credence to I and now components of the ‘here-now-I’ deictic centre.

TASK 4.6 DAYS OF THE WEEK Using a spoken corpus, such as COCA or the Spoken BNC2014: 1)

Search for the frequencies, per million words, of the following and note the totals a b

2)

the lexicalised days of the week the items yesterday, today and tomorrow.

Compare the results to those in Table 4.4.

The most frequent, and quite possibly the most complex, representation of time deixis is tense. According to Levinson (1983: 77), ‘tense is one of the main factors ensuring that nearly all sentences when uttered are deictically anchored to a context of utterance’ (cf. Lyons, 1977). A brief examination of any extract from spoken corpora (or indeed written ones) illustrates the prevalence of tense in conveying time deixis. Consider extract 4.13, tense underlined. (4.13) [Context: Two family members are discussing an acquaintance. Speakers are numbered according to the original transcripts. Yoke is a slang term in Irish English, meaning thing. It can also be used pejoratively to refer to a person, as is the case here.]

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Say that yoke was only ringing me to brag about last night. Oh Paddy. Um. Did he ring you or texted you? Rang me. You should ring back for the laugh. No I’m not wasting credit on him because he’ll say oh he just can’t live without me and oh boy god Paddy I can live without you. (LCIE)

As we can see, time is marked through the use of a verb in a number of different ways (e.g. past simple, present simple, past continuous, will future) used in the extract. However, most of these make reference to either the present or around the immediate present time. This ‘around the immediate present’ time reference is established by the presence of the only one non-tense deictic expression last night. Therefore, all the past time deictics encoded by the verb phrases (e.g. was only ringing, texted, rang) refer to the recent past. In addition, the will future he’ll say refers to immediate future time. This extract demonstrates the importance of the verb phrase in anchoring speakers in the ‘here-now-I’ deictic centre.

Discourse deixis Similar to anaphora or cataphora, discourse deictics can be used to point to elements in the preceding or following discourse. However, there are a number of differences between discourse deictics and anaphoric or cataphoric reference (see Diessel, 1999: 100–103). As we have seen, an anaphoric reference is used to ‘track’ a preceding noun phrase. Take, for example, the anaphoric use of this in extract 4.14 taken from a radio phone-in programme. In this extract, this (in bold) refers ‘backwards’ to a previously mentioned tattoo that ’s husband has on his shoulder. (4.14) [Context: Radio phone-in programme, on a call discussing tattoos. = female, participant; = female, presenter. Speakers are numbered according to the original transcripts. indicates the beginning and the end of overlapping speech.]





I know because I mean you’ve seen people with things on their arm ’’I love Jane’’ and then many years later they’re married to Susan which is a bit bit awkward. That’s right yes yes no no there’s nothing nothing like that am. Right and wha= you you really did do you do not like this I mean it’s not just a mild thing I mean you think that there are all sorts of negative associations. I do actually yes aam maybe years ago sort of arr uh I don’t want to aah sort of upset sailors or anything by saying it aah that sailors had them done and aam also I think

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there’s um a lot of undesirables criminals and people like that and ah I feel maybe aam eh in years to come he might regret it ah having this put on. Yeah did you did you you’ve seen it obviously I mean. Oh I have yes. (LCIE)

Discourse deictics, on the other hand, are used to ‘focus the hearer’s attention on aspects of meaning, expressed by a clause, a sentence, a paragraph or an entire idea’ (Diessel, 1999: 101). In extract 4.15, the discourse deictic this (in bold) is used by while chatting to one of her female friends to refer to an extended narrative, not a single noun phrase. (4.15) [Context: Female friends chatting. Speakers are numbered according to their appearance in the extract.]



Jeanette’s house is the funniest house I’ve ever been in. Listen to this. I remember when I was in first year of college Jeanette’s mother was having a surprise eighteenth birthday party for her right. Jacinta and Mandy couldn’t go right. They’d invited the three of us to go right. You must have been invited too but I don’t know why you didn’t go. Anyway and typical me I thought I better go you know and represent like. Represent. So I get the train from Cork to Dublin right. Jeanette’s mother is there right and she’s such a chatterbox right and she loves my dad and she’s always saying tell him to ring me. [Laughter] I arrive and I’m kinda nervous like cos I’ve never met all of her family before. I’ve met like Linda and that was it and I get to the house anyway and I’m sitting down anyway and they had made so much food like and I was like no I’d just eaten cos I’d eaten on the train like but we had a few sausages and rashers anyway. We were about to have a big dinner within a half an hour of me having these rashers and sausages like. Oh I could have hung on like. Next thing she arrives over with eight sausages on a plate and that was it. Eight sausages and six slices of bread. I was just like “oh my God”. I was just like ah I have enough. Like on a plate. On a small side plate with just eight sausages. All her brothers and sisters were sitting around me like and asking me was I ok and the eight sausages like. [Laughter] (LCIE)

’s use of this in Listen to this anticipates the full story of her journey to a friend’s eighteenth birthday party that follows and is also intended to illustrate what means by Jeanette’s house is the funniest house I’ve ever been in. As extract 4.15 demonstrates, discourse deictics focus attention on aspects of the ongoing conversation and, therefore, in contrast to person, place and time deixis, do not reference the immediate, physical environment. Discourse deixis is distinct from anaphora in that the distal demonstrative pronoun this in extract 4.15 refers only to content produced by ; deictic demonstratives do not move beyond speaker boundaries as can anaphoric or cataphoric reference (see Chen,

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1990). This is in contrast to extract 4.14, where we can see that the anaphoric use of this moves across speaker boundaries in that it is used by both and . Discourse deictics can also be employed to refer to the underlying intention of the content of an utterance (also known as illocutionary force; see Chapter 6). Extract 4.16 exemplifies the use of a demonstrative that (in bold) with a focus on the illocutionary force of an utterance. (4.16) [Context: Family members chatting about an upcoming wedding. = female (age 23); = male (age 27); = female (age 24). Speakers are numbered according to their appearance in the extract.]



Oh look at that the Bay View over there. That’s the hotel there Anna where Judy is having her reception. Oh right yeah. And if I don’t lose enough weight I won’t be there. That’s a lie. Well I must get dieting fast so won’t I and lose some of my eight stone. [Laughter] (LCIE)

In extract 4.16, the interpretation of that is more complex than the tracking of a previous noun phrase. The demonstrative that does refer to ’s assertion And if I don’t lose enough weight I won’t be there. However, more specifically, that refers to the meaning embodied by ’s assertion. Through saying And if I don’t lose enough weight I won’t be there, is not commenting on whether or not she will be at the wedding, but is, in fact, claiming that Right now, I’m fat. ’s That’s a lie is a response to ’s intended message and not the literal content of the utterance (also known as propositional content). Fillmore (1997) also includes deictic items peculiar to written discourse such as above or below in discourse deixis.

TASK 4.7 IDENTIFYING DISCOURSE DEICTICS Extract 4.17 is an extended piece of writing from an essay contained in the British Academic Written English (BAWE) corpus (see Appendix). The extract is from a history essay that explores the rise of modern China. 1)

2) 3)

Read the piece and identify the discourse deictics. Remember: the realm of discourse deixis moves beyond anaphora and cataphora, to the level of sentence, idea or, in the case of written academic discourse, argument. To what category of deixis does the writer (used on two occasions in extract 4.17) belong? Examine the use of items identified as discourse deictic (in this text) in other corpora, such as the academic component of COCA, and explore whether or not these items are used consistently as discourse deixis.

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(4.17) Despite the consolidation of power during the reign of the Emperor Kangsi to Qianlong, there remained however, certain underlying grievances that were never fully eradicated. . . Though westerners have had a presence in China dating back to the Yuan dynasty, the Opium Wars and the corresponding treaty system marked a watershed for China–West relations, resulting in the change of status quo, of perceptions; and manifested itself in the increasingly intrusive presence of the West. . . It is in this context that the above question should be addressed, and the writer will examine firstly the internal conditions and entrenched corruption which made it conducive for the outbreak of social unrests, followed by the implications of change brought about by the West, such as the desire to trade, introduction of new technology . . . and in turn produced a virulent anti-foreign nationalism which threatened the social order during the period in question. Hence the writer will argue that the social unrests at the beginning of the 19th Century was due more to the internal rather than external factors; but increasingly, the presence of the West is crucial to the emergence of violent xenophobic nationalism, which account for the social unrests in the later part of the 19th Century. (BAWE: File 0019j) Levinson (1983) specifies items such as utterance initial but, therefore, in conclusion, well and however in discourse deixis, as they indicate the relationship, in both written and spoken language, between an utterance/sentence and the prior discourse. For example, as in extract 4.17, however, though not sentence initial, does signal a contrast between what follows however and what has been previously written in the sentence. Therefore, more generally, Levinson (1983: 89) contends that ‘the scope [of a proper theory of discourse deixis]…may be very large, ranging from the borders of anaphora to issues of topic/comment structure’.

Social deixis Social deixis refers to ‘those aspects of language structure that encode the social identities of participants (properly, incumbents of participant-roles) or the social relationship between them, or between one of them and persons or entities referred to’ (Levinson, 1983: 89). For example, as already mentioned, many European languages contain the tu/vous distinction. Hence, social deixis can contain information about the conversational participants such as age, sex, kin relationship, social class or ethnic group. For this reason, terms of address (see also Chapters 5 and 9) are often included as a common way of realising social deixis (especially in English, which, in comparison to many other languages, has a relative paucity of linguistic devices which convey social deixis). Extract 4.18, taken from MICASE, features the use of a formal title and surname Professor Gaston by an undergraduate student who has called to a university professor’s office during her allotted office hours. (4.18) [Context: Economics office hours. Speakers are numbered according to the original transcripts. = female faculty; = male undergraduate; = male

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undergraduate. Square brackets in the transcription indicate backchannels; - indicates a false start on the part of a speaker; (xx) indicates one or more words that are completely unintelligible.]



oh okay I see what you’re saying. then we went carefully over incidence, um reminding us what the tax is and, we have elastic inelastic and by the time we got done I had put, all this stuff up [ (xx) to see] so they could, re- remember what, um, consumer expenditure is what supplier, revenue is what the tax is. yeah (xx) compare E to E-prime, hi how are you be with you in just a minute. [ hi Professor Gaston okay great.] compare E to E-double-prime, um compare E-prime to E-double-prime for any of the things we’d ask about, whether it’s expenditure or, (spiralling) tax, and then we did the same thing only, this was the one extreme case we did, uh what if we had perfectly inelastic, demand? and I told them they should look at the other three, [ mhm] extreme cases. then we did the same thing for supply, and reminding them that the same straight upward shift for the tax doesn’t look the same, here, um and again we could compare E to E-prime E to E-double-prime or E-prime to E-double-prime but the one, interesting thing we noticed here is that, whether the big green rectangular big purple rectangle’s bigger is gonna depend on price elasticity of demand not on any characteristics of these, supply curves. and I told them they should practice redrawing these because it shouldn’t look like, muddles of lines they should see things in here. (MICASE: Transcript OFC280SU109)

Rühlemann (2019) cites the example of a university professor as an illustration of the range of address forms that can be used to refer to one addressee. Each of these encodes the range of social relationships that can exist between an interlocutor and the professor. For example, here we have the use of the formal title and surname that encodes the formal relationship between undergraduates and faculty. However, Professor Gaston’s friends probably address her using a first name, maybe familiarised, or her nickname, whereas her partner might use a term of endearment such as darling and, if there are children involved, then Professor Gaston is likely to be simply mum.

TASK 4.8 SOCIAL DEIXIS AND CONTEXT Examine extract 4.19 which is part of a conversation in the Spoken BNC1994. 1) 2)

Based on the social deictics used (marked in bold), what might be the context of the speech situation? Use the social deictics, and any other linguistic clues, to determine ‘who’s who’ in the conversation.

REFERENCE

(4.19)



















Chrissy? Mm? Want some turkey? Do you want some turkey? No thanks. Did you David? I’ve got hazelnut and ham haven’t I? Mm mm. [unclear], one of those. And some of that. I didn’t wash all this so there’s Well I must admit There’s more if you need it. It tastes better if it’s washed and put in that, in that cling film. Mhm. It keeps better than it’s left in the bottom of the fridge. Has David got some coleslaw? You will eat your coleslaw honey won’t you? Mhm. He’s got some but he’s not very enthusiastic. I thought you said you liked it? I go off and on it, but Oh. Sometimes I do, and sometimes I don’t. Right. Ow! But it, it doesn’t keep forever. When did I make it? Saturday. So it wants using. I’m doing my best, you know ma= Well, I’ve made some more since then. You know me and coleslaw. Oh, so I don’t have to rush it? Well, not that. I’d prefer it to go. Have you got everything you want kiddies? Yeah. Yes. And a bag of crisps, got the same packet. Boys, when we next see Gywneth will you be nice and quiet and kind to her, her Mummy’s just died? (Spoken BNC1994: File KCH)

Empathetic deixis Finally, we come to the notion of empathetic deixis. Empathetic deixis was first posited by Lyons (1977) based on the speaker’s choice of this rather than that, here rather than there or now rather than then, ‘when the speaker is personally involved with the entity, situation or place to which he is referring or is identifying himself with the attitude or viewpoint of the addressee’ (Lyons, 1977: 677). Rühlemann (2007: 192) maintains that empathetic deixis ‘seems to involve preference of deictics that are characterised by being, literally or metaphorically, nearer to the deictic origo (here being nearer than there, now being nearer than

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then etc.)’. Therefore, when a speaker makes a choice of that rather than this, for example, he or she is signalling his or her emotional relationship with the propositional content of the utterance. In extracts 4.20 to 4.22, the use of that (in bold) demonstrates the affective implications of the choice of the demonstrative. (4.20) [Context: Family chatting at home. Speakers are numbered according to their appearance in the extract.]



Yeah exactly. She still has that bike of hers. Does she? Yeah. (LCIE)

(4.21) [Context: Female friends chatting. Speakers are numbered according to their appearance in the extract.]



And did you see that dress she had on that night lately? It was to about here and it had a big piece missing here and there. I saw that yeah. And she’s not skinny enough to wear that. Would she not use fake tan? You might as well go out snow white. (LCIE)

(4.22) [Context: Extended family chatting. = female (age 47); = male (aged 53); = female (age 38). Speakers are numbered according to BNC file metadata. - indicates a false start on the part of a speaker.]





Key, that, when we first bo- when we first bought our car through that Scottis- that bloody bank. Scottish Amicable. Scottish Amicable. Like Widows. They’re always ringing up. They ring up at seven and eight o’clock at night. Yeah. Asking us whether we want to borrow some money. (Spoken BNC1994: File KB1)

In extract 4.20, mentions that bike, in extract 4.21 mentions that dress and in extract 4.22 refers to that bloody bank. On all three occasions, these marked uses of the distal demonstrative that seem to signal a sense of disapproval on the speaker’s part. This is further emphasised by the presence of the taboo item bloody in extract

REFERENCE

4.22. Lakoff (1974) calls this use of demonstratives emotional deixis. She claims that the emotional deictic that, as in extracts 4.20 to 4.22, where the subject alluded to belongs to neither the speaker nor to the addressee, ‘appears to establish emotional solidarity between the two by implying that both participants in the conversation share the same views toward the subject of the discussion’ (1974: 352). Both Argaman (2007) and Rühlemann (2007) note that little study has been devoted to empathetic deixis. Indeed, Rühlemann (2007: 222) concludes that ‘empirical research based on corpus data might potentially advance the already existing knowledge on this intriguing type of deixis substantially’. For example, Rühlemann and Clancy (2018) have argued that the choice of was over were, or vice versa, in as-if clauses (e.g. She treats me as if I was/were a stranger) as a case of empathetic deixis. Using the COCA corpus, they maintain that when speakers choose was as in She treats me as if I was a stranger, they are indicating closer proximity to the factuality of the comparison, and, by extension, closer proximity to their deictic centre, than when the speaker chooses were as in She treats me as if I were a stranger. This choice, therefore, may reflect a case of empathetic deixis.

4.5 REFERENCE IN USE: ‘THAT’ AND SPEAKER ATTITUDES Although some corpus pragmatic studies (see e.g. Rühlemann and Clancy 2018) are emerging from the field, empathetic deixis remains a much under-researched area in general, at least in comparison to the other more traditional categories of person, place and time. In order to further investigate the phenomenon of empathetic deixis, we decided to conduct an investigation into the use of that in two corpora – the first of these is the spoken component of the BNC Baby (see Appendix). The BNC Baby is directly comparable in size to LCIE, the second corpus we employ in the investigation of the behaviour of that. The use of that is very frequent in spoken language in general; therefore we limited our search to nouns that directly co-occur with that, which, we reasoned, might allow for the further examination of the notion of degree of emotional attachment and solidarity displayed by the use of that as a determiner, as evidenced in extracts 4.20 to 4.22. Our first step was to generate concordance lines for that and then sort those lines one item to the right (1R; see Chapter 1). Table 4.5 presents the first 15 nouns 1R of that in alphabetical order. That clauses (e.g. that book from the library or that area near the river) have not been excluded from the frequency counts; however, Table 4.5 offers a candidate list that allows the researcher to identify viable frequency patterns for the analysis that follows. Table 4.5 has a number of similarities, among them that that occurs frequently in noun phrase patterns, such as that day, that night and that money in both corpora. However, what intrigued us the most was the frequent occurrence of items used to refer to both men and women in both corpora (items shaded and in bold in Table 4.5). The BNC Baby contains the patterns that bloke (14 occurrences), that girl (15 occurrences), that lady (19 occurrences) and that man (25 occurrences). Similarly, LCIE features the patterns that fella (25 occurrences), that girl (17 occurrences), that guy (19 occurrences) and that man (18 occurrences). Extracts 4.20 to 4.22 demonstrate the use of that and a connection to a negative attitude either embodied by the shared knowledge surrounding some of the occurrences

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REFERENCE Table 4.5 Frequency of occurrence of nouns (in alphabetical order) 1R of that in the BNC Baby and LCIE N

BNC Baby

Frequency

LCIE

Frequency

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

area bloke book car corner day door film girl hand lady letter man money night

14 13 11 21 13 16 18 16 15 10 19 11 25 15 16

day fella girl guy house man money morning night part point place road side thing

47 25 17 19 38 18 14 10 34 14 15 16 16 19 59

of an expression itself, such as that bike (extract 4.20) or that bloody bank (extract 4.22), or evident from the surrounding co-text, as in that dress (extract 4.21). Our aim here, then, is to ascertain the attitudes or evaluations present when interlocutors make reference to people using that. In order to examine this, concordance lines for the occurrences of that bloke in the BNC Baby and that fella in LCIE were generated for comparative purposes using AntConc (Anthony, 2019). Overall, bloke occurs on 87 occasions in total in the BNC Baby in contrast to 6 occurrences in LCIE (there is one instance of the use of that bloke in LCIE). In contrast, fella occurs on 230 occasions in total in LCIE as opposed to 23 instances of fella in the BNC Baby (that fella accounts for four of these). Therefore, the choice of fella or bloke reflects a varietal difference between British and Irish English at a lexical level and this raises the possibility of a connection between lexical choice and variation at a pragmatic level when this choice is associated with the determiner that. Figure 4.1 illustrates the concordance lines for the occurrences of that bloke in the BNC Baby and Figure 4.2 represents the instances of that fella in LCIE. In Figure 4.1, line 9 is struck through, as it represents a duplicate of line 8 and this has been reflected in

Figure 4.1 Concordance lines for that bloke in the BNC Baby

REFERENCE

the counts in Table 4.5. This illustrates one of the strengths of corpus research where the results of one corpus tool can be checked against those of another. This is important, as raw frequency counts may include duplicate items in the results generated.4 In addition, since the Spoken BNC1994, of which the BNC Baby is a constituent part, is part-of-speech (POS) tagged to aid readability of the concordance lines, the tags have been hidden using the ‘Hide tags’ option in AntConc. Obviously, not all of the instances of that bloke in Figure 4.1 are deictic in nature; for example, in line 2, that bloke is a cataphoric reference to Richard. In order to ascertain whether the use of that bloke is connected to empathetic deixis, we need to determine whether or not we can connect that bloke with shared views, attitudes or emotions between the interlocutors. We can do this by examining the environment, or co-text, in which that bloke appears, and determining whether it is a positive or negative one. In terms of a negative environment, in line 10, that bloke collocates with died and in line 13 with virus. If we study the extended co-text by clicking on the concordance lines and viewing the transcripts, we can also see negative environments in other examples such as in line 12, the transcript for which is contained in extract 4.23. (4.23) [Context: Husband and wife chatting. = male (age 29); = female (age 30).]









It’s like that er truck driver that came into your place when er you and er that bloke that used to there. And a he came in there and er for his glasses and er old was having a headache actually everything Oh yeah. And he, he was a er said he was nearly enough, near enough blind! Mm! And here he is driving trucks around the countryside! Did he? Yeah. And he persisted as well! Yeah, he didn’t need glasses for driving! You know er! The old, old ones are the worst, I tell you! Yeah. (BNC Baby: File KD3)

In extract 4.23, a husband and wife are chatting, and therefore we can reasonably expect that they share a high degree of shared knowledge. Their use of that bloke refers to a truck driver with bad eyesight who drives around the countryside while not wearing glasses, an understandably undesirable scenario. Similarly, we can examine the environment in which that fella occurs in the concordance lines from LCIE in Figure 4.2. Figure 4.2 represents a larger sample of concordance lines than that shown in Figure 4.1, but, again, not all of the occurrences of that fella are used deictically. For example, in line 11, that fella is, again, a cataphoric reference to Jim what’s his name. Similarly, in line 9, I don’t trust that fella is a cataphoric reference to That Dec (reference to That Dec does,

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Figure 4.2 Concordance lines for that fella in LCIE

however, appear to also carry negative connotations). Interestingly, there are a number of deictic references that, although they demonstrate a shared knowledge, are also indicative of negative shared views, attitudes or emotions. For example, he’s an awful dickhead that fella (line 4); that fella ran into the back of her car (line 5); Like what the hell is that fella saying like? (line 6); that fella’ll start doing tommers5 (10); she wouldn’t be still hankering after that fella (12); have no faith in that fella (19); that fella from Limerick he got killed (22); he was put off the road for ten years that fella (23); and she says that fella is prowling around all the time (25). Each of these mentions has negative connotations and, key to the notion of empathetic deixis is how a speaker manipulates his or her proximity to their deictic centre through the indexing of the referent (Rühlemann and Clancy, 2018). Figures 4.1 and 4.2 demonstrate a possible pattern between the use of that + fella and associated negatively evaluated behaviour in Irish English spoken discourse. Through the choice of the distal determiner that by the speaker, the referent is placed at a distance, thereby strengthening this negative evaluation.

TASK 4.9 THAT + NOUN IN COCA With the findings from Section 4.5 in mind, examine Table 4.6 which presents the top 20 most frequent that + noun patterns in the spoken component of the COCA corpus (these results were generated using the search that _nn*). Some of the results (e.g. that students or that women) are obviously part of a that clause. Some of the results (e.g. that kind, that sort or that case) are most likely part of larger multi-word units. However, many of the patterns are similar to those evident in Table 4.5, such as that + day, night or money.

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1) 2)

Use the online COCA interface to analyse a downsample of 100 occurrences from one of the patterns from Table 4.6. Determine whether or not there might be an empathetic deictic dimension to the use of the item you have sampled.

Table 4.6 Top 20 frequency results for that + noun (that _nn*) N

FORM

FREQUENCY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

that way that people that time that night that day that kind that point that moment that students that women that year that question that part that money that person that morning that sort that children that information that case

27,985 27,017 23,932 18,130 17,479 15,544 13,623 8801 7650 7112 6966 5737 5523 5404 5356 5305 4716 4373 4328 4293

4.6

CONCLUSION

In this chapter we have looked, through the lens of corpus pragmatics, at the different types of reference and focused, in the main, on exophoric reference in the form of deixis. Throughout, we have drawn upon corpus data to illustrate the ubiquity, and, therefore, the importance of referential items to the study of language in use in general. This has demonstrated the as yet largely untapped potential of corpus linguistics for the analysis of referential systems, particularly in relation to categories such as discourse and empathetic deixis. Corpora allow us to systematically recall all potentially deictic items and, through more in-depth analyses of concordance lines and source files, to narrow down the relevant items for further categorisation and analysis. With this boon comes the drawback that, at times, the research may struggle to recontextualise the data, especially in the case of large corpora, as discussed in Chapters 2 and 3. It has been argued (see e.g. Vaughan and Clancy, 2013) that small, specialised corpora can be especially useful in addressing this

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(see Chapter 8). However, from a methodological point of view, the increasing amount of metadata available with larger corpora, such as the Spoken BNC2014, which has been used throughout this chapter, means that the researcher has access to a variety of contextual information necessary for the iterative analysis of a broad range of referential items. As discussed in Chapter 3, the availability of metadata for spoken corpora greatly facilitates corpus pragmatics research.

4.7

FURTHER READING

Botley, S. and T. McEnery, 2001. ‘Demonstratives in English: A corpus-based study.’ Journal of English Linguistics, 29(1), 7–33. This corpus-based study offers an analysis of demonstrative pronouns (this, that, these and those) based on an exploration of three 100,000-word corpora. The paper explores a variety of questions commonly associated with demonstratives, including their function and distribution across genres. Rühlemann, C., 2007. Conversation in Context: A Corpus-driven Approach. London: Continuum. This volume places deixis at the core of the analysis of the spoken component of the British National Corpus. In addition to providing ‘traditional’ deictic analyses of person, place and time deixis (see in particular ch. 4), Rühlemann also integrates other features of conversation, such as speech-reporting, discourse markers and vocatives and terms of address into the deictic system. Rühlemann, C. and B. Clancy, 2018. Corpus linguistics and pragmatics. In C. Ilie and N. Norrick (eds), Pragmatics and its Interfaces. Amsterdam: John Benjamins, pp. 241–266. This chapter integrates the qualitative methodology typical of pragmatics with the quantitative methodology predominant in corpus linguistics. To illustrate, the choice between indicative was and subjunctive were in as-if clauses is examined in COCA. This was/ were choice is considered in relation to empathetic deixis, a realm which remains much under-researched in pragmatics. Vaughan, E. and B. Clancy, 2013. ‘Small corpora and pragmatics.’ Yearbook of Corpus Linguistics and Pragmatics, 1, 53–73. The authors explore the manifold advantages of using small, domain-specific corpora in pragmatic research, among them the constant interpretative dialectic between text and context and the fact that the results generated by these corpora, especially when looking at high frequency items, are manageable, even for the novice researcher. The suitability of corpora in the 20,000 to 50,000-word range for corpus pragmatic study is illustrated by a contrastive analysis of the occurrences of the pronoun we in C-MELT (see Appendix) and a corpus of family discourse. The results demonstrate the complexity of we with regard to personal and social deixis.

NOTES 1

Ironically, the metadata for the Spoken BNC2014 provides us with the date of recording so that we can actually determine when today and tomorrow were, but the point is that this cannot be done purely by reference to the immediate context.

REFERENCE 2 3 4

5

This example is taken from Halliday and Hasan (1976: 39). For more information about TravCorp see Clancy (2011). This struck-through concordance line has been included for illustrative purposes. The line can be deleted from the list in AntConc by holding down the ‘Ctrl’ key, clicking on the concordance line and pressing the ‘Delete’ key. Tommers is an Irish English slang word for paid work that people do when they are also in receipt of government payment for being unemployed. This practice is illegal in Ireland.

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CHAPTER 5

Politeness

5.1

LINGUISTIC POLITENESS

In this chapter we set out to explore some of the most influential theories of linguistic politeness that are essential reading for those who wish to research this phenomenon. However, before doing so, it is worth taking time to examine our own intuitions about politeness.

TASK 5.1 POLITE LANGUAGE What words do you most commonly associate with politeness? In what situations do you most frequently/least frequently use them? When we think about politeness, what do we consider polite language behaviour to be? For example, do we consider terms like sir or madam, which show respect towards a person, polite? Is using fixed expressions like please, thank you, excuse me or sorry polite, socially acceptable behaviour? Or is language which we use to avoid sounding too direct such as Would you mind awfully if I asked you to move? an example of language which might be considered ‘distancing’ or ‘hypocritical’? If someone told you to Have a nice day, how would that make you feel? We are all, linguists and non-linguists alike, acutely aware of the phenomenon of politeness and its implications for our everyday language use. Take, for example, extract 5.1 from the Spoken BNC2014. (5.1) [Context: = female (age 36); = male (age 36).]



a lot a lot of the Chinese told me to stop saying thank you so much mm UNCLEARWORD erm tut yeah I say thank you to them and they’re like oh no no more thank yous

POLITENESS















I say it like every second sentence mm yeah you order a cup of coffee in a shop mm in a café cos we we think that’s a way of showing of respect and you say thank you and they’d say mm it’s my job yeah why would you say thank you to me? yeah I’m not doing you a favour I’m doing my job yeah mm yeah we’re extreme and it’s actually quite annoying it is annoying mm far too annoying it’s er it’s just I don’t know how I think we must’ve colonised the world by being like super polite maybe people just lower their defences a bit and then yeah and then we just build some railway lines and er mm mm I mean how did we colonise the world by being so polite mm well we had guns excuse me do you do you mind if I? oh sorry I’ve eaten that pasta a bit quick would you mind if I stick a flag here and call it? (Spoken BNC2014: Text S7FU)

In extract 5.1, the speakers equate politeness with a particular form thank you and a particular behaviour showing respect. Ironically, the speakers are discussing the overuse of thank you in service encounters, specifically in a café setting. This is ironic, as contemporary linguistic politeness literature informs us that service encounters, at least when the attention is focused on the business at hand, are where forms traditionally associated with politeness such as please and thank you most frequently occur (see e.g. House, 1988; Wichmann, 2005; Binchy, 2005). ’s utterance a lot of the Chinese told me to stop saying thank you so much also demonstrates an awareness of cross-cultural differences regarding politeness (see e.g. Sifianou and Blitvich, 2017). Applying corpus linguistic techniques in order to compare the use of polite language in different cultures yields some interesting results, but also raises the question of how these results might be interpreted.

TASK 5.2

THE USE OF PLEASE

Examine the frequency results for the occurrences of please (per million words) in the Spoken BNC2014 and the spoken component of the ICE-Ireland corpus in Table 5.1.

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100

POLITENESS

1) 2)

3)

Consider the differing results for please. What might explain the difference? Does it mean that British people are more polite than Irish people? ICE-Ireland was collected from the early 1990s (from both Northern Ireland and the Republic of Ireland), whereas the Spoken BNC2014 was collected between the years 2012 and 2016. What might this tell us about the frequency differences in the use of please? Can you think of any ways in which corpus tools could help to further investigate the difference between the results? (see our discussion of cheers in Chapter 7).

Table 5.1 Frequency counts per million words for the occurrence of please in Spoken BNC2014 and ICE-Ireland

please

Spoken BNC2014

ICE-Ireland (Spoken)

244.51

116.2

In addition, when we consider politeness, we seem to have an instinctive understanding of what constitutes rude or impolite language or behaviour, as illustrated in extract 5.2. (5.2) [Context: = female (age 27); = female (age 32).]





I was in the library the other day and there were people just having a full-blown row (.) I thought they were on the phone but they were actually sitting next to each other (.) I think they were you are meant to be quiet in the library I was just like yeah I wouldn’t want to do that anywhere but in the library where everyone else is being quiet? and also it’s just rude in the library isn’t it? (Spoken BNC2014: Text S3RN)

In extract 5.2, the speakers equate impoliteness with a form of behaviour – specifically that you are required to be quiet when in the library, again, perhaps, in order to show respect to others (see extract 5.1). These everyday notions of polite language use and behaviour are, as Terkourafi (2011: 160) puts it, at a ‘disconnect’ from the linguistic study of politeness and impoliteness. Some theories of linguistic politeness do not examine these everyday understandings but instead concentrate on other linguistic features and strategies (see e.g. Brown and Levinson’s theory in Section 5.2). By doing so, politeness theorists seem to suggest that an everyday view of politeness does not provide the linguist with the full picture – therefore, in addition to looking at the forms that politeness takes and the behaviour associated with it, the how and where we do politeness, we also need to take into account issues such as when and why linguistic politeness is achieved.

POLITENESS

TASK 5.3 POLITE LANGUAGE USE IN DIFFERENT SITUATIONS Consider how you make a polite request in different situations. 1) 2)

How do you make a request in your workplace, as opposed to at your family dinner table? Consider the person to whom you are making the request. How might the language of the request vary depending on whether the request is to your boss, your colleague, your parent, your sibling or your child?

In order to consider the answers to some of the questions raised thus far, it is insightful to consider the distinction made by linguists between first order politeness, or politeness1, and second order politeness, or politeness2.

Politeness1 versus politeness2 Politeness1 is used to refer to folk, lay or commonsense interpretations of politeness. This is the politeness or impoliteness evident in extracts 5.1 and 5.2 when people seek to characterise polite or impolite language use. Inevitably, expressions such as please, thank you or sorry, those regarded as considerate or respectful, are mentioned. However, we also encounter people who consider polite language to be obsequious, dishonest or unfeeling; a case in point is the expression Have a nice day, seemingly an integral part of polite language usage in the US but sometimes viewed as ‘unfeeling’ in other countries (it should be stressed that this reflects a cross-cultural situation). Therefore, interpretations of what constitutes polite language and behaviour are inherently evaluative and differ from one culture to another, one group of speakers to another and even one individual speaker to another. Linguists such as Watts (2003) (see Section 5.4) argue that our own interpretation of what constitutes polite language forms the basis for our evaluation of how polite, or impolite, we consider other people to be. On the other hand, politeness2 is concerned with politeness as a technical term used by linguistic researchers when studying spoken and written language, such as when using Brown and Levinson’s model (see Section 5.2). We can illustrate the distinction between politeness1 and politeness2 by examining extract 5.3 of family talk. (5.3) [Context: The family is talking about Christmas. = male (age 24); = female (mother); = male (age 14); = female (age 22). Feck off is often used in Irish English as a polite expletive.]

It’s religious it’s the birth of Jesus and we all should be aware of that. [laughs]

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POLITENESS

It’s nothing got to do with presents. [  Shut up.  [laughs] Come here Connor shut up. It’s nothing to do with presents and happiness it’s got to do with celebrating the birth of Jesus. Okay so we won’t give you any presents. [

We’re not allowed be happy because we are Catholic. [  Connor shut up. [

You’re having no presents so are you? I’ll say a prayer for you. We are Catholic. We are not allowed be happy. It’s all about the birth of Jesus. [laughs] That’s okay so I’ll get you a novena said for Christmas. ☼ [shouts] Good. Feck off. (LCIE)

When we examine this extract closely, we can see that , Connor, is told to shut up three times (marked by ) and , Connor’s mother, is shouted at by (marked by ☼), all of which could be construed as rude behaviour. There are also four speaker overlaps (marked by [ ) as the participants attempt to seize control of the speaker turn. None of these features are considered traditionally polite; indeed, in many contexts, telling someone to shut up or talking over a speaker would be considered impolite or rude. However, if we further explore the extract, we can see the presence of laughter and that the conversation appears to proceed without any notable conflict taking place, indicating that the speakers remain unaffected by the apparent impoliteness. This raises a key question for researchers of linguistic politeness: do we label the family polite or impolite? As we will see, in terms of politeness2, theoretically or objectively at least, according to Brown and Levinson, the speakers are not being polite and this is signalled by, for example, the absence of politeness strategies such as indirectness or hedging (see Section 5.2). However, politeness1, due to its evaluative nature, allows the researcher to consider that this family represent an example of negotiated politeness, where one family have constructed a level of politeness which they have evaluated as acceptable for use in this particular context (see Section 5.4). The question of what constitutes polite and, indeed, impolite, language usage is one of the most researched topics in contemporary linguistics. This chapter examines three distinct seminal theories (or models) of politeness, and demonstrates key features of these models in context. 1. 2. 3.

The face-saving approach to politeness (Section 5.2); Impoliteness (Section 5.3); Discursive politeness (Section 5.4).

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5.2

THE FACE-SAVING APPROACH TO POLITENESS

Perhaps the most famous and most remarked-upon (both positively and negatively) study of politeness is Brown and Levinson’s ([1978] 1987) study. Brown and Levinson’s approach to the study of politeness is based around the concept of face-saving. Brown and Levinson define politeness as a complex system for softening face-threatening behaviour. They view politeness as a phenomenon that can be codified, thereby enabling the linguist to measure politeness quantitatively. This can be done effectively using corpus software. Much of what is written about face in politeness theory revolves around the work of Goffman (1956, 1959, 1967), who employed his background in sociology in order to formulate what has become one of the key notions in politeness research. Drawing upon the work of Durkheim (1915), Goffman developed a concept of face inextricably bound to English idiomatic expressions such as ‘to lose face’; that is, to be embarrassed or humiliated, and ‘to save face’; that is, to prevent damage to one’s reputation or the loss of people’s respect for the speaker. Goffman (1967: 5) defined face as ‘the positive social value a person effectively claims for [him- or herself]’. In order to maintain this positive self-image, a person invests emotional energy in the face they present to others which requires a degree of effort on their part, a process Goffman refers to as face-work. For Brown and Levinson, face consists of two related aspects; positive face and negative face. For both of these aspects of face our essential needs are the same – we want people to like us – and this impacts upon our linguistic behaviour. From the point of view of positive face, we want to receive acknowledgement from others that we are liked, accepted as part of a group and that our wants are understood by them. In the case of negative face, we want to be independent and not have our actions imposed upon by others. According to Brown and Levinson, these two basic face needs are satisfied by a variety of politeness strategies. In our everyday interactions, people behave as if our face needs will be respected by others; however, despite this assumption, people sometimes engage in actions that threaten both positive and/or negative face, what Brown and Levinson refer to as Face Threatening Acts.

Face threatening acts (FTAs) When politeness researchers refer to an FTA, they refer to a communicative act performed by the speaker that does not respect either the hearer’s need for space (negative face) or their desire for their self-image to be upheld (positive face), or both. Two examples of an FTA (indicated by ) can be seen in extract 5.4, which features two siblings discussing an incident which occurred involving a colleague. (5.4) [Context: = female (age 23); = female (age 16).] …that was the year that guy was working there and got caught stealing the drink and they thought it was Kevin stealing it. I was there. What about him anyway?

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 

Oh you came after. I remember Kevin. I knew him like. I was up in the rooms and he often came up there. I knew Kevin well. No because the summer I was working there you weren’t working there. Mary I know for a fact I was working there when he was working there. (LCIE)

is telling about an incident of mistaken identity involving Kevin, a colleague in their workplace, most likely in a bar. claims that there is no need to tell her the story as she was familiar with Kevin and the event that occurred and worked with him; however, is apparently unwilling to accept this. disagrees with with the utterance, No because the summer I was working there you weren’t working there. According to Brown and Levinson, this constitutes an unmitigated FTA on ’s positive face because is refusing to satisfy ’s (the hearer) desire to be right (see sub-section on positive politeness, p. 103) and refusing to agree. This, in turn, triggers another FTA in response to . Brown and Levinson view politeness as a complex system for softening FTAs. If an FTA has to be performed, then the speaker has five communicative choices – bald on record, positive politeness, negative politeness, off record and don’t perform the FTA (these choices form what they refer to as superstrategies) – in order to accomplish this, as illustrated in Figure 5.1.

Baldly (without redress) Posive politeness

On record

Perform the FTA

Baldly (with redress)

Off record

Negave politeness

Don’t perform the FTA

Figure 5.1 Brown and Levinson’s (1987) strategies for performing FTAs

The first decision a speaker has to make is whether or not to perform the FTA; in other words, do you speak or do you hold your tongue? Should you choose the latter option, communication can be achieved by gestures like pointing a finger (although there may be situations where this may still constitute an FTA!) or nodding your head. On the other hand, the speaker can decide to say something, in which case they say something off record or on record. Performing an FTA off record involves strategies such as metaphor, irony, rhetorical

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questions, understatements or hints. Alternatively, the speaker can go on record, and this requires the speaker to make a strategic choice either to perform the FTA with or without redress. Redress, Brown and Levinson (1987) maintain, is action a speaker takes by modifying their utterance in some way in order to take the hearer’s face into account; in other words, redress involves the use of mitigation (mitigation will be explored further in relation to positive and negative politeness). Another option available to a speaker is to go on record without down-toning or mitigating their utterance, what Brown and Levinson refer to as a bald FTA. In extract 5.5, which features a university laboratory session from the MICASE corpus, we can see two requests performed baldly without redress (in bold). (5.5) [Context: Biopsychology lab session; S1 = instructor; all other speakers are students.] S7: S1: S1: SS: S1: SU-m: SU-m: SU-m: S1: SU-f: S1: SU-m: S1:

what did, what did you say with the gloves? uh, put the gloves in the plastic garbage bag. Actually it’s due on Monday, alright, yeah. when is your critique due? Monday. Monday. Thursday. Monday? Monday I thought it was Thursday. critique. I thought it was Thursday. the the outline was due on Thursday. wait wait wait how we gonna get ’em to you? give ‘em to me in class, y’all are planning to… (MICASE: Transcript LAB500SU044)

Although in the form of imperatives, both constitute requests on the part of the instructor. There are no markers of linguistic mitigation present. In this case, S1 may be relying on the relationship between teacher and student to mitigate the imperatives; however, in most cases, in choosing the bald on record option, the speaker is opting for the most face-threatening route. The final choice available to a speaker is to choose to redress the FTA using either a positive or a negative politeness strategy and it is to these strategies that our attention now turns.

Positive politeness As we have already stated, positive face requires that the individual’s positive self-image be respected in everyday interaction with others. In order to achieve this, Brown and Levinson (1987) claim that conversational participants often work to minimise the social distance between them. Positive face is saved by conversational participants co-constructing a feeling of closeness and fostering the belief that all speakers are working towards a common

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goal. As we can see in Table 5.2, Brown and Levinson list 15 strategies a speaker can employ in order to avoid threatening the addressee’s positive face. Table 5.2 15 strategies Brown and Levinson list in order to avoid threatening positive face Strategy Pay attention to a hearer’s interests, wants, needs or goods Exaggerate interest in, approval of or sympathy with a hearer Intensify interest and involve the hearer (use involvement devices such as questions tags, direct quotes, historic present) Use in-group identity markers (solidarity address terms, dialect features, slang, contraction) Seek agreement/make small talk Avoid disagreement (token agreement, pseudo-agreement, white lies) Find common ground (change to the hearer’s deictic centre; see Chapter 4) Joke Assert or imply knowledge of and concern for a hearer’s wants Offer, promise Be optimistic Use inclusive ‘we’ forms Give (or ask for) reasons Assume or assert reciprocity Give gifts

Positive politeness behaviour is often compared to that which is characteristic of interaction in an intimate setting, such as between husband and wife or within family discourse (see Blum-Kulka, 1997; Clancy, 2005). Brown and Levinson also maintain that because positive politeness can be associated with intimate language use it can be used as a ‘social accelerator’ (1987: 103), where, for example, strangers, in using markers of positive politeness, can indicate that they want to form a closer bond. Extract 5.6 features English language teachers in the workplace ruing their lack of status within their organisation, and is a good example of a number of positive politeness strategies in action in that, as we can see, the teachers exploit these strategies to build on a sense of collegiality. (5.6) [Context: = male (thirties); = female (thirties); = male (twenties).] Yes but we don’t have the power to throw anybody out what I mean is we haven’t been given that kind of clout we don’t have that status in the university if they fail calculus they’re out if they fail English they just continue. Yeah. So [laughs] so I think we should just accept that our horrible lowly status. [General laughter] We’re the poor cousins. Yeah and we know that. (C-MELT)

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The echoing of the inclusive form we, in bold, in the extract creates an ‘in-group’ and fosters teachers’ feelings of solidarity and common ground (for more on the use of we see Chapter 4). The atmosphere is a joking one, signalled by the presence of humour, and this adds further to the we’re all in this together dynamic (see Vaughan, 2007: 185), strengthening the sense of collegiality. It is also interesting to note, especially in comparing positive politeness with negative politeness in the workplace, that the teachers’ boss is not present at this meeting. One of the most common positive politeness strategies, in-group identity markers, such as nicknames, falls under the banner of terms of address, which are ‘traditionally one of the central topics in politeness research’ (Eelen, 2001: 38). Address terms offer methodological advantages to researchers of linguistic politeness in that they can be clearly and unambiguously identified within a text. Address terms can generally be subdivided into seven semantic categories, as outlined in Figure 5.2. However, as Figure 5.2 also demonstrates, not all address terms function as positive politeness markers – as the categories move from the more informal such as nicknames and first name familiarised to the more formal such as honorifics, the politeness strategy changes from positive to negative politeness. Level of formality

Category

Example

Politeness strategy

Informal

Endearments Family terms Familiarisers First names familiarised Full first names Title and surname

Positive politeness

Formal

Honorifics

honey, baby, love Mammy, Daddy, son mate, man, folks Brad, Jen Bradley, Jennifer Mr Holmes, Dr Watson, Professor Moriarty sir, ma’am, your honour

Negative politeness

Figure 5.2 The semantic categorisation of in-group terms of address (adapted from Leech, 1999)

In positive politeness, some address terms function to mitigate or down tone utterances. Mitigation of an FTA, also referred to as downtoning or softening in politeness literature, can involve the use of politeness markers such as terms of address in order to reduce the force of an utterance. Take extract 5.7: here the speakers on a radio phone-in are discussing marital breakdown when they get into an argument. (5.7) [Context: = caller; = presenter.]



. . . but as time goes on it’s cool these days ah and pardon me for using that word because it’s a slang word I don’t like. But as they say it’s cool to say “I’m separated”. It’s attractive. Is it? It’s attractive to ah men and women.

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Well now I’ve interviewed a fair number of separated people down through the years and I don’t think anybody ever found it cool or a great experience. I mean there was an awful lot of pain and that kind of+ How long+ +thing. +ago is that Marian? Well on and off over the years. (LCIE)

We can see that the presenter contradicts the caller and the caller responds with a challenge. The addition of the term of address in the form of a full first name (in bold) by the caller is crucial in mitigating the FTA posed by the challenge. In using it the caller appeals to the presenter as an equal and, in a sense, reiterates their common goal of discussion rather than argument, thus re-establishing the ‘pseudo-intimacy’ of the context (O’Keeffe, 2006). Although the address term functions as a marker of positive politeness in extract 5.7, as already mentioned, certain address term categories such as honorifics function in the realm of negative politeness, the focus of the following section. This illustrates a feature of Brown and Levinson’s theory – that, depending on the context, strategies such as address terms can be used to soften threats to positive or negative face (we also deal with address terms in Chapters 4 and 7).

TASK 5.4 POSITIVE POLITENESS STRATEGIES Extract 5.8 is taken from the Switchboard component of the Open American National Corpus (OANC) (see Appendix). Read the extract and work out how many distinct positive politeness strategies are being used by the speakers. (5.8)







could you hang on one minute Jim thank you. yes ma’am. I am so sorry to keep you on hold are you at work okay I am too. no problem yes yeah um I think what you have is the way the. um. the justice system works is they bend over backwards trying to protect the guilty so many things in their back pardon yes I know. oh it’s insane it’s insane. my wife participated in a jury trial several years back wherein the individual after it was over and they had came up with the maximum sentence. yes yes. in the jury form they found out that uh the gentleman involved had a long history of the same type offense which was theft of uh property. right uh-huh oh yes.

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> I promise I will promise (BNC Spoken 2014: File SDAB)

TASK 6.2 FELICITY CONDITIONS FOR PROMISES In Figure 6.3, we have begun the process of distinguishing the felicity conditions for promises by identifying the propositional content and the sincerity condition. 1)

What are the preparatory and essential conditions that must be met in order to distinguish an act as a promise? Felicity conditions for promises [A = act, H = hearer, S = speaker] Propositional content:

Future A of S

Preparatory:

1. 2.

Sincerity:

S intends to do A

Essential:

Figure 6.3 Felicity conditions for promises (adapted from Culpeper and Haugh, 2014)

Felicity conditions differ depending on the speech act being performed, and subtle changes in any of the four categories may generate a new illocutionary utterance force. If any of the conditions for a specific speech act are not being met, then the utterance is infelicitous. In the example of a request, if the speaker does not want the hearer to do the action that is being requested, then the utterance is not successful as a request. The emphasis

SPEECH ACTS

thus shifts from the notion of sentences as being either true or false, to the notion of utterances being felicitous or infelicitous. It is worth noting in this context that felicity conditions also apply to constatives.

Speech act classification Following the early revisions in his theory, Austin, and later Searle (1976), turned their attention to the identification of different kinds of speech act function in language. Searle’s (1976) taxonomy of speech acts is based entirely on felicity conditions. He establishes a number of meta-categories of speech acts that follow patterns of felicity conditions. Searle (1976) suggests the following classification of basic acts: 1 2 3 4 5

Representatives, which commit the speaker to the truth of the expressed proposition (paradigm cases: asserting, concluding, etc.); Directives, which are attempts by the speaker to get the addressee to do something (paradigm cases: requesting, questioning, etc.); Commissives, which commit the speaker to some future course of action (paradigm cases: promising, threatening, offering); Expressives, which express a psychological state (paradigm cases: thanking, apologising, welcoming, congratulating); Declarations, which effect immediate changes in the institutional state of affairs and which tend to rely on elaborate extra-linguistic institutions (paradigm cases: excommunicating, declaring war, christening, firing from employment).

There are, however, a number of issues that arise from the classification model outlined by Searle. For example, there is a degree of overlap between different meta-categories. We will explain this in more detail when it comes to the speech act of making suggestions. Table 6.1 illustrates the results for the frequency of occurrence of Searle’s (1976) speech acts across three different speech situations in the SPICE-Ireland corpus (see Appendix): BRN = broadcast news, CLD = classroom discourse and FTF = face-to-face conversation. These counts were generated simply by searching for each of the tags, , , , and (these tags represent the speech acts representatives, directives, commissives, expressives and declarations respectively) using corpus concordancing software. The results have been normalised per 10,000 words. As Table 6.1 highlights, the occurrence of representatives, directives and expressives is notably more frequent in the face-to-face component of the corpus than in either the broadcast news or classroom discourse components. Table 6.1 Distribution of speech acts in three speech situations in SPICE-Ireland (normalised per 10,000 words) Speech situation







BRN (broadcast news) CLD (classroom discourse) FTF (conversation)

996.5 920 1670.7

44 391.1 629.1

7 22.8 27.3

14.5 31.7 55.4

2 0.5 0.4

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TASK 6.3 SPEECH ACT CLASSIFICATION Consider Table 6.1: 1)

2)

With the exception of declaratives, why might the other speech act categories be more frequent in face-to-face conversation than in either classroom discourse or broadcast news? What characteristics of the speech situation classroom discourse might make it the ‘middle ground’, in terms of speech act frequency, between broadcast news and face-to-face conversation (see also Chapter 8)?

Direct and indirect speech acts The notion of the indirectness of a speech act is often related to the grammatical form of a sentence. It occurs when the locution is apparently at odds with the illocution of an utterance. When the illocutionary force is in line with the linguistic form, we can expect the following patterns: declarative = assertion imperative = order/request interrogative = question Both Austin and Searle, however, note that most utterances are indirect; that is, the illocutionary force of many utterances is not reflected in the sentence form. Nattinger and DeCarrico (1992) distinguish between conventional and non-conventional indirect speech acts. Conventional indirect speech acts can be described in terms of the recurrent phrases used to introduce them. These speech acts (e.g. Can you pass me the water?) are immediately recognised as being a request rather than a question about the ability of the hearer to pass the water. The form a request takes is often motivated by the speaker’s wish to be polite (see Chapter 5). Leech’s (1983) scale of directness suggests that Could you…? is a more indirect request strategy than Can you…?, the past tense modal marking both increased tentativeness and politeness (see also Chapter 9 in the context of teaching pragmatics).

TASK 6.4 CAN YOU…? VERSUS COULD YOU…? Aijmer (1996) states that in addition to sentence type, felicity conditions and the type of subject (for example, the choice of you as subject in an interrogative rather than I in a declarative), other strategies are used to mark a request as polite or indirect. Using the examples of Can you…? and Could you…?, taken from LCIE in Figures 6.4 and 6.5, determine what other strategies, if any, are used in conjunction with Could you…? to mark it as a more indirect request strategy than Can you…?.

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Figure 6.4 20 concordance lines for Can you…? in LCIE (sorted 1L)

Figure 6.5 20 concordance lines for Could you…? in LCIE (sorted 1L)

However, there is no such correspondence between form and function with non-conventional indirect speech acts. Searle (1975: 61) gives the often-quoted example: X: Let’s go to the movies tonight. Y: I have to study for an exam. Searle argues that the meaning of Y’s response is understood on the basis of non-linguistic, extrinsic factors. It can potentially fulfil a range of different functions depending on the situational context and the immediate discourse co-text. Thus, the hearer infers the meaning of an utterance with reference to a set of inference procedures relating to his or her knowledge of the context in which an utterance is made. Searle also refers to primary and secondary illocutionary acts where in the example above the primary act is an indirect act functioning as a rejection of X’s suggestion. The secondary act is a direct act which provides information about Y’s planned activities which prevent him or her from taking X up on his or her suggestion of going to the movies.

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Indirect speech acts and the cooperative principle Indirectness in speech acts occurs when the locution (i.e. the words that are being used) does not fully determine the illocutionary force of the same utterance. The question of how we disambiguate this type of indirectness, or how we know what a speaker means when they are not saying it in a direct way, has led scholars to consider the processes we use to infer the meaning of indirect utterances. Such processes are often linked to a set of principles that form part of the background knowledge of the speaker and hearer (Grice, 1975; Leech, 1983; Levinson, 1983). Grice (1975) argues that a speaker’s words often convey more than the literal meaning of the words uttered. To interpret another speaker’s utterance, or to arrive from the surface meaning to the implied meaning, he puts forward the concept of conversational implicature. This process can only be successful if the listener cooperates. Hence Grice developed his cooperative principle (CP): that all people are essentially cooperative in order to achieve the purpose of being ‘maximally efficient’ (1989: 28) in interaction with others. In order to elaborate on the CP, Grice formulated four maxims: Quantity, Quality, Relation and Manner. 1 2 3 4

Quantity: Speakers should be as informative as necessary for listener comprehension, by ensuring that they are both succinct and explicit; Quality: Speakers should be truthful and not say anything for which they cannot provide adequate evidence or do not believe to be true; Relation: Speakers are assumed to be saying something that is relevant to what has been said before; Manner: Speakers should be clear and orderly in order to avoid ambiguity and obscurity.

In conversation, however, these maxims are often flouted, which is where the notion of implicature comes in. If we say something that apparently has no relation to the previous utterance, one or more of the maxims is flouted. However, since the cooperative principle works as a background guide for hearers and speakers, the hearer attaches meaning to the utterance in relation to obvious divergence from the maxim. Levinson (1983: 102) gives the following example: A: Where’s Bill? B: There’s a yellow VW outside Sue’s house. Speaker B’s response seems to be unrelated to speaker A’s utterance and, at a literal level, flouts the maxim of relevance and quantity. According to Grice, a hearer will interpret an utterance according to the cooperative principle at some level and infer meaning from the divergence from it. The hearer will thus infer that the fact that a yellow VW is outside Sue’s house must be relevant to the question he or she has asked, that Bill might drive a VW, and that he might therefore be in Sue’s house. In terms of conventionalised indirect speech acts, similar inference processes are proposed. The utterance Can you pass the salt?, then, will flout the maxim of relevance if it is taken literally, as the speaker is unlikely to be interested in the ability of the hearer to pass the salt. Therefore, an interpretation of a directive is inferred. However, it is more likely in the case of conventionalised indirect speech acts that

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they are not subject to the same elaborate inference procedures as non-conventionalised speech acts. We will return to this issue in the following section. There have been several criticisms levelled against this theory (see Levinson, 1983). First, there are other possible maxims than the four maxims that form the basis of the cooperative principle (see e.g. Leech’s (1983) politeness maxims). Since the cooperative principle is mainly based on language that is informative, the more interpersonal side of interaction remains under-represented by the maxims in the cooperative principle (see also Kasper, 1990). The Gricean maxims might also be considered to be rather vague in that it is difficult to determine the point at which a maxim is flouted due to, say, lack of information or relevance. The level of information that a speaker must provide before flouting the maxim of quantity, for example, is highly context specific. It is also specific to the culture in which the exchange takes place. A court hearing might require the speaker to provide more, and more relevant, information than a casual conversation between friends. The point at which maxims are seen to be flouted thus depends on the context in which the interaction takes place. Extract 6.4 taken from a telephone call to the National Health Service Corpus (NHS Direct) illustrates this point. (6.4) Advisor: Caller: Advisor: Caller: Advisor: Caller: Advisor: Caller:

Okay. How can I help then [name removed]? Right. I went to see the doctor yesterday. Mm. I’ve got erm what they’re calling a middle ear infection. Yeah. Erm it’s a new doctor cos I’ve erm recently moved into the area. Mhm. Erm when I’ve been before I’ve been prescribed something different. This time she’s given me antibiotics and basically the problem is that I’ve collected them I’m a bit worried about taking them cos I’m not actually sure if I might be pregnant and erm obviously I I know about you know not taking medication when you’re pregnant. So I just wanted to really check what I could do and really whether I should be taking antibiotics anyway with you know all these things about you’re not supposed to take them unless you really need them. (NHS Direct corpus)

The context of extract 6.4 is highly institutionalised and the quantity of information that is being provided is therefore extensive. The caller is not flouting the maxim of quantity in this context. However, if the context was a casual conversation between friends or colleagues this maxim might have been flouted. In extract 6.5, taken from the same corpus, we find that the caller is flouting the maxim of relevance to achieve a humorous effect. The reason for her call to the health service relates to her concern about taking a particular medication and the effects of that medication on a possible pregnancy. (6.5) Advisor: Right. And are you allergic to anything? Caller: Only cats. [laughs] If that’s any help.

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Advisor: Yeah. So what’s happened tonight? Why haven’t you started taking the [name of medication]? (NHS Direct corpus) The advisor’s question relates to possible allergies to prescription medications but the caller takes her question literally, and provides an answer that is not directly relevant (only cats). Flouting of maxims for humorous effect is not something that the advisor would expect in this context and she quickly returns to the main topic of the consultation. The dependency on context when it comes to assessing the degree to which speakers adhere to individual maxims, or flouting them as the case may be, adds to the difficulty of using Gricean maxims as a descriptive tool for unpacking indirectness in language.

Indirectness: semantics and pragmatics The processes underlying our understanding of indirectness discussed in this chapter thus far rely on inference procedures which are part of the hearer’s knowledge, i.e. the hearer infers the meaning of indirect utterances through reference of what is expected in different contexts. However, there are other points of departure to explain indirectness which relate particularly to conventionalised indirect speech acts. Morgan (1978) points out, for example, that a sentence such as Can you pass the salt? can be calculated according to inference procedures such as those outlined above, but this might not be what the hearer does when he or she hears this utterance. Instead, it triggers what he calls a short-circuited implicature. A short-circuited implicature refers to the process of recognising a specific utterance as one that has acquired a separate meaning, or in this case function, from the literal meaning of the sentence. In this sense, it is similar to how we understand an idiom or other forms of formulaic language. •

•

Conventionalised Indirect Speech Act: Can you pass the water please? (‘can’ implies that the speaker is interested in the hearer’s ability when instead the speaker is making a request for action); Idiom: at the end of the day (the literal meaning is a time reference while the idiomatic meaning is used to express that everything has been taken into consideration).

Sadock (1974) suggests that we may claim an idiomatic expression whenever the intended meaning is at odds with the literal meaning of an utterance. Can you X? is thus regarded as an idiomatic expression for Do X. A similar example is the phrase Why don’t you X? which often stands for Do X – as such it is not a question which the individual words and grammatical form would suggest, but a suggestion to follow a proposed line of action. The non-compositionality of these idioms ‘stems from their discoursal uses, since their surface meanings can be readily decoded’ (Moon, 1998: 47). Indirect speech acts can thus be considered as examples of routinised language (Aijmer, 1996), where there is an entrenchment of meaning in certain lexico-grammatical strings as a result of extended usage.

SPEECH ACTS

A number of studies have tried to account for the use and processing of routinised language in terms of semi-fixed functional phrases (Cowie, 1988; Fernando, 1996; Moon, 1994, 1998; Wray, 2013, 2014). Nattinger and DeCarrico (1992) discuss examples of indirect speech act frames, such as Can you X? They describe such pre-assembled formulaic chunks of language as existing ‘somewhere between the traditional poles of lexicon and syntax, conventionalised form/function composites that occur more frequently and have more idiomatically determined meaning than language that is put together each time’ (1992: 57). Assuming that the realisation of (indirect) speech acts relies heavily on some sort of routine formula, they suggest a model of syntactic frames for language teaching purposes, which in the example above would read something like this: modal + you + verb phrase. Research into routinised speech act formulas in a corpus has highlighted the ubiquitous use of such formulaic language related to a specific speech act force (Adolphs, 2008), which lends further weight to the argument that the hearer’s understanding of indirect speech acts does not necessarily rely on inference procedures alone. This is particularly true for more conventionalised forms of indirect speech acts, such as indirect requests.

6.3 IDENTIFYING AND ANALYSING SPEECH ACTS IN A CORPUS As discussed in Chapters 2 and 3, studying speech acts in a corpus requires a different approach to the traditional methodologies such as discourse completion tests (DCTs) in that the starting point has to be a common linguistic realisation (usually an IFID), such as utterances starting with Can you X? to identify requests or suggestions (see e.g. our analysis of gratitude in Chapter 7). This approach has, in the past, made it difficult to identify all of the different forms of speech act realisations that might perform a specific function in a corpus. However, corpus analyses of speech acts have advanced significantly and corpus linguistics has now become a viable methodology for their study (see Chapters 2 and 3 on corpus pragmatics).

The example of suggestions The question of how many speech acts there are, and in what way meta-categories such as directives and commissives can be broken down into more delicate levels of description, has been one of the issues addressed in Speech Act Theory. However, an issue that needs to be raised in relation to the identification of speech acts, either through the use of corpus analysis or a different methodology, is whether or not lexico-grammar or speech act verbs should be taken into account as guides to illocutionary forces, or whether the classification of speech acts should be based solely on pragmatic criteria, such as felicity conditions. A corpus analysis of the speech act suggest is used here to serve as an example to highlight this issue. Suggestions come closest to Searle’s (1969) category of advisement, a subcategory of directives, which the speaker believes will benefit the hearer (1969: 67). Suggestions can take a number of different forms and are often introduced with either a speech act verb

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or a set of multi-word units that make their function easily identifiable, as illustrated in the examples below taken from two corpora of spoken academic discourse: MICASE and the Nottingham Multi-Modal Corpus (NMMC). 1 2 3 4 5 6 7 8

Why don’t you take some notes? (MICASE); Why don’t you write this up? (MICASE); Let’s just pass this over for first reads… (MICASE); Let’s look at a population… (MICASE); Let’s just have a look at this… (NMMC); So I’d suggest that you might want to begin by… (NMMC); How about, if we start with Erin… (MICASE); Well, you should take chemistry, you should take French… (MICASE).

These eight examples of suggestions taken from MICASE and the NMMC illustrate some of the issues with speech act classification. Examples 6 and 8 are relatively straightforward in that they meet the felicity conditions for a suggestion and example 6 even includes the speech act verb suggest. Examples 1 and 2 are indirect speech acts as they take the form of a question, but the intended meaning is a suggestion. Examples 3, 4 and 5, and to a certain extent example 7, are problematic for a different reason. Examples 3, 4 and 5 include the speaker, at least at a semantic level, in the proposed line of action. This presents a problem with Searle’s classification. If the speaker commits him- or herself to an action, then these utterances should count as commissives. However, since they also include the hearer, they should be directives. The relationship between the speakers is important in this context, as a directive force might be implied if the utterance is produced by the speaker who is institutionally recognised to have more power, i.e. the lecturer in this case.

TASK 6.5 EXPLORING THE CLASSIFICATION OF SPEECH ACTS Table 6.2 illustrates that the frequencies of the multi-word units why don’t you and why don’t we in MICASE are quite similar. Using the instances of the units in Figures 6.6 and 6.7, determine why these units illustrate some of the difficulties associated with Searle’s identification and classification of speech acts. Table 6.2 Frequency counts for why don’t you…? versus why don’t we…? in MICASE Form

Frequency

why don’t you why don’t we

60 77

SPEECH ACTS

Figure 6.6 15 randomly chosen concordance lines for why don’t you…? in MICASE

Figure 6.7 15 random concordance lines for why don’t we…? in MICASE

A distinction has been made between units that, at a semantic level, include the speaker, such as why don’t we… and let’s, and those that only include the hearer, such as why don’t you or maybe you should (Tsui, 1994). The rationale for making such a distinction lies in the ‘rate of the imposition’ (Brown and Levinson, 1987) which is higher when the burden of the suggestion is on the hearer rather than on both hearer and speaker. However, an inclusive unit such as let’s does not necessarily realise an inclusive suggestion. The suggestion let’s close the

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door usually only involves either the hearer or the speaker, rather than both, in carrying out the suggested action. Yet the speech act unit let’s suggests that both are involved. However, it seems that this ambiguity is not important for the participants in the interaction, otherwise there would be more emphasis on clearly articulating who is supposed to take responsibility for the proposed action. It is likely that extended usage can override the semantics of such an utterance, which comes to acquire a meaning in its own right as argued above. In the case of let’s, the meaning is closely related to the function as a discourse-structuring device which becomes more prominent than the illocutionary force of the suggestion.

6.4

WHAT IS A SPEECH ACT CONTEXT?

At the beginning of this chapter we saw that the illocutionary force of an utterance could depend to a large extent on the context in which it is used. In this section we will look in more detail at possible ways in which we may describe such contexts and how those descriptions can help us in the analysis of speech acts. Searle (1969) argues: ‘suppose at a party a wife says “It’s quite late”’. That utterance may be at one level a statement of fact; to her interlocutor who has just remarked on how early it was, it may be (and be intended as) an objection; to her husband it may be (and be intended as) a suggestion or even request’ (1969: 70). The interpretation of the speech act that Searle describes depends both on its place in the ongoing discourse as well as on situational factors. Hymes (1972b) proposes a distinction between speech situation, speech events and speech acts. Speech situations are activities that are recognised by a community, such as birthday parties or dinners. In a way, they form a wider category for speech events which are describable by rules of speech, while speech situations are broader constructs which relate to specific activities rather than to rules for speaking. A speech event could be a lecture, for example, which is marked by a particular structural organisation, as well as a specific distribution of speaker roles. Speech acts occur within speech events and speech situations, and are to some extent determined by them. We discussed earlier how highly ritualised speech situations, such as hiring and firing from a job, or a christening at a church, can only be performed felicitously if the speakers have the authority to carry out the speech act and are in the right place to do so (Section 6.2). According to Hymes (1972b), the speech act encodes social norms in linguistic form. The interpretation of speech acts thus leads to an analysis of the sequential organisation in discourse as well as to an analysis of the social roles of the speakers in the particular context they are engaged in at the time. In order to delineate criteria for analysing different contexts, various approaches have been developed, especially in the field of genre theory.

Speech acts, frames and genres While the types of inference procedures proposed by Leech (1983) and Brown and Levinson (1987) rely predominantly on the (shared) internal knowledge of the speaker and hearer, they make little reference to the knowledge of the participants about the context of the situation. Yet, since speech acts occur within speech events, speakers must have some idea of the constraints that the situation puts on possible contributions to the conversation. Speakers and hearers have what has been called a frame or schema around

SPEECH ACTS

which they orient themselves when they speak (Aijmer, 1996; Bateson, 1972; Brown and Yule, 1983; Cook, 1994; Coulmas, 1979; Goffman, 1981). Aijmer (1996: 27) argues that a ‘frame should be regarded as a hypothesis about speakers’ stereotypic knowledge of a situation and how this knowledge is organised in the long-term memory’. A frame includes criteria such as the identity of the participants, the setting and the reason for the interaction (see Coulmas, 1979). As situations recur, certain ways to perform speech acts recur and become conventionalised, such as thanking (see Chapters 3 and 7) or offering, for example, food (see Chapter 2). What frames try to quantify then are situational factors which would link linguistic indirectness or explicitness to contextual features. One area that has focused on establishing categories that account for the relationship between language and situation is genre theory (Mitchell, 1957; Hasan, 1985, 1999; Ventola, 1987; Hammond and Derewianka, 2001). Many accounts within genre theory are based on the assumption that speech events are describable in terms of stages that are either optional or compulsory in the completion of the event. A service encounter, for example, will have an opening, possibly a hand-over of goods phase and an ending. In extract 6.6, taken from a service encounter in a shop, we see evidence of all three stages. In addition, there is a shift in focus from the exchange of goods to an episode of small talk about the weather. (6.6) [Context: = customer 1; = shop assistant; = customer 2.] Stage Opening

Hand-over Small talk

Hand-over Small talk Ending

How we doing? Hi there how are you? [sound of till] That’s one seventy seven please. Alright seventy seven give it to you now. Not a bad day shur it’s not? Naw it’s cold though. Cold. ‘Twas nice earlier on the sun was shining. Turning cold out there now is it? It is yeah. I’d say we’ll get a right cold spell of it. I’ll give you twenty seven there if you don’t mind. Grand no problem. Sound yeah. I d= I agree with you I don’t mind the cold you know as long as it’s not raining. As long as tis not raining is the main thing. Thank you very much. That’s right. Thanks good luck. (LCIE)

Hymes (1972b) argues that genres and speech events are not identical, but that different genres can occur in one speech event. Hence, in an office meeting, participants may follow the items for discussion on the agenda, and then ‘drift into’ a conversation about the weekend plans of one of the participants. The dynamic character of genres, the fact that

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speakers can themselves change the frame they orient to from one minute to the next, means that in order to understand the context of speech acts we need to consider smaller units of discourse. In extract 6.7, the PhD supervisor asks the part-time student to talk about their recent move to another place of work. The supervisor signals clearly in the first turn that this part of the discourse does not relate to the thesis. The latter is the accepted and expected topic for a PhD supervision session. However, by shifting the frame of discourse, albeit only slightly, to a personal matter, the supervisor introduces a different context for the interaction and this is reflected in both the content and the turn structure of this part of the supervision session. Following this digression from the main topic, the supervisor resumes his primary role and brings the conversation back to discussing the student’s research. (6.7) [Context: = supervisor; = student.]







Okay. Alright go on then tell me where you’ve got to. I d= not thesis wise I mean+ Oh right. +we’ll come on to thesis in the moment. Right okay. But er New York wise+ Yes. +oh God. It’s so full on it’s unbelievable + Yeah. +but but I’m I’m okay I’m keeping it+ Hm. +you know all together. I think the er you know the main the main aspect of it is just this massive learning curve. (NMMC)

This leads us to look at the different ways in which speech acts have been considered within a discourse framework which will be further explored in the following section.

6.5 SPEECH ACT CLASSIFICATION IN DISCOURSE ANALYSIS There are a number of discourse level models which involve speech acts as core units of analysis. Sinclair and Coulthard (1975), for example, incorporate situational factors as well as some lexico-grammatical features into their classification scheme, and define acts by their interactive function. The discourse model developed by Sinclair and Coultard involves a rank scale which is used in the description of classroom discourse. Each of the ranks has its own structure which can be analysed with reference to the rank below. The highest rank is the lesson; this is made up of various exchanges which in turn consist of moves. A typical move structure consists of an opening move in the form of a question by the teacher (Initiation), an answering move by the student (Response), and a follow-up (Feedback) move by the teacher evaluating the student’s answer. The lowest rank are acts which are more general than the speech acts in Searle’s categorisation scheme, but can

SPEECH ACTS

be further classified at the level of sub-act. Sinclair and Coulthard differentiate between meta-discursive, interactive and turn-taking acts. Their three initiating (interactive) acts at the exchange level are: 1) 2) 3)

Informative Directive Elicitation

An informative act is realised through a statement that provides information relevant to the lesson, while a directive act requests a non-verbal response (e.g. Open your books). An elicitation act requests a linguistic response. Extract 6.8 features an example of an elicitation by a lecturer in an academic supervision session. (6.8) [Context: = supervisor; = student.]

Can it be made to work institutionally though? I don’t know but I think I I’ve got to just work systemically.

ELICITATION RESPONSE (NMMC)

Sinclair and Coulthard’s model is based on British primary school classroom data and many adaptations have since emerged which apply the model to conversational and other types of data (Burton, 1981; Tsui, 1994). Tsui (1994) differentiates three primary classes of acts based on the three moves of an exchange: initiating acts, responding acts and follow-up acts. Her classification criteria for the different speech act classes are based on intended speaker response. Table 6.3 illustrates what she classifies as initiating acts and the speaker response they are designed to elicit.

Table 6.3 Initiating acts (Tsui, 1994) Speech act

Discourse function

Elicitations Requestives Directives

To elicit an obligatory verbal response or its non-verbal surrogate. To solicit non-verbal action with the option to carry out this action. To solicit non-verbal action with no option of whether or not the addressee will carry out solicited action. To provide information and to report events and states of affairs, recount personal experience, etc.

Informatives

Tsui (1994: 91) contends that: requestives subsume utterances which have been referred to in the speech act literature, as requests, invite, ask for permission, and offer. They do not subsume those which have been referred to as order, command, and instruct. The latter are subsumed under a different subclass: directives.

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According to Tsui’s classification, suggestions are therefore a subcategory of directives. She distinguishes between mandatives, which direct the addressee to perform an action for the benefit of the speaker, and advisives, which direct the addressee to perform an action for his or her own benefit. Interestingly, Tsui’s model cannot easily accommodate suggestions such as those in the examples above either. Utterances such as I would suggest that we take your bag inside (Adolphs, 2008) are neither mandatives nor advisives. She therefore creates a further category, which curiously becomes a sub-class of requestives which she calls proposals. A proposal, according to Tsui, ‘prospect[s] both speaker action and addressee action and is typically realised by “Can/Could/Shall we do X? ”’ (1994: 100). It is beneficial to both speaker and hearer. Her matrix for requestives is outlined in Table 6.4. Table 6.4 Requestives (Tsui, 1994: 104)

Speaker benefit Addressee benefit S+A benefit

Speaker (S) action

Addressee (A) action

Request for permission Offer

Request for action Invitation

S+A action

Proposal

The problem with classifying utterances in the abstract (i.e. detached from their discourse context) is that it is difficult to think about cost and benefit to the speakers and hearers when they are abstracted from their social roles. Role relationships are of major importance (Leech, 1983; Levinson, 1983); however, in real data it is not always easy to determine how they affect the cost–benefit scale. The example we used in Section 6.3 from MICASE Let’s look at a population (example 4) does not seem to have immediate benefit to anybody. When it is placed into its academic context, however, where it is used by a lecturer, and its discourse context of starting a new transaction in the discourse, thus signposting a change in the structure of the lesson, it becomes clear that cost and benefit scales become secondary. The difficulties in analysing suggestions as outlined above are related partly to the grounds on which a directive is differentiated from a requestive. Corpus data in general seems to suggest that apart from speaker and hearer benefit, there is a type of benefit related to completing a particular task. There can be tensions then between speech act classifications and taxonomies which were developed on the basis of invented examples, and the analysis of speech acts in corpus data. Finally, one of the issues that arises when we draw upon transcribed corpus data as the basis of analysis of speech acts and discourse structure is that our analysis is necessarily limited to the data types that have been collected. In terms of spoken corpora, this is often still limited to transcripts rather than to audio-visual data (see Garcia McAllister (2015) and also Chapter 3 for more on this limitation for pragmatics research). However, in everyday conversation, some of the discourse functions are performed through non-verbal acts and some of the categories of discourse acts are predicated on the effect of non-verbal action (see e.g. the discourse function of ‘directives’ in Tsui’s framework above). A transcript can therefore only provide part of the picture of the overall interaction that has taken place. Ongoing developments in multimodal spoken corpus analysis are trying to address this issue, and advances are being made in the analysis of language and gesture within a corpus

SPEECH ACTS

linguistic framework (see Knight et al., 2009; Lücking et al., 2013; Diemer et al., 2016; Kok, 2017; Rühlemann, 2019). These developments are likely to have a significant impact on the way in which we are able to describe systematically speech acts and discourse structure, and may even challenge some of the more traditional taxonomies of discourse function.

6.6

CONCLUSION

In this chapter we have introduced the main terms and concepts which have been developed in the area of Speech Act Theory. We have covered the underlying arguments for regarding language as action, as well as looked at different ways of classifying speech acts in context. We have shown that the use of real data changes the way in which we might approach both the identification of speech acts and their classification. In particular, we have looked at studying speech acts in the extended discourse context in which they occur, and we have discussed related models for analysing speech acts in discourse. As such, this chapter has covered theory and practice that is traditionally seen as belonging to the area of pragmatics, as well as theory and practice related to the area of discourse analysis. Speech acts are a key unit for both of those disciplines and once we start to look at real data in use it is often advantageous to bridge those traditional boundaries in order to enhance our descriptions of language.

6.7

FURTHER READING

Aijmer, K., 1996. Conversational Routines in English. London: Longman. Drawing upon data taken from the London-Lund Corpus of Spoken English, this book analyses recurrent speech act expressions, such as thank you or Can youX? A range of speech act functions are covered, including indirect requests, thanking and apologising. The book offers an in-depth analysis of pragmatic functions and also takes into account the discourse context in which they occur. Barron, A., 2017. ‘The speech act of “offers” in Irish English.’ World Englishes, 36(2), 224–238. This article focuses on speech act variation in Irish and British English. The study compares corpus data, specifically in the form of the spoken face-to-face text category, in the Republic of Ireland component of ICE-Ireland with ICE-Great Britain. The article demonstrates the value of cross-cultural comparative speech act research given that significant differences were unearthed between offers in the two corpora at both pragmalinguistic and sociopragmatic levels. Jucker, A.H. and I. Taavitsainen (eds), 2008. Speech Acts in the History of English. Amsterdam: John Benjamins. This edited volume takes a historical perspective to the study of speech acts and includes a set of articles that explore the theoretical and methodological underpinnings of the use of speech acts. The volume is divided into three parts: directives and commissives, expressives and assertives, and methods of speech act retrieval. It is a particularly useful book for those interested in studying speech acts on the basis of corpus data.

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Weisser, M., 2016. ‘DART – The dialogue annotation and research tool.’ Corpus Linguistics and Linguistic Theory, 12(2), 355–388. Because corpus pragmatics is still in its relative infancy, automatic pragmatic tagging, although increasingly common, represents an ongoing challenge in the field. In this article, Weisser outlines the use of his Discourse Annotation and Research (DART) tool to tag the SPAADIA, a corpus of telephone transactional dialogues. DART automatically annotates up to 57 speech act types and facilitates the extraction of both formal (syntactic) and functional (speech act) properties.

CHAPTER 7

Pragmatics and language variation

7.1

PRAGMATICS AND LANGUAGE VARIATION

This chapter employs a range of different corpora to examine pragmatic variation within the same language in some detail. However, before we begin the corpus work, it is worth exploring the study of linguistic variation in general. The first point of note is that the study of language variation has traditionally focused on phonological, lexical and syntactical levels. The systematic study of variation at a pragmatic level is a relatively recent development (see Schneider and Barron, 2008a; Cheshire, 2016). This has been flagged as a serious concern, since any description of language that focuses solely on language as a system and ignores language as a living, emergent, negotiated, co-constructed enterprise is ‘not only incomplete, but inadequate’ (Schneider and Barron, 2008b: 3; see also McCarthy and Clancy, 2019). The second point of note is that, again traditionally, the focus has been on historical variation, or variation over time, and geographical variation, variation over space. However, as the focus has shifted from phonology, lexis and syntax, so too has the type of variation being studied, and there is now a lot more emphasis placed on variation in social space in addition to the more traditional historical and geographical variation. Variation in social space can be examined from two different perspectives. We can look at social variation from a macro-social perspective – that is, the influence of factors such as age, gender, ethnicity, social class, etc. – and from a micro-social perspective – that is, variation influenced by more ‘local’ factors such as the degree of social distance between participants (e.g. strangers, friends, family), power (an employee talking to her or his boss) or register (see Chapter 8 for more on register). These types of variation – historical, geographical and social – can be examined on a number of levels (Schneider and Barron, 2008b: 20–21), illustrated in Table 7.1. Table 7.1 Levels of variation (Schneider and Barron, 2008b: 20–21) Level of variation

Research focus

Formal level

Linguistic forms such as discourse markers, stance markers, hedges, etc. Analysis of this type can be classified as form-to-function (see Chapter 3) Speech act realisation and modification. Analysis of this type can be classified function-to-form (see Chapters 3 and 6) Sequential patterns such as adjacency pairs, interactional exchanges or interactional phases (such as openings or closings) Content-related questions such as ‘What topics are considered taboo?’ ‘What topics are considered suitable for small talk?’, etc. Turn-taking phenomena such as overlaps, interruptions, backchannels, etc. (see Chapter 8)

Actional level Interactional level Topic level Organisational level

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The levels described in Table 7.1 all have an influence on intralingual pragmatic choice (i.e. pragmatic variation within the same language), both for native and non-native speakers. From a non-native perspective, the obvious benefit of highlighting the influence of these factors lies in the pedagogic realm. Ren and Han (2016: 425) point out, specifically in relation to speech acts, that it is of ‘paramount importance that teachers and learners are well informed about the intralingual pragmatic variation found in different varieties of English’. However, it is also worth stressing here that understanding intralingual variation is of equal importance to the native speaker. Lippi-Green (1997: 30) points out that ‘[language] variation isn’t without consequences’. Wolfram and Schilling-Estes (2006: 100–101) argue that conflict within different social and ethnic groups in modern American society is due to a failure to understand that ‘different groups have different language-use conventions which might have nothing to do with the intentions that underlie particular language uses’. This statement has, of course, ramifications far beyond contemporary American society. The study of pragmatic variation within the same language has, in the main, concentrated on those languages described as pluricentric – that is, languages that have more than one standard variety due to the fact that they are often used in a number of different countries. Therefore, English is a pluricentric language, as there are a number of different varieties of English used in a number of different countries – this chapter explores variation within and between Irish, British and American English. Other examples of pluricentric languages include, but are not limited to, Spanish, French, German, Portuguese, Arabic and Swahili. Although the focus of this chapter is on pragmatic variation within the English language, we acknowledge that English is by no means the benchmark for intralingual pragmatic variation. For example, Placencia and García (2007) detail the considerable work that has been conducted on regional pragmatic variation in Spanish. Schneider and Barron’s (2008a) publication, one of the first to address the dearth of studies into pragmatic variation, contains studies that examine five different languages – English, Dutch, German, Spanish and French – twelve different national varieties (e.g. Plevoets et al. (2008) explore variation between Netherlandic Dutch and Belgian Dutch) and two sub-national varieties of Ecuadorian Spanish (Placencia, 2008). Barron and Schneider’s (2005) publication The Pragmatics of Irish English was one of the first publications of its kind to focus on intralanguage pragmatic variation, in this case within the national variety of Irish English, and this has paved the way for many of the more recent publications (see e.g. Aijmer, 2013; Amador-Moreno et al., 2015). With the exception of Aijmer (2013) and selected chapters from Barron and Schneider (2005), Schneider and Barron (2008a) and Amador-Moreno et al. (2015), not all variational research has been done using a corpus linguistic methodology. There is, however, as this book demonstrates at a broader level, a fast-emerging corpus pragmatic field, with selected research focused on pragmatic variation between languages from a historical, geographical or social viewpoint and at a number of levels of pragmatic analysis. A selection of this research includes O’Keeffe and Adolphs’ (2008) study of response tokens in CANCODE and LCIE; Rühlemann’s (2007) and Bednarek’s (2008) division of the BNC into different registers in order to explore a variety of pragmatic phenomena such as co-construction, deixis and humour (Rühlemann, 2007), and language and emotion (Bednarek, 2008); Clancy’s (2016) examination of the sub-corpus of intimate spoken language from LCIE and his focus on both macro- and micro-social variation, and Vaughan et al.’s (2017) comparison

PRAGMATICS AND LANGUAGE VARIATION

of the frequency of occurrence of vague category markers (see Section 8.4) in LCIE and CANCODE. This is merely the tip of the iceberg in relation to intralanguage pragmatic variation research that represents an ongoing and, indeed, burgeoning trend in the study of pragmatics in general. As is the case for corpus linguistics in general, any analysis of intralingual variation is improved through a comparative process. Our introduction to the analysis of pragmatic variation involves the comparative use of a number of language corpora (for descriptions of individual corpora see Appendix). The corpora used encompass three varieties of English – American, British and Irish – and include a range of different spoken and written context types allowing a sufficient base for a comparative analysis of variation within a language, in this instance English. Our focus in this chapter is on pragmatic items with a high frequency across varieties of English. Our examination of response tokens, pragmatic markers, vague language and speech acts begins with a deliberately broad focus across regional varieties; however, we then seek to narrow the analysis down in order to account for both similarities and differences in geographical, historical and social variation in English.

7.2

RESPONSE TOKENS AND VARIATION

Our first foray into pragmatic variation within the same language is in relation to response tokens (see also Chapter 9). We use the term response token to refer to a range of linguistic items that occupy turn-initial position, but which, in occupying this position, have a particular pragmatic function: that of the process of engaged listenership (see e.g. McCarthy, 2002). Response tokens can be categorised as both minimal and non-minimal. Minimal response tokens are often referred to as backchannels, monosyllabic or monomorphemic forms such as mm or yeah that assume a role as inter-turn feedback in an extended speaker turn (Peters and Wong, 2015), as is evident in extract 7.1. (7.1) [Context: Speakers are numbered according to the order in which they occur in the extract.] Well of course it’s you know it’s it one of the last few things in the world you’d ever want to do you know unless it’s just you know really you know for and for their uh you know for their own good Yes yeah I’d be very very careful and uh you know checking them out uh our had to place my mother in a nursing home she had a rather massive stroke about uh Um-hum Uh six eight months ago I guess and uh we were I was fortunate in that I was personally acquainted with the uh people who uh ran the nursing home in our little hometown Yes So I was very comfortable you know in doing it when it got to the point that we had to do it but there’s well I had an occasion for my uh mother-in-law who had fell and needed to be you know could not take care of herself anymore was confined

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to a nursing home for a while that was really not a very good experience uh it had to be done in a hurry I mean we didn’t have you know like six months to check all of these places out and it was really not not very good uh deal we were not really happy with the Yeah Nursing home that we finally had fortunately she only had to stay a few weeks and she was able to to return to her apartment again but it’s really a big uh big decision as to you know when to do it Yeah (OANC Switchboard: File sw2005-ms98-a-trans) In this extract we can see that the tokens yes, yeah and um-hum, marked in bold, are functioning as ‘continuers’ (Schegloff, 2000) in that, although interpersonally important as they are demonstrating listenership, the listener does not attempt to take the floor from the speaker. Instead, the listener seeks to encourage the speaker to continue with his or her turn. This leads to an extended narrative about the placing of older people in nursing homes. These response tokens are often described as having a floor-yielding function. In this way, according to Tottie (1991: 255), backchannels ‘grease the wheels of the conversation’. As the extract demonstrates, the tokens can occur singly, um-hum, or in clusters, yes yeah. Response tokens are also prone to repetition and this, coupled with their tendency to cluster, makes them very frequent in spoken language. Non-minimal response tokens are, on the other hand, frequently made up of adjectives, adverbs, short phrases or clauses such as lovely, wow, absolutely, that’s great, not at all or what a pity. In extract 7.2, in addition to minimal tokens such as uh-huh and mm (all marked in bold), we can see the use of the non-minimal response token that’s + adjective in the form of that’s good. Again, the tokens cluster – Oh that’s good and Oh, OK. The extract demonstrates the use of both minimal and non-minimal response tokens in what appears to be a radio or television talk show setting. The interviewer, , uses a response token at the beginning of each of their speaker turns in order to refer to each of the interviewee’s answers to the questions before proceeds to ask another question. In these instances, is offering positive feedback and social support; for example, the response Oh that’s good on hearing that they are interviewing a person whose surname is Polk and lives in Polkton. Therefore, we can see that response tokens can occupy an entire speaker turn as in extract 7.1, but can also be associated with the taking of the speaker turn as in extract 7.2. Response tokens such as these are often attributed with having a floor-grabbing function. In this way, response tokens reflect the importance of the turn-initial slot in the architecture of conversational turn-taking.1 (7.2) Welcome back to our show! OK. This is Maria, and I don’t know your last name. Polk. Oh that’s good. From Polkton, Maria Polk. OK. And where did you grow up? Were you born in this area here? I was born in Cottonville. Right outside of Norwood in Stanley County. Oh, OK. When you were little, did your mom read you books, or did somebody read you books in your house?

PRAGMATICS AND LANGUAGE VARIATION

My mama read to me and my sister. Uh-huh. What kind of books were your favourites? Do you remember any that were maybe a real favorite of yours? Mm, I kind of liked them all. Um, I didn’t really have a favorite. (OANC face-to-face: File PolkMaria) To conduct research into response tokens, there are various methodological options. We could take the forms already identified in the literature and conduct form-to-function analysis by searching for these items. Alternatively, we could take a function-to-form approach: by identifying all turn-opening forms and then sifting through these to identify response token items (see Chapter 3 for a description of form-to-function and function-to-form approaches in corpus pragmatics). In this case we opted for the former approach. Word frequency lists for the spoken OANC face-to-face data and the OANC switchboard data were generated and the items that have been identified in the literature as response tokens, both minimal and non-minimal, were extracted from the frequency lists and presented in Table 7.2. These frequency results reflect the raw frequencies for each item and are not indicative of the items’ turn position (we expand further on this point in relation to our more detailed treatment of uh and well). Therefore Table 7.2 represents a list of response token candidates. Table 7.2 Frequency results for response tokens candidates in OANC (face-to-face) versus OANC (switchboard) corpora (normalised per million words) OANC (face-to-face) Item 1 2 3 4 5 6 7 8 9 10

um uh well really yeah no oh right ok uh-huh

OANC (switchboard) Frequency 9790 8690 3375 3275 2375 1915 1880 1820 1490 1270

Item

Frequency

uh yeah well um oh right uh-huh um-hum really good

19,895 13,773 6600 6060 5400 5099 4685 4579 4312 2362

In the OANC face-to-face corpus there are seven minimal response tokens – um, uh, yeah, no, oh, ok and uh-huh – whereas in the switchboard corpus there are six – uh, yeah, um, oh, uh-huh and um-hum. The other items in the table include high frequency discourse markers such as well, really and right. Good occurs in tenth position in the switchboard corpus data, it does not occur in the top ten items in the face-to-face data and adjectives such as good have been reported on in the previous literature as having higher interpersonal import due to its predominant use in positive and supportive engagement (see e.g. McCarthy, 2003, 2015). In general, as Table 7.2 demonstrates, the frequencies are higher in the switchboard corpus than in the face-to-face corpus due to the nature of the speech

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event. Face-to-face conversation allows us the possibility of paralinguistic or kinaesthetic response, whereas response has to be verbal on the telephone. Furthermore, frequent clustering of response tokens occurs in telephone calls where there are more pre-closing and closing routines (see e.g. Antaki, 2002). In these cases, the response tokens function to signal that the conversation is entering this phase while simultaneously functioning to maintain interpersonal relationships (see also Schegloff and Sacks, 1973; Jefferson, 1973; Button, 1987; Hartford and Bardovi-Harlig, 1992; Carter and McCarthy, 2006). As Table 7.2 demonstrates, in the face-to-face corpus there is a notable drop in frequency after the first and second response token items, um (9790 occurrences) and uh (8690) respectively, to well (3375). Similarly, in the switchboard corpus there is a notable decrease in frequency from the most frequent item uh (19,895) to yeah (13,773) to well (6600). This drop-off in frequency has been noted by other studies in different varieties of English. For example, McCarthy (2015) notes a similar pattern in a comparison of response tokens between Irish (LCIE) and British (CANCODE) Englishes. For the purposes of further comparison, we decided to compare two of the most frequent minimal and non-minimal response tokens, um and well respectively, from the face-to-face data to the occurrences of these tokens in the switchboard data. The combined frequency of both items is approximately the same in both datasets – they account for 13,165 occurrences in face-to-face and 12,660 in the switchboard data (see Table 7.2). However, the frequency difference, across tokens, is much higher in the face-to-face data; um has 6415 more occurrences than well, whereas in the switchboard data well has 540 more occurrences than um. Tottie (2015) treats uh and um as variants of one variable UHM but in Table 7.2 they are listed separately and are not included in the counts for uh-huh and um-hum which are treated as distinct items. Tottie (2015: 381) also labels uh and um as planners, ‘which is indicative of their use to give speakers time for online planning of their contributions to the conversation without necessarily implying uncertainty or dysfluency’. Well, on the other hand, working beyond the lexical sphere of, for example, its use as an adverb in I know him well, is often associated with a range of linguistic items used to preface disagreement, such as I mean or I don’t know. These items have been shown to typically mitigate or soften disagreement by positioning it further back in the turn (see Kotthoff, 1993; Holtgraves, 1997). Schiffrin (1987: 126) highlights the importance of well to the maintenance of discourse coherence due to the fact that it often occurs at a point where ‘upcoming coherence is not guaranteed’, such as the refusal of an offer. In order to get an impression of the pragmatic patterning of um and well, we used a sampling approach (see Chapter 3, Section 3.3). We randomly generated a sample of 100 occurrences for each of the items in both sub-corpora. Therefore, for each item, we examine 200 occurrences; 100 in the face-to-face data and 100 in the switchboard data for each item. The high frequency of these items means that an examination of each individual occurrence is, perhaps, beyond the scope of the chapter but this sample might point towards some interesting future research directions. The occurrences of um and well in the downsample were first generated in concordance lines and then examined individually in context. Through this iterative sifting process, we were able to identify those items that occurred in a turn-initial position (in general, coding for turn position in the turn-taking process is not a straightforward matter; see Tottie (2015) for more on this issue). Table 7.3 provides the frequency for each item in turn-initial position, subdivided into a comparison between their occurrences in the face-to-face data and their occurrences in the switchboard data.

PRAGMATICS AND LANGUAGE VARIATION Table 7.3 Occurrences of um and well at turn-initial position in the OANC sub-corpora based on 100-item downsample for each um

Turn-initial position

well

face-to-face

switchboard

face-to-face

switchboard

13

24

16

34

Interestingly, the 13 occurrences of um in initial position in the face-to-face data, which corresponds to 13 per cent of occurrences in the downsample, is very similar to the results from other corpus studies. Kjellmer (2003), using the COBUILD corpus, also records a 13 per cent sentence initial position, Rühlemann (2007), using Spoken BNC1994 data, records a 14 per cent figure and Tottie (2015) documents turn-initial UHM at 15 per cent in the SBCSAE. In the OANC switchboard data, um has a higher frequency, 24, at turn-initial position perhaps due to the fact that more questions are asked in general in the switchboard data as opposed to the face-to-face data, where questions often appear to have been designed to elicit longer responses from participants. In relation to well, the figures are a little different. Well occurs in turn-initial position on 16 occasions in face-to face conversation and 34 in the switchboard data. In order to more closely examine these results, both um and well were further examined in relation to their function in turn-taking.

TASK 7.1 UM AND TURN POSITION Figure 7.1 illustrates 20 randomly generated concordance lines for the occurrence of um in the Spoken BNC2014. 1) 2)

Based on these concordance lines, what initial hypotheses might be generated in relation to the position of um in turns in contemporary spoken British English? How do these initial, tentative results compare to those in Table 7.3?

Figure 7.1 20 random concordance lines for um in the Spoken BNC2014

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In order to step up the analysis a little, in Table 7.4, the turn-initial instances of both um and well were examined as to whether they had a floor-yielding role (i.e. as a backchannel rather than being used by the speaker in an attempt to take over the floor), or a floor-grabbing function (i.e. acknowledging the previous speaker turn but then followed by a contribution which ‘takes’ the conversational floor) (see extracts 7.1 and 7.2).

Table 7.4 The turn-taking function of um and well in the OANC spoken sub-corpora based on 100-item downsample for each um

Floor-yielding Floor-grabbing

well

face-to-face

switchboard

face-to-face

switchboard

2 11

5 19

2 14

3 31

Although admittedly working from a small sample, it appears that both um and well, when in turn-initial position, function predominantly in both sub-corpora to signal interlocutor engagement with the previous turn and that this engagement is followed by a contribution that necessitates the taking of the floor. In other words, both tokens seem to have a ‘turn-grabbing’ function. This function is evident in the use of well (in bold) in extract 7.3. (7.3) And, uh, so I guess you’re a big Yankee fan. Big time Yankee fan. It’s been a good couple of years for us Yankee fans here lately. And, uh, we were down on Fifty-Third Street, which is five blocks away from Central Park, and, um, my fiancé had just passed her boards and it was our anniversary, so I decided to surprise her with walking down to Central Park off of Fifty-Eighth. And, um, it kind of just worked out perfect. I proposed to her. I was lucky enough for her to say, “Yes.” And, um, so, yeah, she’s been up north a couple of times and in the PA area as well the Poconos where you hear the honeymooners always go. Uh-huh. And, um, so Well it sounds like you have a pretty bright future ahead of you. Not too bad. It’s getting brighter and brighter, it seems, every day. And, um, it’s going to be a new adventure for us going out to Denver, CO, with me being a pharmaceutical sales representative and my fiancé being in the medical profession as well, being a nurse. And, um I’ve heard that’s a beautiful area. (OANC face-to-face: File QuelerAdam)

PRAGMATICS AND LANGUAGE VARIATION

In this extract, uses well in turn-initial position as part of an extended turn that functions to signal to to continue with their answer and provide some additional information. This use of well comes after a turn where, arguably, um has been involved in yielding the turn to (um in this instance serves to illustrate the difficulties in coding for turn position in that in ’s turn And, um, so, it is moot as to whether um is in turn-initial, medial or final position). Overall, response tokens such as well and um, and really, yeah, right, etc., have a role to play in the determining of speaker intention. When a speaker uses a response token such as well, it is subject to interpretation by the other conversational participants as a signal of intention (see Tottie, 2015). In the case of um and well, this intention may be that, while acknowledging what has been said in the previous turn, the speaker now wishes to hold the conversational floor for a period of time before they yield it again, perhaps ironically, through the use of a token such as um.

TASK 7.2 WELL, TURN POSITION AND FUNCTION Figure 7.2 illustrates 20 randomly generated concordance lines for the occurrence of well in the Spoken BNC2014. 1)

2) 3)

Based on these concordance lines, what hypotheses might be generated in relation to both the turn position and function of well in contemporary spoken British English? How do these results compare to those in Table 7.4? Return to Task 7.1: what are the functions of um? Can any connection be made between turn position and function based on the instances of well and um in these tasks?

Figure 7.2 20 random concordance lines for well in the Spoken BNC2014

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Reflecting on the methodology here, we used existing research on the forms that are associated with turn openings to get a broad view of the process of engaged listenership across our two sub-corpora of American English. Then, we used a downsampling approach (of 100 items from each dataset) to look very closely at turn-openers. This micro-analysis gives us much more insight and ultimately it provides indicative results that can be further tested on a number of levels. For example, the concordance analysis could be extended to every occurrence of uh and well in both sub-corpora in order to build a complete picture of the patterning of these items. Alternatively, this approach could be extended to include other items in Table 7.2, such as yeah or really. Finally, these results could be compared to other corpora of spoken English across different varieties in order to investigate the patterning of this fundamental feature of the turn-taking system which fulfils a very particular, but nonetheless vital, pragmatic function.

7.3

PRAGMATIC MARKERS AND VARIATION

The term pragmatic marker (PM) is used as an umbrella term for a large number of linguistic items that operate outside of the structural limits of the clause. Since they are clause independent, one of their defining characteristics is their optionality which makes them ideal bedfellows in the study of the interpersonal realm, as they are part of language as discourse rather than language as system (see McCarthy and Clancy, 2019). Although there is much debate on issues such as the terminology used to refer to PMs, their definition and their polysemous nature, it is generally accepted that, through a process of grammaticalisation, they have acquired functions that are both textual in that they organise discourse (often referred to as discourse marking) and interpersonal in that they encode aspects such as speaker attitude or involvement in some way depending on the context (often referred to as pragmatic marking) (see e.g. Schiffrin, 1987; Östman, 1995; Brinton, 1996; Fraser, 1996; Aijmer, 2002, 2013). Aijmer (2015) describes PMs as a category in constant flux with new items being added constantly. Hence, Amador-Moreno et al.’s (2015) further broadening of the categorisation of PMs to include, among other linguistic items, tag questions and vocatives. We use the term pragmatic marker here to encompass both their textual and interpersonal spheres of meaning (other studies use the terms discourse marker and pragmatic marker interchangeably or refer to these items as discourse-pragmatic markers or D-PMs). There is a considerable body of PM research working at the interface of corpus linguistics and pragmatics which highlights the influence of context on the meaning and function of PMs. Existing research has investigated PMs in relation to their use in a number of language varieties (see e.g. Holmes’ (1986) study of PMs in New Zealand English, Andersen’s (2001) analysis of London teenage English, and Aijmer’s (2013) work on the ICE suite of corpora which includes Australian, Canadian and Singapore English among others). PMs have also been examined cross-culturally (see e.g. Müller, 2005; Fung and Carter, 2007) and from a diachronic perspective (see Brinton, 1996; McCafferty and Amador-Moreno, 2012; Andersen, 2016). As discussed in Chapter 3, PMs are often the focus of corpus pragmatic research, as they can be recalled relatively easily through form-to-function processes (see also Chapter 9 where we explore PMs pedagogically).

PRAGMATICS AND LANGUAGE VARIATION

In order to illustrate the variability of PMs within the English language, in this section we compare their use in the written and spoken domains. We have chosen to focus on the British Academic Written English (BAWE) corpus in order to represent the written sphere, whereas spoken language is represented by the Limerick Corpus of Irish English (LCIE). Here we take a form-to-function approach, based on multi-word units. The majority of the literature on PMs has been devoted to the occurrences of single items such as like, just or actually, or twoword items such as you know, I mean or I think. In order to expand upon this, we have utilised WordSmith Tools Version 7.0 (Scott, 2017) to generate the most frequent two-, three- and four-word clusters2 in both corpora, and the results are evident in Tables 7.5 and 7.6. These results represent the raw frequency counts for each item. In these instances, the counts are not normalised. The default minimum frequency setting for chunks in WordSmith Tools is five occurrences which we adopted as our cut-off point, but which proved to be unnecessary given the frequencies of the top five two-, three- and four-word clusters in each corpus. First, let us consider the written British English as represented by the BAWE – if we are to apply our definition of a PM to the results shown in Table 7.5, primary amongst these: their optionality, their textual and interpersonal functions, and the fact that they have little or no semantic meaning, then the four-word cluster on the other hand (highlighted) is the only item to meet the criteria as a PM within the top five most frequent items. All the other items listed in Table 7.5 are syntactic fragments frequently used in the construction of a phrase, clause or sentence. Extract 7.4 illustrates the use of on the other hand in an undergraduate linguistics essay. As we can see, it is used as a linking adverbial to ‘in some way mark incompatibility Table 7.5 Most frequent two-, three- and four-word clusters in BAWE BAWE

Two-word

Frequency

Three-word

Frequency

Four-word

Frequency

1 2 3 4 5

of the in the to the it is and the

63,624 36,694 24,102 16,473 16,111

in order to as well as due to the one of the the use of

3899 2364 2335 2010 1868

on the other hand as a result of in the case of the end of the it is important to

836 724 608 582 568

between information in different discourse units’ (Biber et al., 1999: 878), in this case two sentences where ideas about the use of indefinite pronouns among male and female speakers are contrasted. In this way the adverbial acts as both a structural device signalling that a contrast/concession unit is forthcoming, and also in an interpersonal sense in that the writer is signalling to the reader that, based on their reading, they have evaluated the use of interpersonal pronouns as a difference between the speech of men and women. (7.4) In this assignment it is clear that females use a far greater quantity of indefinite pronouns and in the majority of cases these are seen to be used as a device to distance themselves from making direct claims. They are mainly used as a result of a lack of confidence and awareness that they do not want to be seen as overly self-assured and

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therefore females are often presumed to be unconfident, hesitant speakers. Males on the other hand, are seen to use less indefinite pronouns, indicating the confidence in their speech in that they are more able to talk directly about matters. However, as women become more socially equal to men, their patterns of lexical use are likely to change and therefore it is debateable that these features will be used in such great quantity in the future. (BAWE: File 6120b) In contrast, the results for the most frequent two-, three- and four-word units in spoken Irish English, represented by LCIE, reveal three items that meet our criteria for categorisation as PMs: the two-word you know and the three-word I don’t know and do you know. You know has been shown to be the third most frequent two-word unit in the Spoken BNC1994 and I don’t know the most frequent three-word cluster (Adolphs and Carter, 2013). Here, it should be acknowledged that these three items have potentially semantic meaning – where know functions as a lexical verb, for example, Do you know who saw him? and can also occur in fixed phrases such as Better the devil you know. Similarly, I don’t know and Do you know? have literal, semantic meaning connected to factuality and (un)certainty. Items with semantic meaning have not been eliminated from the counts in Table 7.6.

Table 7.6 The most frequent two-, three- and four-word clusters in LCIE LCIE

Two-word

Frequency

three-word

Frequency

Four-word

Frequency

1 2 3 4 5

you know in the of the do you I don’t

4406 3435 2354 2332 2200

I don’t know do you know a lot of you know what do you want

1212 769 522 379 373

you know what I know what I mean do you know what I don’t know what do you want to

230 215 208 134 121

The instances of multi-word units shown in Table 7.6 that have purely semantic, as opposed to pragmatic, meaning were not eliminated from the counts, as to attribute these frequency results purely to the lexical system would be to miss the interpersonal element that is associated with them and, by extension, their pragmatic role in the structure of discourse and the establishment and maintenance of relationships. For example, the three linguistic items highlighted in Table 7.6 are associated with either you or I, demonstrating the interactive nature of many of the most frequent units in spoken language. Second, you know and I don’t know have been associated with the realm of linguistic politeness. Extract 7.5 demonstrates the role of you know by two young female participants in an informal, interview setting. (7.5) [Context: informal interview between two female students - = third-level student; = second-level student.] Are there many tourists around?

PRAGMATICS AND LANGUAGE VARIATION

Many tours? Oh tourists. Oh yeah Killarney’s like the capital of tourists. I suppose like em French German like you know American like especially. You get everything here like you know. Do you ever talk to them? Em some all right like you know but like I suppose I’d be really interested in the money you know. Do you get lots of tips? What kind of tips they offer like. They’re all right like you know. Good craic. Who give the best tips? Em to be honest with you I’d say em the English do really. You see em the American’s like are usually like they’re fairly old like you know. The way it is the old ones like you know they don’t give you nothing like. So that’s about it like you know. What do you want to do when you leave school? Hopefully I’d say I’ll go to college anyway. You see most of my brothers and sisters went to U L so I’d like to go there as well like you know cos they’ll be up there maybe and there’s some good craic like you know. (LCIE) In this extract uses you know on ten occasions over relatively few utterances, all of which are optional. On each occasion you know is not used in a lexical sense, nor is it used to convey uncertainty. Instead, it serves a different pragmatic function. Of the five utterances, you know occurs in turn final position in four of them, thus signalling that she is turning the floor over to , not because is unwilling to continue speaking, but because the norms of politeness of the situation, an interview, necessitate it (see Fox Tree and Schrock, 2002). You know is also seen to cluster with like, in the particular order like + you know, in each of these instances. Aijmer (2002) argues that the clustering of certain pragmatic markers indicates that they share a similar function and also serves to underline their phatic nature (see also the work of Diani (2004) in relation to I don’t know and I mean).

TASK 7.3 CLUSTERS IN ACADEMIC SPOKEN ENGLISH Table 7.7 illustrates the top ten most frequent two-, three- and four-word units in BASE. Using Tables 7.5 and 7.6 as reference points, discuss the similarities and/or differences between spoken academic British English versus written academic English and/or Irish English casual conversation. Table 7.7 The ten most frequent two-, three- and four-word clusters in BASE BASE

two-word

Frequency

three-word

Frequency

four-word

Frequency

1 2 3 4 5

of the in the going to you know and the

9958 7766 4184 3722 3659

going to be one of the a lot of in terms of I’m going to

975 880 872 733 649

the end of the at the end of is going to be if you want to to be able to

218 195 191 170 167

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PRAGMATICS AND LANGUAGE VARIATION Table 7.7 Continued BASE

two-word

Frequency

three-word

Frequency

four-word

Frequency

6 7 8 9 10

to be sort of if you to the this is

3612 3601 3595 3471 3053

we’re going to this is the if you like you can see and this is

605 509 494 494 492

if you look at in terms of the at the same time the way in which going to talk about

152 136 134 129 123

Finally, and as we pointed out in Chapter 1, individual items such as know and think provide many of the building blocks for longer clusters that are of importance in the interpersonal realm. For example, from Table 7.6 you know has the potential to form a syntactic frame for a six-word PM, you know → do you know → do you know what → do you know what I → do you know what I mean. Do you know what I mean occurs on 104 occasions in LCIE, making it by far the most frequent six-word unit, and on 120 occasions in the Spoken BNC1994 (remember: LCIE is a one-million-word corpus and the Spoken BNC1994 is a ten-million-word corpus). The interpersonal nature of do you know what I mean is evident in extract 7.6 where it acts to mark shared knowledge between speaker and listener(s). (7.6) [Context: Charity committee meeting; speakers numbered in order of appearance in the extract.] But ano= but what I think would happen when we get maybe Mike or Chris or somebody helping, it’s not that they’re taking work off Wendy, but that we will do more physical checks, do you know what I mean, with the stock control. Wendy will do the computer bit and they’ll do the counting bit. That kind of thing. And erm somebody like Mike or Chris is perfectly capable of get their bits of paper to check to tick off things like that but Wendy will have to check it and put it you know they could do some of the legwork but not yet. No. (Spoken BNC1994; File J9P) In this extract we see that does not hand the turn over to but instead keeps talking after the use of do you know what I mean which occurs in turn medial position. Here, the pragmatic function of the PM is slightly different to that in extract 7.5. appears to be discussing the changing of work practices, an often troublesome area in the workplace, and uses the PM to invite to think about what has been suggested. Interestingly, the transcriber has separated the PM from the other utterance comment using commas, which might suggest a short pause on the part of the speaker both before and after the PM. This is due to the fixed nature of the phonology of multi-word units. In other words, these units have to be said quickly in a single intonational unit (O’Keeffe et al., 2007). Therefore, the commas represent the probable need for the speaker to take a breath both before and after the multi-word unit. Do you know what I mean does not

PRAGMATICS AND LANGUAGE VARIATION

appear to receive an immediate verbal response in extract 7.6, although a non-verbal one may have occurred. The importance of the study of pragmatic markers is evidenced by their prominence on spoken corpus word frequency lists. For example, we can see from Table 7.6 that items with the potential to function as PMs such as you know and I don’t know are the most frequent two-word and three-word units respectively. Therefore, corpus word frequency evidence highlights a considerable number of high frequency PMs that play a crucial role in the organisation and management of spoken discourse. In terms of variation, there appears to be some evidence that frequency patterns may be relatively consistent across some varieties of English; Adolphs and Carter (2013), for example, have found that I don’t know is also the most frequent three-word unit in the Spoken BNC1994. These findings have clear implications for pedagogical awareness and intervention strategies. We should be aware of features of naturally occurring speech such as PMs and they should be added to classroom vocabulary lists due to both their frequency of occurrence and their importance to successful interaction (see e.g. O’Keeffe et al., 2007; Martinez and Schmitt, 2012). The tentative finding that there may be some consistency of occurrence with regard to similarity in the frequency of two-word and three-word (or, indeed, six-word) units across different varieties of English is also of potential pedagogic value in that learners can be quickly familiarised with a set number of everyday spoken language routines key to successful spoken interaction across geographical space.

7.4

VAGUE LANGUAGE AND VARIATION

Vague language involves the purposeful use of words or phrases with general meaning to refer to items in a non-specific, imprecise way (see also Chapters 8 and 9). This non-specific, imprecise use of language does not, however, signal that the language user is being, in any way, sloppy or lazy in their use of language; instead vague language has been shown to be highly interactive, prioritising interpersonal involvement above actual explicitness. Vague language can be subdivided into a number of categories, including, but not limited to (see also Channell, 1994): • • •

Vague additives – for example, approximators (about, ish, etc.) and, the focus of this section, vague category markers (and things like that, or whatever, etc.); Lexical vagueness – quantifiers (piles of, a few, etc.) and expressions such as yoke, thingy or whatchamacallit; Vagueness by implicature – ○ ○

A: Can your mother help? She lives nearby. B: She lives nearby but she’s in her seventies now.3

(Speaker A wants Speaker B’s mother to help out domestically but Speaker B implies, through the use of the vague expression she’s in her seventies, that she may not be in a position to help.)

159

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TASK 7.4 IDENTIFYING VAGUE LANGUAGE ITEMS Extract 7.7 is part of the transcript from a cabinet meeting held in the White House on 12 February 2019 (source: https://factba.se/transcript/donald-trump-remarks-cabinet-meeting-february-13-2019). Identify the vague language items used in the extract. (7.7) [Context: = US President Trump.] They’ve already announced, in some cases – and in many cases, they have announced – they’re moving back into the country. They want to be a part of the United States. It’s like a miracle in the United States, what’s happening. But we have a lot of companies that have left. In many cases, they left our country and they’re moving back. And that means a lot of jobs. Speaking of jobs, we have to have more people coming into our country because our real number is about 3.6, 3.7. It took a little blip up during the shutdown and went up to 4. And 4 – any country would take a 4. But we’re about 3.7; probably going lower. We need people. So we want to have people come into our country, but we want to have them come in through a merit system, and we want to have them come in legally. And that’s going to be happening. We’re doing very well in that regard. But we have tremendous numbers of companies. And you’ve been reporting on them. A lot of car companies are coming back to the United States. We want to keep the job boom going strong, and we must protect our economy. (Cabinet Meeting, White House, 12 February 2019)

Similar to pragmatic markers, vague language has, through a process of grammaticalisation, acquired textual and interpersonal functions which are distinct from the items’ original meaning. In order to access vague reference, listeners rely on shared context; therefore, vague language tends to be heavily context dependent. It relies on conversational participants for interpretation and is therefore a strong indicator of shared knowledge and marker of in-group membership. In order to examine pragmatic variation we will focus on a subcategory of vague additives that are referred to as vague category markers (VCMs). VCMs are, typically, a set of expressions, often clause or turn final, that consist of a conjunction, and or or, followed by a noun phrase. VCMs that begin with and are traditionally referred to as adjunctives, whereas those that begin with or are known as disjunctives (see Overstreet and Yule, 1997a, 1997b).4 In order to do this, we take a form-to-function approach and draw upon existing research to identify six frequent examples of VCMs (see e.g. Walsh et al., 2008; Vaughan et al., 2017) and compare them across two corpora: the Limerick Corpus of Intimate Talk (LINT) and the British Academic Spoken English (BASE) corpus. The tokens chosen for analysis are: the adjunctive VCMs (and) (all) (that) kind of thing; (and) (all) (that) sort of thing; (and) (all) (that) type of thing; and the disjunctive VCMs or whatever; or something and or anything. The normalised frequency results for these selected adjunctives are presented in Table 7.8.

PRAGMATICS AND LANGUAGE VARIATION Table 7.8 Comparative frequencies of selected adjunctive VCMs in the LINT and BASE corpora (normalised per million words)

(and) (all) (that) kind of thing (and) (all) (that) sort of thing (and) (all) (that) type of thing TOTAL

LINT

BASE

73 10 2 85

43 83 7 133

Table 7.8 shows that what have traditionally been referred to in the literature as adjunctives are, overall, more common in spoken academic discourse than in the discourse of family and close friends. Vague language in spoken academic discourse has a role to play in the presentation and organisation of knowledge. It may also play a part in inducting students into the community of practice of their chosen discipline. In addition, adjunctives have been shown to be used to invite solidarity and to stress in-group membership and social similarity (see e.g. Overstreet, 1999; Aijmer, 2013). Extract 7.8 demonstrates the use of the VCM and that sort of thing (marked in bold) in BASE. Other vague language items, primarily kind of and sort of, and the PM you know (see Section 7.3) have also been highlighted in the extract. (7.8) [Context: History of art seminar; , , = students; non-student. Speakers numbered according to the order in which they occur in the extract.] thank you and we thought that we we’ve divided his work into sort of periods kind of the first one is has to do with parcels and the whole idea of wrapping things up in a kind of rough manner like across like the bridge here and the and and in a kind of surrealist yeah like that one like wrapping things up and then the second period is all about beauty and that kind of renaissance you know sort of period of beautiful drapery and and monumentality like like that one you see the that’s kind of isn’t it orange yeah yeah it’s sort of islands and that sort of thing so he moves away from the what we have called the parcel era the what parcel era it kind of the parcel era well we we did take it into this he started off by wrapping all sorts of objects anything you know so a cup a can and these are all kind of in in articles like you know later works which you know cost millions and are are are you know are are really being done on a big scale he he we discussed his we we you know his modus oper of you know he has this fixation for wrapping things he likes small things and then he goes on and he starts wrapping like the

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the Chicago museum and it’s just you know it it’s and so and he says oh I’ll just wrap bigger things (BASE: File ahsem007) In extract 7.8 uses the VCM with the noun phrase islands in islands and that sort of thing. The students are discussing the artist Christo (and his later collaborations with JeanneClaude), famous for wrapping everyday objects in fabric in order to turn them into sculptural items. He started with everyday objects such as telephones, but later moved on to larger collaborative projects such as the Reichstag in Berlin and the Pont Neuf in Paris, but also islands and stretches of coastline. In this extract, uses islands and that sort of thing to acknowledge that their fellow students have this shared knowledge and so there is no need to say, for example, islands and the Reichstag and the Pont Neuf and stretches of coastline, as it is assumed that this knowledge is implicit and shared. In doing this, is constructing solidarity, in-group membership and social similarity among their peers. also frequently alternates between kind of and sort of markers that have been flagged to reduce social distance and to express a desire for a relaxed relationship between speakers and listeners (see e.g. Holmes, 1993; Aijmer, 2002). Finally, you know is used on multiple occasions by in the final turn in the extract, where it again clusters with like (see also extract 7.5) on one occasion. On this occasion you know may function in a similar way to the vague items used by in that the speaker may not feel the need to expand specifically on their ideas given the shared knowledge that exists between the classmates (cf. Clancy, 2016).

TASK 7.5 ADJUNCTIVES IN COCA Table 7.9 illustrates the frequency results for the search item * that type of thing in the COCA corpus overall and in the individual spoken, fiction, magazine, newspaper and academic sections. As can be seen, * that type of thing occurs predominantly in the spoken component of COCA, with only one occurrence of the adjunctive in the academic component. This appears to contradict the findings of Table 7.8. Table 7.9 Frequency counts for the item* that type of thing in COCA

1.

How might this apparent contradiction be explained? Pay particular attention to corpus design when considering the answer to this question.

PRAGMATICS AND LANGUAGE VARIATION

In contrast to Table 7.8, Table 7.10 shows that disjunctives are notably more frequent than adjunctives in both the discourse of intimates and spoken academic discourse. Table 7.10 Comparative frequencies of selected disjunctive VCMs in the LINT and BASE corpora (normalised per million words)

or whatever or something or anything TOTAL

LINT

BASE

174 745 269 1188

237 226 53 516

In addition, disjunctives are more than twice as frequent in the speech of intimates as they are in spoken academic discourse. In their study, Overstreet and Yule (1997a, 1997b) found that while adjunctives were present in the conversation of non-familiars, disjunctives were relatively rare. In extract 7.9, the speakers are discussing various liquid nutritional supplements and is searching for the name of a particular brand. offers a range of suggestions, including Ensure, which she states is like a milkshake or something. Here, the or something is used as a mitigator or softener to indicate that there are other, alternative options to what she has suggested and that what she has proposed is not definitive. (7.9) [Context: Two female speakers talking about a sick relative. is in the 40 –50 age group and is in her twenties.]







There’s a few. There’s Complan and then there’s the Build-up. There’s there’s something else like that now. What’s the what’s the name of that one? Ensure There’s Complan or Build-up or Ensure. Ensure like Ensure is like a drink. Like a milkshake or something. Ensure. Ensure or Ensure Plus Sip? Fortisip? What? Fortisip That’s the one. (LCIE)

The disjunctive or something has been shown to function to mark utterance content as inaccurate or approximate, or to indicate alternative options and express tentativeness

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in relation to offers, proposals or requests (Overstreet, 1999; Clancy, 2016). This use of or something as an indicator of the existence of alternative options is supported by ’s continued efforts to remember a particular brand Fortisip which the participants eventually manage to negotiate together. In spoken academic settings there may be a reluctance, especially on the part of students, to indicate inaccuracy, approximation or tentativeness in their spoken interactions, given that their tutors/lecturers may be present and that they might be graded on content. This may account for the lower frequency of the disjunctive VCMs in Table 7.10.

TASK 7.6 DISJUNCTIVES IN COCA Table 7.11 illustrates the frequency results for or whatever in the overall COCA corpus and its component parts. Although the frequency counts appear to support the hypothesis that disjunctives are more frequent in spoken discourse than in academic discourse, there is a much greater frequency difference between or whatever in the spoken and academic components of COCA than is evident in Table 7.10. How might this frequency discrepancy be explained? Table 7.11 Frequency counts for the item or whatever in COCA

Vague language has been extensively studied and markers of vague language are seen as central to everyday, efficient discourse, especially in the case of spoken language (see e.g. Channell, 1994; Cutting, 2007; Cheng and O’Keeffe, 2015; Haselow, 2017). There is a variety of linguistic resources available to speakers to mark formality or informality, closeness or distance, or politeness or impoliteness. Vague language plays a role in all of these social intricacies given, for example, its interpersonal role in softening expressions, marking in-group membership or simply as a representation of a speaker attending to a listener’s needs by not being pedantic. As Carter and McCarthy (2006: 202) remark, vague language should not be viewed as a sign of careless thinking or sloppy expression but rather of the ‘sensitivity and skill’ of a speaker. It is for these reasons that vague category markers have been referred to as ‘exemplars of pragmatic encoding par excellence’ (Vaughan et al., 2017: 212).

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7.5

SPEECH ACTS AND VARIATION

In order to examine speech acts and variation within the same language, we have decided to focus on gratitude. Without dwelling too long on something that we have previously addressed in Chapter 3, the use of corpora in the examination of speech acts has been much debated. However, one certain way of overcoming the form-to-function mismatches that characterise the automatic retrieval of linguistic phenomena such as speech acts from corpora is the use of lexical hooks to search corpora (Rühlemann, 2010; Vaughan et al., 2017; Clancy, 2018; Rühlemann and Clancy, 2018). In the specific case of speech acts, these hooks are often referred to as illocutionary force indicating devices (IFIDs; see Chapters 3 and 6). Therefore, this section will focus on three IFIDs commonly associated with expressions of gratitude: thank, thanks and cheers.

TASK 7.7 SPEECH ACTS AND VARIATION Based on your observations and language intuition, what are the three most commonly used expressions of gratitude in English? Go to the Google N-Gram Viewer (https:// books.google.com/ngrams) and search for these items by typing each of the three, separated by a comma, into the search box. This task can, of course, be done using other languages – this tool allows the user to search a variety of language corpora, such as Chinese, French, German or Hebrew. 1) 2)

How might the results generated from Google N-Gram Viewer, based on your choice of expressions of gratitude, be interpreted? Do they confirm or refute your intuitions about the most commonly used expressions of gratitude?

In order to offer a little rationale for our choice of items, and to respond to Task 7.7, thanks, thank you and cheers were entered into the Google Ngram Viewer (https://books. google.com/ngrams). Without wishing to debate the pros and cons of the use of this corpus tool (see e.g. O’Keeffe 2018), what we can see on an exploratory level from Figures 7.3 and 7.4 is that since approximately the 1980s, thanks, thank you and cheers have been enjoying something of a renaissance in both American and British English, in that their frequency of use has begun to rise. While we freely admit that this chapter is predominantly focused on spoken language and expressions such as thanks or cheers may be used in informal speech contexts, representations of which are not widely contained in the Google books corpus, or, in the case of cheers, may have changed its use as a speech act of toasting to one of gratitude (see Schauer and Adolphs, 2006), neither, to borrow Scott’s (2017) keyword analogy, are we comparing apples with phone boxes. Therefore, in order to examine more thoroughly the results from Figures 7.3 and 7.4, we have compared the frequency of thank, thanks and cheers in the Spoken BNC1994 to the Spoken BNC2014. The counts for thank include thank you, thank you very much and thank you (ever) so much and those for thanks include

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Figure 7.3 Frequency of use of thanks, thank you and cheers in American English, 1800 to 2008

Figure 7.4 Frequency of use of thanks, thank you and cheers in British English, 1800 to 2008

thanks very much, thanks (ever) so much, thanks for that and thanks a million. The frequency counts were generated using Lancaster University’s online Corpus Query Processor or CQPweb interface (https://cqpweb.lancs.ac.uk/).

TASK 7.8 SPEECH ACTS AND VARIATION OVER TIME Table 7.12 presents the frequency results, normalised per million words, for thank, thanks and cheers in the Spoken BNC1994 and the Spoken BNC2014.5 1) 2)

How have the frequency results for the use of the items changed over the 20-year time period between the Spoken BNC1994 and the Spoken BNC2014? Why might this be the case?

PRAGMATICS AND LANGUAGE VARIATION Table 7.12 Frequencies of thank, thanks and cheers in the Spoken BNC1994 versus the Spoken BNC2014 (normalised per million words) Spoken BNC1994

Spoken BNC2014

Item

Frequency

Item

Frequency

thank thanks cheers

512.55 140.95 13.52

thank thanks cheers

348.26 110.92 35.89

As can be seen, Table 7.12 demonstrates that the frequencies for both thank and thanks have in fact dropped, though in the case of thanks not by very much, in the years between the collection of the Spoken BNC1994, completed in 1994, and the Spoken BNC2014, collected between 2012 and 2016. In contrast, the frequency of use per million words of cheers has almost tripled. This approach to the study of variation is admittedly a broad-based one, where all speakers in both corpora have been treated as a homogeneous whole and no variation within the corpora has been addressed, at least not yet, nor have the items been disambiguated for non-gratitude use; for example, We heard loud cheers coming from the stadium or We had Sue to thank for that or She managed it no thanks to them. In order to investigate more closely the possible reasons for these frequency changes, we present the ten most frequent collocates for each of the three items in the Spoken BNC2014 in order to give us a more contemporary picture of the present behaviour of these items. We are, after all, interested in why the use of cheers has increased so dramatically over recent years. Collocation is, as we have described in Chapter 1, an approach to the study of a linguistic item that considers the likelihood of words occurring next to or near one another. The CQP corpus software allows us to generate lists of collocates and accompanies those lists with log-likelihood scores. Therefore, the results for thank, thanks and cheers represent collocation by significance – the higher the log-likelihood score, the stronger the evidence that the items collocating is not purely due to chance. The top ten collocates of thank are illustrated in Table 7.13. The default parameters automatically set by CQP were used for Table 7.13 Top ten collocates for thank in the Spoken BNC2014 Spoken BNC2014 N

Collocate

Log-likelihood

1 2 3 4 5 6 7 8 9 10

you thank much very oh UNCLEAR please thanks okay god

11,603.608 3102.55 1815.444 1593.37 439.593 432.154 389.254 388.794 364.749 345.414

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Tables 7.13 to 7.15 – collocates are within -/+3 items of the node. Punctuation marks have been excluded from the collocation lists for each item but extralinguistic information such as UNCLEAR in Table 7.13 and NAME in Table 7.15 has been included. The collocates of thank reveal quite a lot about the patterns that occur with it. For example, you is the most frequent collocate, the pronoun providing evidence of the interactivity of the item, and is closely followed by much and very. Hence, the fixed phrase thank you very much which is the third most frequent four-word unit in the Spoken BNC1994 (Adolphs and Carter, 2013). We can also see that items such as thank (and, indeed, thanks and cheers) are prone to repetition and reciprocation, as both thank and thanks are collocates. Schauer and Adolphs (2006), for example, have demonstrated how the repeated and reciprocal use of expressions of gratitude can be extended over several conversational turns, as discussed in Chapter 3. Please is also a collocate and, as you might expect, occurs most frequently in the speaker turn that immediately precedes the turn containing thank. There are two response tokens oh and okay (see Section 7.2) – these most frequently precede thank, such as in Oh thank you or Okay thank you. However, I’m okay thank you, while not very frequent in the corpus (there are 12 occurrences), is, nonetheless, an example of a refusal rather than gratitude. Schauer and Adolphs (2006: 129) emphasise the importance of knowing how to politely refuse an offer, suggesting that ‘the ability to express gratitude and at the same time to refuse a proposition is one of the main skills that students might need to possess in a native speaker context’. Table 7.14 demonstrates the top ten collocates for thanks in the Spoken BNC2014. Thanks shares a number of similar traits to thank but there are also some differences that are also worthy of note. Table 7.14 Top ten collocates for thanks in the Spoken BNC2014 Spoken BNC2014 N

Collocate

Log-likelihood

1 2 3 4 5 6 7 8 9 10

for thank much cheers alright okay oh fine ‘m no

473.827 386.088 210.342 205.895 202.285 197.589 192.166 183.963 177.755 166.338

Similar to thank, thanks is prone to repetition and reciprocation and collocates with both thank and also, in this case, cheers (in position 4). There are also other items we first encountered in Table 7.13 such as much, oh and okay. In contrast to thank, for is the most frequent collocate and this item is associated with a range of fixed phrases such as thanks for that, thanks for the heads up, thanks for asking or thanks for getting back to me. There is, of course, evidence of other phrases present in the collocation frequency list, such as the obvious I’m fine thanks. Interestingly, there is no pronoun in the top ten – the item thanks in itself perhaps embodying interactivity due to its inherent informality. Finally, thanks is also

PRAGMATICS AND LANGUAGE VARIATION

associated with the speech act of refusal with no occurring in position 10 – 60 per cent of these occurrences of no directly precede thanks. There are a couple of elements that distinguish cheers from thank and thanks. The first of these is that, as well as being a noun, it has lexical meaning as a verb which means that it can be used with a third person -s. However, the Spoken BNC2014 contains only one example of the use of cheers as a verb. The second element is that it can be used as a toast rather than as an expression of gratitude and we further discuss this in relation to its collocates here. The third element is the frequency issue – as Table 7.12 has shown. In the past 20 years or so the use of thank and thanks has become slightly less frequent, whereas the use of cheers has almost tripled in its frequency of use. The top ten collocates for cheers are illustrated in Table 7.15. Table 7.15 Top ten collocates for cheers in the Spoken BNC2014 Spoken BNC2014 N

Collocate

Log-likelihood

1 2 3 4 5 6 7 8 9 10

cheers thank mate thanks NAME dears bye mm alright guys

41,74.703 318.2 231.132 204.799 89.882 73.992 69.538 52.783 43.368 42.204

Again, Table 7.15 shows these items to be collocates of one another, demonstrating their tendency towards repetition and reciprocity indicating their interactivity. Cheers is its most frequent collocate, though of note here is that within the collocation window of -3 to 3, cheers shows a relatively even spread of frequency across all positions which basically means that cheers does not necessarily show a pattern of immediately preceding or following itself. What is most striking about cheers, in contrast to thank and thanks, is its tendency to collocate strongly with terms of address (see Chapter 5): mate (position 3), NAME (position 5), dears (position 6) and guys (position 10). Of these, dear is a term of endearment, and mate and guys belong in the category of familiarisers; both categories are on the informal end of the cline of terms of address and are used to bring people together through the creation of a shared membership (see Leech, 1999). In Chapter 3 we discussed the methodological approach of using the available metadata from a corpus to drill down into IFIDs such as cheers in order to provide more finegrained analysis. For example, in the Spoken BNC2014, the occurrences of cheers guys and cheers (my) dears, although too few to allow for any type of generalisation, are used predominantly by females in the 19- to 29-year-old age group. The rhyming present in cheers (my) dears is echoed by another phrase present in the Spoken BNC2014, cheers big ears, and is evidence of creative play with language. According to Carter (2004: 108), linguistic creativity and inventiveness is almost always contextually embedded ‘in so far as it pertains to the social relations which obtain between participants’ – the data gathered for the Spoken

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BNC2014 is predominantly from informal speech contexts (Love et al., 2017) or, as detailed on the BNC2014 website, ‘recorded in informal settings (typically at home) and took place among friends and family members’, and, in the case of cheers mate and cheers guys, (my) dears and big ears, the participants appear to be on a mainly similar sociocultural footing.

TASK 7.9 CHEERS AND SOCIOLINGUISTIC VARIATION In the Spoken BNC2014, cheers mate occurs 20 times. Access the concordance lines using the CQPWeb interface and, using the corpus metadata, determine the predominantly gender, age and socioeconomic bracket of the users of this phrase. Finally, it should also be noted that in Table 7.15 cheers collocates with bye and this connection, also noted by Schauer and Adolphs (2006), is a problematic one and highlights the challenges associated with the corpus pragmatic analysis of IFIDs as well as pragmatic annotation (see Chapters 3 and 6). In the case of cheers, it can be difficult to ascertain whether it is an expression of gratitude or a discourse marker signalling leave-taking. This does, however, point towards the possibility of cheers being involved in three different speech act types: toast, gratitude and leave-taking. This, coupled with cheers’ tendency towards heightened interactivity, as evidenced through its collocating with terms of address, and with the spoken language characteristic of the Spoken BNC2014 (see Love et al., 2017), may account for its rise in frequency in Table 7.15. Indeed, we might speculate that the data collection devices, personal smart phones utilised for the Spoken BNC2014, allowed for more interactivity given that smart phones are far less intrusive than the devices employed as part of the collection of the demographically sampled component of the Spoken BNC1994. The rise in frequency of use of cheers does, however, again raise a core issue in this chapter – different varieties of the same language have different strategies, both linguistic and non-linguistic, at their disposal in order to accomplish successful pragmatic interaction. However, what emerges from the chapter, and intralingual pragmatic research in general, is that users of different varieties have different perceptions of which strategy is appropriate in which situation.

7.6 FURTHER READING Aijmer, K., 2013. Understanding Pragmatic Markers: A Variational Pragmatic Approach. Edinburgh: Edinburgh University Press. In her book, Aijmer marries the traditional subset of pragmatic markers – items such as well, actually or in fact – with the more recent approach of variational pragmatics, i.e. pragmatic variation at a macro- and micro-level. Therefore, the book focuses on variation in pragmatic markers at varietal, text and activity level. Using the ICE suite of corpora, Aijmer demonstrates how the examination of PMs at these levels broadens our understanding of the categorisation and function of these key pragmatic items.

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Flöck, I., 2016. Requests in American and British English. Amsterdam: John Benjamins. This volume examines the use of request strategies across both cultural and methodological dimensions. From a cultural point of view, the structure of request strategies is compared in naturally occurring conversation in British and American English. From a methodological pint of view, these strategies are compared in non-elicited data in the form of ICE-Great Britain and the Santa Barbara Corpus of Spoken American English and elicited data in the form of DCTs (see Chapter 2). The validity of the current use of DCTs as a method of collecting data for pragmatic research is challenged, and suggestions aimed at modifying and improving this data collection technique are posited. McCarthy, M., 2015. ‘Tis mad yeah’: Turn openers in Irish and British English. In C. Amador-Moreno, K. McCafferty and E. Vaughan (eds), Pragmatic Markers in Irish English. Amsterdam: John Benjamins, pp. 156–175. This chapter demonstrates how corpus linguistics can be used to highlight the important connection between the turn-taking system and its pragmatic function. Building on his (2002) work in relation to single-word lexical response tokens in British and North American English, McCarthy encourages the broadening of what are traditionally considered pragmatic markers to include turn-initial, non-minimal lexical response tokens such as right, lovely, grand, etc. What emerges is that varieties of English share much in common in terms of the items that realise pragmatic functions at turn openings; however, each variety does show a preference for a distinct core of items at initial position in the turn. Vaughan, E., McCarthy, M. and Clancy, B. 2017. ‘Vague category markers as turn final items in Irish English.’ World Englishes, 36(2), 208–223. Although the title suggests a focus on one variety of English, this article compares intimate corpus data from Irish and British English. In particular, the focus is on vague category markers – (and) things/stuff (like that), and/or whatever, and so forth – which have been identified in the previous literature as frequently occurring. These items are then used as linguistic hooks to search the corpora. The findings show that VCMs in final position frequently trigger speaker change but that their use as a trigger is more common in British English than in Irish English which tends to favour more traditional pragmatic markers such as like and you know in turn final position.

NOTES 1 The term ‘architecture’ is attributed to the work of Seedhouse (2005). 2 Throughout the book, we mostly refer to these items as multi-word units. However, in the WordSmith Tools software, these items are referred to as clusters. 3 Example adapted from Cheng and Warren (2003). 4 Vague category markers have also variously been referred to in the literature as general extenders (Overstreet and Yule, 1997a, 1997b), generalised list completers (Jefferson, 1990), tags (Ward and Birner, 1993), terminal tags (Dines, 1980), extension particles (Dubois, 1993), vague category identifiers (Channell, 1994) and vague extenders (Stubbe

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and Holmes, 1995; Cheshire, 2007; Tagliamonte and Denis, 2010; Parvaresh et al., 2012; Parvaresh, 2018). 5 These frequency differences are statistically significant. To check the statistical significance of comparative frequency results, an online tool such as the ‘Log-likelihood and effect size calculator’ (http://ucrel.lancs.ac.uk/llwizard.html) can be used.

CHAPTER 8

Pragmatics and variation at the level of register

8.1 PRAGMATICS AND VARIATION AT THE LEVEL OF REGISTER In this chapter we will explore the notion that specific registers involve the use of language in pragmatically specialised ways. To support this idea, we will draw upon real language from different contexts, such as casual conversation, healthcare communication, crime fiction, service encounters and drama in the form of Shakespearean tragedy. Chapter 7 looked at variation within the same language and focused on the use of pragmatic phenomena such as speech acts, pragmatic markers, etc. in different varieties of English. This chapter takes a similar approach in that it investigates variation, but where it diverges from Chapter 7 is that it takes the notion of register as its starting point and employs a corpus linguistic approach to examine the pragmatic features that are characteristic of these specific situations. We need to consider a number of aspects in order to delineate a certain type of language use as specific to a particular spoken or written register. The term register, from Halliday (1978: 31–32), refers to the ‘very simple and very powerful [.] fact that the language we speak or write varies according to the type of situation’. Register, and the concept of variation at this level, is primarily associated with the work of Douglas Biber (e.g. Biber, 1988, 1995; Biber et al., 1999; Biber and Conrad, 2009). Registers are defined ‘according to their situations of use’ (Biber et al., 1999: 135). Therefore, when we consider the description of registers, we need to examine characteristics such as purpose, topic, setting, etc. (see Table 8.1). The study of variation at the level of register is distinct from the study of linguistic variation between speakers living in different geographical regions or in particular social groupings. There is a constant need for both speakers and writers to move competently between registers, regardless of whether they are using, for example, British or American English. Registers are generally described in terms of their characteristic lexico-grammatical features (see e.g. Biber, 1995); however, some of the linguistic features that characterise pragmatics in use, such as backchannels, pragmatic markers or vocatives, extend beyond the realm of traditional lexico-grammatical description. Corpus pragmatics can be used to identify these characteristic pragmatic features given that the field fulfils the three requirements of comprehensive register study: a large number of texts, the consideration of a wide range of linguistic features and the need for comparison across registers (Biber, 1995). The concept of comparability is core to this chapter, as it is to the corpus linguistic endeavour in general; that is to say, we can only gauge that something is different, or special, by comparing it. Using corpora and corpus linguistic tools, service encounters can be compared with casual conversation, crime fiction with theatre plays, and so on. This allows us to connect the functional characteristics of linguistic items with their situational characteristics.

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Finegan and Biber (1994) and Biber et al. (1999: 15–17) provide a useful matrix for the major distinctions between the situational characteristics which distinguish registers from each other (see Table 8.1). When looking at variation in any context, it is worth attempting to complete this matrix. We use the examples of two specific discourse domains that feature in this chapter by way of illustration: service encounters, which traditionally involve one person (a vendor, clerk, waiter, etc.) providing a service or goods for another (customer) and crime fiction. Table 8.1 Identifying characteristics of situational variation (based on Biber et al., 1999: 15–17) Register characteristic

Service encounter

Crime fiction

Mode Interactiveness and online production Shared immediate situation

spoken spontaneous but with a degree of advanced planning the shop/restaurant/post office/hairdresser/etc. transactional public local

written (+ written dialogue) none (restricted to fictional dialogue) none

Main communicative purpose Audience Dialect domain

entertainment/pleasure public regional/global

TASK 8.1 IDENTIFY THE REGISTER CHARACTERISTICS Using Table 8.1 as a template, identify the register characteristics of a telephone helpline. Examining a register under these headings allows us to provide a comprehensive linguistic description of one register in comparison to another. In this chapter, we combine the study of the situational characteristics as outlined in Table 8.1 with a corpus linguistic methodology in order to unearth patterns of pragmatic features that are characteristic of a particular register. In Section 8.2 we blend corpus linguistics and conversation analysis with pragmatics to look at variation at the level of speaker turn and sequences of turns. In Section 8.3 we examine the usefulness of corpus tools such as keywords in exploring the salient pragmatic features of, for example, English language teacher meetings, the novels of Arthur Conan Doyle, service encounters and Shakespearean tragedy.

8.2

COMPARABILITY AT THE LEVEL OF TURNS

In exploring the pragmatics of language in specific contexts, we can compare variation in a number of ways. The first of these is structural and, therefore, here we turn to the work of conversation analysts. Conversation analysis (CA) is a research tradition that has grown out of ethnomethodology, an area within sociology rather than linguistics. Researchers such as Sacks, Schegloff and Jefferson have, since the 1970s, contributed to, and strongly influenced, research into the structures underlying face-to-face interaction (e.g. Schegloff, 1968; Sacks et al., 1974; Schegloff et al., 1977; Sacks, 1992).

PRAGMATICS AND VARIATION AT THE LEVEL OF REGISTER

Conversation analysis (CA) Fundamental to the CA approach is that conversation typically involves more than one person and people take turns at talking; therefore, the notion of the speaker turn is key. Distinct from, say, the canonical approach to the study of speech acts (see Chapter 6) which considers one utterance, or turn, and assigns it a label such as request, promise or greeting, CA considers one speaker turn in light of the turn that preceded it and those turns which follow. Therefore, a turn is part of the intricate architecture (Seedhouse, 2005) of casual conversation and CA is concerned with unravelling the structures and patterns underlying our everyday spoken interaction. Grice (1989) states that conversation is essentially a cooperative endeavour (see Chapter 6), and CA has shown this to be the case as turn-taking systems generally adhere to a number of patterns. 1. 2.

3. 4.

One speaker tends to speak at a time – they are said to have the conversational floor while speaking; A speaker turn typically has three parts – a turn preface (or pre-start), a turn construction unit (TCU) and a post completer (typically a tag question, vocative, pragmatic marker, etc.); The other conversational participants orientate themselves to the conversational floor using this three-part structure; Listeners employ their knowledge of grammatical and prosodic patterns in order to predict what is known as a transition relevance place (TRP) within a TCU. When a TRP is reached, an intricate process of speaker change is triggered.

In extract 8.1, has the conversational floor and her pre-start (Sacks et al., 1974: 719) I mean acts as a turn preface that signals this turn’s relation to the prior turn in some way. (8.1)

I mean unbelievable actually I mean it was unbelievable as a simple memory exercise you know. (BNC Spoken 2014: File S263)

After the TCU comes to a finish with the item exercise, signals a possible TRP using the pragmatic marker you know. The process of speaker change can occur in a number of different ways. For example, the current speaker may select the next speaker through the use of, say, a vocative. Alternatively, the next speaker in the sequence may self-select or, if there is silence after a speaker turn has been completed and no one takes the floor, then the current speaker may retake the floor. Although this process of turn transition commonly occurs with remarkable precision (Rühlemann, 2019), both overlapping speech, a timing issue where a speaker fails to adequately predict a TRP, or interruption, an aggressive move to seize the conversational floor where a speaker ignores or refuses to recognise a TRP (Cameron, 2001), can take place. Turn sequencing is also organised based on what is known as a preference system. The smallest of these turn sequences is what is known as an adjacency pair. In this

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sequence type, the second turn in the sequence is ‘not just related to the first but functionally dependent on it’ (Cameron, 2001: 96). Take, for example, extract 8.2. (8.2) yeah so would you like to sit over here or there? I’ll sit here. (BNC Spoken 2014: File S7RW) This extract illustrates the question–answer adjacency pair where the first turn, in the form of a question, receives the preferred response, in the form of an answer to that question. In other canonical adjacency pairs the preferred response to a greeting is a reciprocation of a greeting, the preferred response to a proposal is an acceptance, and so on. Participants do, however, have the option of providing the dispreferred response. For example, a question might be answered by another question, a greeting by a non-reciprocation and a proposal by a refusal. The dispreferred response (marked in bold) has implications in terms of turn structure, as is evidenced in extract 8.3. (8.3) yes but then once you ’ve seen it on the television you might sa- well I’ve seen it on the television now so I don’t need to bother to go and spend the two thousand pounds to do it myself now so it could save you a lot of money well I’m not sure about that I think seeing on the television is one thing and going is quite another thing I don’t think you get the thrill and the experience no of the erm no I don’t rail travel no and the places that you see which presumably will be very idyllic (BNC Spoken 2014: File SAXQ) This turn sequence begins with an assertion, the preferred response to which is agreement. However, responds with the dispreferred response of disagreement marked with the turn preface well I’m not sure about that. This triggers a much more complex sequence than that evident in extract 8.2, with offering a very detailed account for the dispreferred response over a number of turns. Sequences are, of course, not limited to adjacency pairs. Corpus pragmatic studies have investigated extended sequences in co-constructed casual conversation (see Clancy and McCarthy, 2015), conflict talk (see Clancy, 2018) and narratives (see Rühlemann and Gries, 2015; Rühlemann, 2019).

TASK 8.2 CONFLICT SEQUENCES AND TURN STRUCTURE Examine the following conflict sequence, characterised by at least three consecutive turns where speakers mutually challenge one another, between two intimates (intimates

PRAGMATICS AND VARIATION AT THE LEVEL OF REGISTER

are either family members or close friends). Conflict sequences are also characterised by dispreferred responses. (8.4)









1) 2)

yeah but it’s still (.) you probably don’t need to clean it that much do you? no but you don’t need to clean it you do need to clean dishwashers you don’t yes you do you don’t that’s why they have the dishwasher tablets and stuff as well for cleaning you just put it in and it’s done I know it cleans the dishes but you do need to clean that as well no you do you’re lying (.) you’re a liar you’re a liar oh rude you’re a liar >> well you’re a liar what? straight up do I care? (Spoken BNC2014: File S5MM)

What is the structure of the turns in extract 8.4? How does this structure differ from, say, the prototypical turn structure in extract 8.1 or the example of a dispreferred response in extract 8.3?

In sum, CA takes a ‘bottom-up’ approach to the study of the social organisation of conversation by means of a detailed inspection of transcribed recordings of specific situations. Essentially, it focuses in on how conversations are structured locally by looking at them in micro-detail, turn-by-turn and, from this, inductive comments are made about these structures. McCarthy (1998) notes that CA offers the possibility of fine-grained descriptions of how participants orient themselves towards mutual goals and negotiate their way forward in highly specific situations. Such highly specific situations are usually socially defined, such as the beauty salon (LeBaron and Jones, 2002) or the post office (McCarthy, 2002), or institutional settings such as courtroom interaction (Atkinson, 1979; Atkinson and Drew, 1979), doctor–patient interactions (Maynard, 2003; Maynard and Heritage, 2005), radio phone-in calls (Hutchby, 1991) or emergency phone calls (Whalen and Zimmerman, 1987; Tracy, 1997; Tracy and Anderson, 1999).

Conversation analysis and pragmatics The CA tradition of establishing the canonical turn sequence of an interaction (i.e. the most typical sequence of turns) is very fruitful from a pragmatics perspective and can be used as a means of comparison for other types of spoken interaction. For example, in order to examine a telephone call opening, a conversation analyst will always begin by looking at the turn sequence for call openings. Let us take as a case study CA work focusing on

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telephone call openings (see e.g. Schegloff, 1968, 1986; Godard, 1977; Halmari, 1993; Hopper, 1989, 1992; Sifianou, 1989; Hopper et al., 1991; Whalen and Zimmerman, 1987; Cameron and Hills, 1990; Hutchby, 1991, 1996a, 1996b, 1999; Drew and Chilton, 2000). Essentially, telephone openings in different settings can be compared in terms of their turn sequences. First a norm had to be established; that is, a sequence of turns which is seen as the canonical structure. Schegloff (1986), for example, characterised the canonical structure for a phone call opening between ‘unmarked forms of relationships’ (that is, those who are not particularly intimate but who are not strangers) as having the following structural organisation. (8.5) [Context: Canonical call opening between ‘unmarked forms of relationships’ (Schegloff, 1986; Drew and Chilton, 2000).] Summons–answer Identification–recognition

Greetings ‘How are you?’ sequences

First topic

0. Phone rings 1. Answerer: 2. Caller: 3. Answerer: 4. Caller: 5. Answerer: 6. Caller: 7. Caller: 8. Answerer: 9. Caller: 10. Answerer: 11. Caller:

Hello Hello Jim? Yeah ‘s Bonnie Hi Hi How are yuh Fine, how’re you Oh, okay I guess Oh okay What are you doing New Year’s Eve?

Based on this as the canonical sequence, we can then compare other call opening sequences. For example, Whalen and Zimmerman (1987) present the following as the typical sequence of call openings between strangers on an emergency phone line. (8.6) [Context: Call openings between strangers (Whalen and Zimmerman, 1987; Hopper and Drummond, 1992: 191).] Summons–answer Business of call

0. Phone rings 1. Answerer: 2. Caller:

Mid-city Emergency Um yeah. Somebody jus’ vandalised my car.

By comparing this institutional interaction with the canonical baseline from Schegloff (1986), we see that there is an attenuation of the stages because the relationship and setting are different. There is no identification–recognition phase, nor do caller and answerer engage in ‘how are you?’ sequences. In CA terms, we can then say that this

PRAGMATICS AND VARIATION AT THE LEVEL OF REGISTER

reflects the institutional organisation of talk in this context of interaction. In pragmatic terms, we could say: • •

•

•

Because of the institutional nature of the interaction, the imperative of politeness norms is not as strong; The pragmatic norms of the situation do not call for the reciprocation of greetings and first names, nor the ‘how are you?’ small talk, which is one of the expected politeness routines between people who know each other in many English-speaking cultures; The institutional context of the call is initiated by the call answerer’s use of an institutional identity at the identification stage. The answerer is defining the pragmatic space between the caller and the answerer as institutional (compare ‘Mid-city Emergency’ with something like ‘This is John, Mid-city Emergency, how can I help?’); The highly institutional, non-personal nature of the opening turn appears to affect the caller who is unsure of how to begin his or her account to this unnamed, ungreeted person on the other end of the line (the caller begins his or her turn with the hesitation, Um yeah).

Another comparison is provided by Drew and Chilton (2000), who look at call openings between intimates, drawing upon a corpus of calls made between a mother and daughter over a two-month period. Most of these calls are for the purpose of ‘keeping in touch’; in other words, there is normally no express purpose for calling other than to maintain contact. (8.7) [Context: Call openings between intimates (Drew and Chilton (2000).] Summons 0. Phone rings Answer + Identification–recognition + 1. Answerer: Hello Greetings (‘How are you?’ also possible) 2. Caller: Hello 3. Answerer: Oh hello First topic 4. Answerer: I’ve been waiting for you Again here we see attenuation of call stages when compared with Schegloff’s canonical or baseline sequence in extract 8.5. It is similar to the pattern for emergency calls between strangers though for different reasons. As Drew and Chilton point out in CA terms, the relationship of the callers allows for the attenuation of the canonical stages because the callers are intimates (they know each other well), and because they are expecting the call. The voice sample provided by Hello is immediately recognised by the answerer and achieves all Schegloff’s stages of answering, identification–recognition and greeting in this interaction. From a pragmatic perspective we could say that: • •

The intimate relationship of the family members is a given, to such a degree that it obviates the need for norms of positive politeness such as name and greeting reciprocation; Unlike the emergency call interaction in extract 8.6, the lack of first name and greeting reciprocation does not create any face threat for the caller or answerer. This is a pragmatically specialised norm in this routine interaction between intimates.

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TASK 8.3 ANALYSING THE PRAGMATICS OF TELEPHONE CALL OPENINGS Read extract 8.8, an extension of extract 6.3, the opening of a call to the NHS Direct helpline. (8.8) 1. [phone ringing] 2. NHS advisor:

3. 4. 5. 6. 7. 8. 9. 10. 11.

Caller: NHS advisor: Caller: NHS advisor: Caller: NHS advisor: Caller: NHS advisor: Caller:

12. NHS advisor:

Good evening. This is NHS Direct. My name’s [name]. I’m a health advisor here. Could I just start by taking your telephone number please? [personal details removed] Okay. How can I help then [name removed]? Right. I went to see the doctor yesterday. Mm. I’ve got erm what they’re calling a middle ear infection. Yeah. Erm it’s a new doctor cos I’ve erm recently moved into the area. Mhm. Erm when I’ve been before [pause 0.5 sec] I’ve been prescribed something different. This time she’s given me antibiotics and basically the problem is that I’ve collected them. I’m a bit worried about taking them cos I’m not actually sure if I might be pregnant and erm obviously I I know about [inhales] you know not taking medication when you’re pregnant. So I just wanted to really check what I could do and really whether I should be taking antibiotics anyway with [inhales] you know all these things about you’re not supposed to take them unless you really need them. Yeah. Okay. Erm [pause 1 sec] okay. Best off that you talk to a nurse about this. Right. Er so you’ve got a middle ear infection. Yeah. What you been prescribed then? Augmen= Aug= Augmentin? Something. Yeah. Yeah. Yeah. Something like that. [laughs] Yeah. It’s Augmentin. That sounds about right yeah. (NHS Direct corpus)

13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23.

Caller: NHS advisor: Caller: NHS advisor: Caller: NHS advisor: Caller: NHS advisor: Caller: NHS advisor: Caller:

1)

Consider the CA interactions that you have just examined and label the structural organisation of the call opening. Consider the call from a pragmatic perspective in comparison with extracts 8.5 and 8.7. How might any similarities and/or differences be explained from this perspective?

2)

PRAGMATICS AND VARIATION AT THE LEVEL OF REGISTER

Conversation analysis, pragmatics and corpus linguistics In order to examine the interface between CA, pragmatics and corpus linguistics, let us look at the NHS Direct corpus and compare its 20 most frequent words with those of the Spoken BNC1994 in Table 8.2.1 Table 8.2 Comparison of the top 20 most frequent words in the NHS Direct corpus and the Spoken BNC1994

1 2 3 4 6 7 8 9 10 11 12 13 14 15 16 18 19 20

NHS corpus

Spoken BNC1994

you I the yeah and right it to a okay erm it’s of know that er just is

the I you and it a ‘s to of that n’t in we is do they er was

What is immediately striking is the high number of the response tokens yeah, right and okay (marked in bold) in the NHS Direct data. This reflects the institutional nature of the helpline interaction as well as the mode (see Table 8.1); that is, the telephone. In addition, because there is a high degree of information-seeking and information-giving, there is, as a result, a high number of response tokens in this particular register. In particular, we see a high number of ‘information receipt’ response tokens (see O’Keeffe and Adolphs, 2008), typically right, which acknowledge the receipt of information from the institutional power-role holder. The fact that the mode of communication is audio only means a higher reliance on response tokens so as to keep the channel of communication open and to work through the caller’s problem as smoothly as possible by incrementing from identifying the problem through symptoms to giving appropriate advice to the caller as evidenced in extract 8.9. (8.9) Advisor: And I understand you’ve got a rash? Caller: Yeah. Yes. Erm [0.5 second pause] and first noticed it really quite how bad it had got last night when I came round my friend’s house for a shower.

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Advisor: Right. Caller: And erm it’s sort of round my waist round about the waistband of my trousers and it’s kind of worked its way up the sides erm [1 second pause] er sort of towards my armpits on on both side. [inhales] Advisor: Right. Caller: Erm and erm I’m wondering what could be wrong. [exhales] Advisor: Right. Okay. Central to the process of successfully expediting the call through its phases is the very careful monitoring of new information between advisor and caller. Both the caller and the advisor mark the understanding of new information through frequent use of response tokens. The caller’s uncertainty in the role of non-expert is indexed by the use of the hesitation devices erm (extract 8.10) and er (extract 8.11), both of which feature in Table 8.2. This non-expert role is further examined in relation to the use of vague language in Section 8.3. (8.10) Advisor: He’s not had any diarrhoea that you know of? Caller: inhales Erm no. His stools were a little bit loose but nothing you know. (8.11) Advisor: What about painkillers? Caller: inhales Er well I had some sort of on the Saturday but I’ve not not really had any since. Building on Table 8.2 and extracts 8.9 to 8.11, one of the most productive avenues for the investigation of the intersection of corpus linguistics, pragmatics and CA has been turn initial items, including, but not limited to, pre-starts (see e.g. Tao, 2003; Vaughan, 2009; Evison, 2013a, 2013b; Clancy and McCarthy, 2015; Clancy, 2016). Researchers have identified a range of turn initial items that are more frequent in one register than in another. For example, Evison (2013a, 2013b) demonstrates that the turn initial items such as mhm, yes, right and okay are more frequent in academic talk than in casual conversation, and argues that these items have a fundamental role in marking this talk as ‘academic’. Corpus pragmatic research in this area is characterised by a similar methodological approach to the identification of turn initial items – corpus mark-up items (see also Section 8.3) such as speaker tags (, , etc.) are used as search items to generate concordance lines and then these lines were sorted one to the right of the tag to identify the turn initial item, as demonstrated in Figure 8.1. In Figure 8.1 we see the presence of a number of response tokens such as oh (line 13), right (line 14), umhum (line 19) and yeah (lines 21–24), but it is also apparent that many turns do not begin with a response token but with, for example, a conjunction (e.g. but (lines

PRAGMATICS AND VARIATION AT THE LEVEL OF REGISTER

Figure 8.1 Sample of concordance lines for as search item from LCIE (sorted 1R)

4–5)), a question word (e.g. how (line 9)) or a pronoun (e.g. they (line 18)). This opens up the possibility that turn initial items can be used in the characterisation of different registers.

TASK 8.4 EXPLORING THE INTERFACE Table 8.3 compares the top 20 most frequent turn initial items in two corpora: English language teacher meetings (C-MELT) and casual conversation between family and close friends (LINT). Table 8.3 Comparison of top 20 most frequent turn initial items in C-MELT and LINT

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

C-MELT

LINT

YEAH I/’M/’LL/’VE/’D AND BUT NO MM OKAY SO OH [NAME] UM HMM RIGHT THAT/’S WELL IT/’S THEY/’LL/’VE/’RE

YEAH I/’D/’M/’LL/’VE OH NO AND WHAT/’D/’LL/’S IT/’D/’LL/’S YOU/’D/’LL/’RE/’VE THAT/’D/’LL/’S HE/’D/’LL/’S AH BUT SHE/’D/’LL/’S THE WELL THEY/’D/’LL/’RE

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17 18 19 20

C-MELT

LINT

WE/’LL/’RE/’VE/’RE THE YOU/’LL/’VE/’RE BECAUSE

IS DO DID SO

We can clearly see the similarities between the language of meetings and that of family and close friends – a comparison only made possible through the application of a corpus methodology: • • • •

1)

Both lists contain initiators such as yeah, no, so, but, well and and, demonstrating their importance in many different registers; The pronouns I and you and the demonstrative that feature prominently on the two lists; C-MELT contains the pronoun we and the syntactically independent items mm, okay, um hmm and right; LINT is distinct from C-MELT with the syntactically dependent items he, she, is, do and did (all shaded) unique to this particular dataset. How might the similarities and differences between the two registers be explained from a pragmatic perspective?

8.3 OTHER METHODS OF COMPARING REGISTERS USING A CORPUS In addition to looking at the connection between the structural features of spoken language and their connection to the study of pragmatics in use, corpus tools are also a very useful means of identifying and analysing other pragmatic characteristics of particular registers, including written ones.

Keyword analysis The process of keyword analysis and its importance to the study of a corpus has been explored in detail in Chapter 1. Table 8.4 illustrates the top 20 keywords for the NHS Direct corpus, using LCIE as a reference corpus, and these results consolidate the high use of the response tokens right and okay (and mm) as discussed in Section 8.2. Also worth exploring are the keywords sort (in position 5) and bit (in position 13). On searching the corpus we find them used frequently by callers when describing their symptoms. They use the multi-word units sort of and a (little) bit as vagueness markers to downtone or hedge the directness of presenting a fact about their symptoms (see also Chapter 5 on hedges and Chapter 7 on vague language). Figure 8.2 illustrates a selection of unsorted concordance lines with sort of as the search item. We also find just used as a vagueness marker in the same way and just often co-occurs with sort of (marked in bold in extract 8.12).

PRAGMATICS AND VARIATION AT THE LEVEL OF REGISTER Table 8.4 Keywords of NHS Direct corpus with LCIE as reference corpus 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

right okay mm antibiotics sort diarrhoea it’s nurse bye any I’ve rash bit your just teeth help infection augmentin advisor

it out the window in a minute. I mean I sort of feel like I could probably manage who said that I should you know cos I sort of er said ``Well I can’t ring the Well it er no because I’d sort of I’d hadn’t the doctor didn’t ask nd you know the girls at work I mean I’ve sort of started a new job and they’re all sort the lunch time laughs dose he sort of sort of s= half spat back and half r well when it’s gonna come it sort of it feels a little bit like a you. +but as soon as I’ve been it sort of goes. So it’s just sort of inhales starting to get erm get sore you know it sort of feels a little bit + if it’s an outer ear although it’s sort of like in your ear+ Mm. No. I mean in some bits of the rash it’s sort of slightly raised but er aside from that+ +but as soon as I’ve been it sort of goes. So it’s just sort of inhales les Yeah. But it’s it’s red. It’s sort of you know itchy red. Yeah. extends following syllable Mm. It’s sort of m= more central but a bit across if you diarrhoea look like? It’s just sort of watery and runny and you know. Figure 8.2 Concordance extracts of sort in the NHS Direct corpus (unsorted)

(8.12) Advisor: Right. Okay. Right. So you’re getting pain or discomfort. Whereabouts? Is it below your belly button? Caller: Yeah. Advisor: Right. Is it in the centre or to one side or right across? Caller: Mm. It’s sort of m= more central but a bit across if you know what I mean. It’s just sort of. It’s not just directly in a line down+

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Advisor: Okay. Caller: +the middle it’s just sort of the general if you stick your hand on the middle of your tummy and that area that’s sort of where it is. Advisor: Right. Does the pain move around? Caller: No. It’s just that just that area. It doesn’t+ Advisor: Right. Caller: +you know. Advisor: Is it like a contraction or is it a stabbing pain? How would you describe it? Caller: Erm [blows out air] well when it’s gonna come it sort of it feels a little bit like a contraction when it’s gonna come I suppose. You know+ Advisor: Right. Caller: +that sort of ooh you know…But the rest of the time it’s just sort of like a dull. (NHS Direct corpus) Extract 8.12 also highlights that bit clusters with another keyword in Table 8.4, it’s (the software treats contracted words as single items) in the description of caller symptoms. We can say that this is a pragmatically specialised usage – when callers are talking about their health problems and symptoms to health professionals, they frequently do so using vague language markers as a hedging device due to their status as non-experts. Keyword analysis also unearths pragmatic patterns in C-MELT (see Vaughan, 2008). When we do a keyword analysis, using LCIE as the reference corpus, we find the results as displayed in Table 8.5. Table 8.5 Keywords of C-MELT with LCIE as reference corpus 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

KET PET students semester class exam we English classes think certificate elementary book pass semesters they intermediate okay pre TOEFL

21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

so kind laughter1 mean maybe sufficient2 grammar insufficient weak level university if materials move3 module inter4 could student yeah post

Notes 1. 2. 3. 4.

Laughter refers to where laughter has been noted as an extralingustic feature. Sufficient, insufficient, level and weak relate to the context of level of attainment and exam results. Move relates to moving students to higher or lower level classes, i.e. student placement. Inter and post refer to intermediate and post PET level respectively.

PRAGMATICS AND VARIATION AT THE LEVEL OF REGISTER

Table 8.5 demonstrates that, as would be expected, there are many words relating to the business of English language teaching, such as reference to the international English language exams KET (Key English Test), PET (Preliminary English Test) and TOEFL (Test of English as a Foreign Language), references to student(s), semester, class, exam, certificate, book, grammar, and so on. When we take away all of these content words relating to the ongoing work of being a teacher, we are left with the 11 items listed in Table 8.6. Table 8.6 Keywords, minus content items, of C-MELT with LCIE as a reference corpus we think they okay so kind mean maybe if could yeah

1 2 3 4 5 6 7 8 9 10 11

It is these words, then, that will offer most insight into the pragmatics specific to this register. The keyword we indexes a predictable sense of team identity among the teachers but when the concordance lines are examined we find that we has some specialised uses and patterns that relate to the pragmatics of this specific register. We can be used as a means of proffering opinion in the meeting in a way that does not threaten the cohesion and harmony of the team (see also Chapter 5). Extract 8.13 features an example of the pragmatically specialised use of we in the C-MELT corpus. (8.13) Teacher 1:

Teacher 2: Teacher 1:

All I’m saying is that we are you know we are going a lot slower than than they have recommended for this book. And I’m not saying that’s that that’s wrong because maybe within our context it might be what we have to do when you consider that three weeks at least out of each semester. Is lost. Are lost.

As we can see in extract 8.13, a colleague is making a critical point which might be face-threatening to colleagues. She uses we (and our) to present this in a collaborative way to express it as our problem. The near repetition of teacher 2’s turn (Is lost) indicates convergence and agreement rather than disagreement on the part of her colleague. Most often, uncontentious issues such as student levels, curriculum, scheduling and student-related matters are presented and discussed with a low degree of hedging compared to more sensitive and face-threatening matters relating to the teachers as individuals or as a group (especially when referred to by their Director of Studies).

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TASK 8.5 EXPLORING KEYWORDS AND THEIR CONNECTION TO PRAGMATICS Table 8.6 also shows maybe as a keyword in C-MELT. Figure 8.3 illustrates a sample of concordance lines for maybe + we in C-MELT.

Figure 8.3 Sample concordance lines for maybe + we in C-MELT (unsorted)

1) 2)

What are the patterns associated with the use of maybe + we? How might these patterns be connected to, for example, politeness strategies (see Chapter 5) employed by the teachers?

Multi-word units Another avenue of exploration when examining the pragmatics of language in specific registers is to look at how words combine and form fixed pragmatic units. We employed the use of this corpus tool in order to explore, for example, the differences between British English spoken and written academic discourse and Irish English casual conversation in Chapter 7. In this section, we move away from the analysis of spoken language in order to analyse two written registers: crime fiction, represented by the novels of Arthur Conan Doyle’s iconic detective Sherlock Holmes, and drama, represented by Shakespeare’s suite of tragedies. Our first step is to build two corpora. The Sherlock Holmes corpus consists of four novels – A Study in Scarlet, The Sign of Four, The Hound of the Baskervilles and The Valley of Fear – and is c. 205,000 words in size. The second corpus contains ten of Shakespeare’s tragedies – Titus Andronicus, Romeo and Juliet, Julius Caesar, Hamlet, Othello, King Lear, Macbeth, Timon of Athens, Anthony and Cleopatra and Coriolanus – and is c. 248,000 words in size. These texts are out of copyright and therefore freely available to download from the internet on sites such as Project Gutenberg (www.gutenberg.org/) or the Oxford Text Archive (http://ota.ahds.ac.uk/). In order to compare both registers, three-word units were generated for each corpus and the results are presented in Table 8.7. In this case, three-word units were chosen due to the sharp fall in frequency of occurrence between three-word and four-word units in the two corpora. For example, the most frequent four-word unit in front of us occurs on 16 occasions in the Sherlock Holmes corpus.

PRAGMATICS AND VARIATION AT THE LEVEL OF REGISTER Table 8.7 The ten most frequent three-word units in Sherlock Holmes corpus and Shakespeare corpus Sherlock Holmes’ novels

1 2 3 4 5 6 7 8 9 10

Shakespeare’s tragedies

Unit

Frequency

Unit

Frequency

it was a that it was one of the there was a out of the that he had there was no that he was there is no it is a

72 71 66 66 65 64 63 62 58 50

I pray you I know not I do not I will not my good lord my lord Ham my lord I I would not it is a this is the

61 59 50 50 41 41 41 39 35 34

In terms of the pragmatic language features of these registers, Table 8.7 reveals a number of different items of interest. If we begin with the Shakespeare corpus, in particular the shaded items, we see the presence of the term of address my (good) lord which is used pragmatically in the corpus to show respect when speaking to a man who is of high rank socially (for more on terms of address see Chapter 5). Similarly, I know not is the archaic version of I don’t know, the most frequent three-word unit in both LCIE and the Spoken BNC1994 (see Chapter 7), and which often functions as a softener or mitigator. The frequency of use of these interpersonal items reflects the situational characteristics of drama, given that its mode is ‘written-to-be-spoken’, and therefore the plays reflect spoken language as it was used at the time. In contrast, if we examine the Sherlock Holmes corpus, on first viewing, all units seem to be similar to other written registers such as academic writing (see Chapter 7), syntactic elements necessary for the correct construction of a clause or sentence. However, what is interesting is the presence, marked in bold, of it was a as the most frequent threeword unit and its present tense equivalent it is a (position 10). Similarly, there was no (position 7) has the corresponding present tense version, there is no (position 9). When concordance lines for these four items are generated and examined in the Sherlock Holmes corpus, the pattern that emerges is that the present tense units it is a and there is no are primarily used in direct speech. Out of the 50 occurrences of it is a, 45 (90%) of them are used in direct speech. Similarly, 50 of the 58 (86%) occurrences of there is no are used in direct speech. In contrast, only 25 of the 71 (35%) occurrences of it was a and 31 of the 63 (49%) occurrences of there was no are used in direct speech. Baynham (1996), in the context of classroom discourse, argues that direct speech is a strategic device used to reduce social distance and maintain interest in contexts where knowledge and/or power are unequally distributed. At the heart of much of crime fiction is a mystery to be solved and it is in this sense that the knowledge gap between writer and reader must be maintained – the writer knows more than the reader and seeks to keep the reader in suspense as the mystery unravels and is eventually solved. The switch to direct speech, from, say, exposition, involves a switch from the past tense to the present tense,

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thus shifting the origo closer to the reader’s deictic centre (for more on this see Chapter 4). Rühlemann (2007) argues that a narrator’s shift from narrative past to historic present is an example of empathetic deixis, where historic present serves as an involvement device ‘enhancing the audience’s affective connection to the narrative’ (p. 193; see also Schiffrin, 1987). In the case of crime fiction, specifically represented here by Sherlock Holmes’ novels, we could argue that the presence of the present tense three-word units there is no and it is a in direct speech also represents an involvement device on the part of Arthur Conan Doyle designed for the pragmatic purpose of heightening reader interest or investment. Take, for example, extract 8.14. (8.14) It was half-past five before Holmes returned. He was bright, eager, and in excellent spirits, – a mood which in his case alternated with fits of the blackest depression. ‘There is no great mystery in this matter,’ he said, taking the cup of tea which I had poured out for him. ‘The facts appear to admit of only one explanation.’ ‘What! you have solved it already?’ ‘Well, that would be too much to say. I have discovered a suggestive fact, that is all. It is, however, VERY suggestive. The details are still to be added. I have just found, on consulting the back files of the Times, that Major Sholto, of Upper Norword, late of the 34th Bombay Infantry, died upon the 28th of April, 1882.’ (The Sign of Four) The extract begins with a narrative sequence and the boundary between this and the beginning of direct speech is clearly marked by the sentence break and then quotation marks. Holmes’ assertion that There is no great mystery in this matter confirms him as the all-knowing detective, given that this assertion is, according to Holmes, supported by the facts. Watson responds with a request for confirmation, which, as we saw in Section 8.2, usually requires agreement as the preferred response. However, Holmes’ response begins with well, clearly the dispreferred one, where Holmes admits that he has, in fact, not solved the mystery but found, instead, a suggestive fact. This sequence of direct speech, introduced by there is no, serves to heighten reader interest as initially the mystery appears to be solved; however, although the reader discovers it is not, they are instead provided with another clue. As we noted in Table 8.1, one of the main communicative purposes of the register is, after all, entertainment.

TASK 8.6 MULTI-WORD UNITS AND THE NOVELS OF JANE AUSTEN Table 8.8 lists the top ten four-word units from a corpus of Jane Austen novels comprising Pride and Prejudice, Emma, Persuasion, Sense and Sensibility, Northanger Abbey and Mansfield Park.

PRAGMATICS AND VARIATION AT THE LEVEL OF REGISTER Table 8.8 The ten most frequent four-word units in the Jane Austen corpus Jane Austen’s novels

1 2 3 4 5 6 7 8 9 10

Unit

Frequency

I do not know I am sure I the rest of the a great deal of in the course of at the same time I am sure you I do not think and I am sure it would have been

133 85 82 80 71 67 57 55 54 49

For this task, build a corpus of the novels of Jane Austen (those listed here) in order that the functions of some of the four-word units listed in Table 8.8 might be further analysed, using, for example, concordance lines. Building a rudimentary written corpus is a relatively straightforward exercise. Follow these basic steps to get started: 1) 2) 3) 4) 5) 6) 7) 8)

Go to the Project Gutenberg homepage (www.gutenberg.org/); Use the ‘search for books’ option to locate the individual novels; Choose the ‘Plain Text UTF-8’ version of the novel and open the file; Copy and paste the content into Notepad, taking care to avoid ‘noise’, such as the website’s terms and conditions detailed at the beginning and end of each novel; Save the Notepad file onto your hard drive (a separate file can be created for each novel or all six novels can be copied into the same file); Download the freely available corpus analysis software package AntConc (www. laurenceanthony.net/software/antconc/); There are a number of excellent tutorials on YouTube explaining how to use AntConc – choose one that deals with the concordance tool; Generate concordance lines for the item(s) listed in Table 8.8.

In order to give this final, more analytical, step 8 some focus, answer the following question: 1.

Based on the analysis of both the Sherlock Holmes and Shakespeare corpora, what pragmatic features emerge from the list and what might these tell us about the register represented by Jane Austen’s novels?

Corpus mark-up: extralinguistic information We first encountered the use of features of corpus mark-up in Section 8.2, where speaker tags were used to identify initial items in speaker turns. The term mark-up is used to refer to

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codes or tags that have been inserted into corpora to indicate features of the text other than the actual words used (see McEnery and Hardie, 2012). One of the many useful aspects of a spoken corpus is that it will contain mark-up such as extralinguistic information about the context, for example, laughter, crying, pauses, hesitations, overt inhalations, and so on. This can prove very useful when looking at pragmatic features. One example of extralinguistic information in a corpus of shop counter recordings (from LCIE) is the sound of the till opening or closing. By searching for this item, we can investigate patterns of use around this. Through sorting the concordance lines for sound of till one item to the right, we can see that the high frequency item now frequently follows this extralinguistic feature (Figure 8.4).

sound of till Now two fourteen thanks. Two fourteen so sound of till Now two fifteen so please pause . sound of sound of till Now two sixty seven so please. Now I have the sixty sound of till Now three twenty so please sound of coins .

sound of till Now sixty eight please pause . Thanks. I don’t sound of till Now one twenty please. Thanks. Thank you.

sound of till Now eight twenty eight so please. sound of plastic bags sound of till Now two forty please. sound of coins Thank you very sound of till Now a pound please. sound of till sound of till Now six eighty so please thank you. Thank you. sound of till Now seventy eight so please. pause Thank you very Figure 8.4 Extract from concordance lines for sound of till in shop recordings from LCIE (sorted 1R)

This allows us to see the contextual pattern whereby the shop attendant rings up the price of the customer’s item on the till (hence sound of till ), and the attendant announces the price of the item to the customer. The shop attendant consistently precedes the announcement of the price with the marker now and follows the price with so and/ or please (see Binchy, 2005). This function of now in Irish English, evident here in service encounters, could be connected to its use as a deictic presentative akin to voici/violà in French or vot/von in Russian (see Clancy and Vaughan, 2012).

TASK 8.7 ANALYSING CORPUS MARK-UP When we look at extralinguistic information in the NHS Direct helpline corpus, we find a lot of caller inhalations noted by transcribers. We therefore treat these as important to this register. When we look at the concordance lines for inhales , we find the following, as displayed in Figure 8.5. When examining the concordance lines, bear in mind that is the caller to the helpline.

PRAGMATICS AND VARIATION AT THE LEVEL OF REGISTER oea that you know of? inhales Erm no. His stools were a little bit hich ones are you on? inhales Oh. Er erm Amoxycillin? Yeah. at about painkillers? inhales Er well I had some sort of on the any health problems? inhales Erm I’ve been ill. Erm I’m I’m s= colour is the rash? inhales Erm 1 sec well it’s red. I ’ve been scratching? inhales Oh yeah. Oh yeah. That how is he with that? inhales I mean he’s not complained about his ear re blisters are they? inhales Well they look like them a bit yeah. ess water than usual? inhales extends following syllable . How can I help you? inhales Well I’ve come to babysit for my sister Figure 8.5 Examples of concordance lines of inhales (unsorted)

1)

What patterns emerge in relation to this extralinguistic information?

The pattern of health advisor question + caller inhalation + hesitation/surprise marker + response is indexical of the power semantic in this context, where the health professional is the ‘primary knower’ (after Labov, 1972) and the caller is unsure as a discourse participant in this specialised context of talking about health with a professional, even though, ironically, the caller is actually the primary knower in terms of what his or her own symptoms and health issues are.

8.4

CONCLUSION

In this chapter we have examined a number of registers so as to exemplify how different approaches can be taken to exploring the pragmatically specialised ways in which language is used. It is crucial to start by looking at specific registers in terms of how their situational characteristics differ from the outset. The process of itemising these (see Table 8.1) helps to tease out the reasons behind the differing use of language across registers. It is when we explore details such as the mode of communication, the role relationships, the shared situational conditions, and so on, that we gain insight into what is behind the language. We stressed here the need for comparison of data. By bringing different data side-by-side and looking at it from perspectives of turn sequences, word frequencies, keywords and multi-word units, we can bring into relief the influence that situational characteristics have on how we use language pragmatically. It is also important to read the texts/recordings so as to gain depth of insight and trigger hypotheses which can be substantiated by follow-up searches. In addition, by looking at how keywords and high frequency items cluster, pragmatic specialisations become more apparent. Frequently, pragmatic markers co-occur, as do vagueness markers and hesitation devices. We also stress that pragmatically specialised patterns emerge even from very small corpora of data. If a collection of data is concentrated around a very specific register, not a lot of data is required to show pragmatically-specialised patterns of use. Findings can

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be corroborated by comparison with larger datasets. The exploration of the pragmatics of different registers also has a pedagogical implication because it tells us more about lexico-grammar beyond the purely semantic and syntactical levels. We devote our entire final chapter to the topic of pragmatics and English language teaching.

8.5

FURTHER READING

Clancy, B. and M. McCarthy, 2015. Co-constructed turn-taking. In K. Aijmer and C. Rühlemann (eds), Corpus Pragmatics: A Handbook. Cambridge: Cambridge University Press, pp. 430–453. The most familiar manifestation of co-construction is where one speaker provides a lexical resolution to another’s turn – effectively finishing their sentence. However, co-construction refers to a wider range of conversational events where speakers collaboratively create either a formal artefact (a word, clause, sentence) or functional artefact (a proposition, speech act, narrative) across turn boundaries. Using a corpus linguistic methodology, this chapter demonstrates how co-construction is closely connected to the realm of pragmatics due to the politeness issues involved in the joint construction of meaning in casual conversation. Jonsson, E., 2015. Conversational Writing: A Multidimensional Study of Synchronous and Supersynchronous Computer-Mediated Communication. Frankfurt am Main: Peter Lang. Although this book does not have an overtly pragmatic focus, it is worthy of further reading. It illustrates the use of Biber’s multidimensional approach to the study of variation in spoken and written registers to analyse computer-mediated conversational writing. Jonsson compares a corpus of conversational writing featuring both internet relay chat and split-window ICQ chat to both a spoken corpus (a subset of the Santa Barbara corpus) and a written one (the Lancaster-Oslo-Bergen (LOB) corpus). This allows for the comparison of CMC with both spoken and written language. Of particular note is that the split-window ICQ chat emerges as the most intimate, conversational form of writing ever documented. Many of the lexico-grammatical features that mark this as highly intimate and conversational – such as first- and second-person pronouns, direct WH questions, modal auxiliaries and negation – form an important part of the English language interpersonal pragmatic system. Mahlberg, M. and D. McIntyre, 2011. ‘A case for corpus stylistics: Ian Fleming’s Casino Royale.’ English Text Construction, 4(2), 204–227. Again, this is not an article that focuses on pragmatics per se. The authors do, however, provide an analysis of the keywords and key semantic domains of a corpus of popular fiction in the form of Ian Fleming’s novel Casino Royale. The identification of reader-centred keywords, particularly those related to the anatomical and physiological domain such as body or hand, are used to show how Fleming employed these stylistic devices to exploit the affective connection between Fleming’s James Bond character and the reader.

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Sacks, H., E.A. Schegloff and G. Jefferson, 1974. ‘A simplest systematics for the organisation of turn-taking for conversation.’ Language, 50, 696–735. This ground-breaking article sets out the principles for simplest organisation of turn-taking in conversation. The authors based their findings on observations of real conversations. Conversational structure, they propose, hinges around the activities of turn construction and turn allocation. The authors propose that the system which they identify is universal across languages. It might therefore be a worthwhile project to investigate this further in different languages (as researchers have done) and to look at how these turn-taking structures, and their influence on the pragmatic sphere, may differ in specific discourse domains.

NOTE 1 Frequency counts for Spoken BNC1994 in Table 8.2 are taken from Leech et al. (2001).

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CHAPTER 9

Pragmatics and language teaching

9.1

INTRODUCTION

For more than three decades there has been an awareness of the importance of pragmatics in the context of language curricula, especially in relation to speech acts (Félix-Brasdefer, 2013; Taguchi, 2013; Basturkmen and Nguyen, 2017). Theoretically, this coincides with an acceptance of a broader post-Chomskyan paradigm of communicative competence entailing more than linguistic competence (Hymes, 1972a; Canale and Swain, 1980). This has meant an acknowledgement of the fact that knowledge of lexis and grammar alone is not enough for a learner to become competent in language use. To know a language is to know when to use it and with whom across different social contexts. This means that competence in a language also entails a discourse, pragmatic and social dimension. In the context of speech acts, the distinction between pragmalinguistic and sociopragmatic knowledge has been a long-held one (see Leech, 1983; Thomas, 1983): • •

pragmalinguistic competence refers to the knowledge of the range of linguistic resources available to perform a speech action; sociopragmatic competence refers to the sociocultural knowledge of how to select an appropriate language choice for a given goal in a particular situation.

Thomas’ (1983: 104) words still ring a warning bell: [s]ociopragmatic decisions are social before they are linguistic, and while foreign learners are fairly amenable to corrections that they regard as linguistic, they are justifiably sensitive about having their social (or even political, religious or moral) judgement called into question. As research into pragmatics across cultures has demonstrated, pragmatic transfer (both pragmalinguistic and sociopragmatic) between languages can, on occasion, make non-native speakers appear overly direct, even rude or insincere. According to Bardovi-Harlig and Mahan-Taylor (2003: 38), ‘the consequences of pragmatic differences . . . are often interpreted on a social or personal level’ (see also, Bardovi-Harlig and Dörnyei, 1998; Rose, 2001; Alcón Soler, 2005; Takimoto, 2006). In the context of the classroom, Vellenga (2004)

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concludes that a ‘pragmatically friendly’ textbook should include pragmatic awarenessraising activities that equip learners with the contextual information, variety of form and in-depth cultural information necessary to make the correct pragmalinguistic (the range of forms available) and sociopragmatic (the right form for the right situation) choices. It is recognised that acquiring pragmatic competence, particularly in a foreign language context, is especially challenging for language learners (see e.g. Rose, 2001; Alcón Soler, 2005; Takimoto, 2006, Nguyen, 2011; Plonsky and Zhuang, 2019; Taguchi, 2019). Over the years, there has been much evidence of scholarship in relation to the teaching of pragmatics, as evidenced by meta-studies which aggregate work in the area (e.g. Jeon and Kaya, 2006; Plonsky and Zhuang, 2019). We also find a robust body of research on pragmatic competence in relation to study abroad (see Pérez Vidal and Shively (2019) for an overview) and in relation to comparing how speech acts and other pragmatic phenomena manifest differently intra- and inter-linguistically (see Schneider and Barron, 2008a; Barron, 2015; Beeching and Woodfield, 2015). However, it is widely recognised that, despite the level of ongoing research in the area, there is still an overall lack of transfer of research findings from this ongoing work to actual classroom practice. A perusal of the mainstream textbooks will quickly confirm that pragmatics has largely not yet trickled down to mainstream syllabi and materials. Bardovi-Harlig and Dörnyei (1998) suggested that in the EFL classroom micro-level grammatical accuracy is prioritised at the expense of macro-level pragmatic appropriateness and many still hold this to be true. However, there is a growing awareness of the need to conceptualise the instructional side of pragmatics if there is to be an impact in the classroom (see e.g. Nikula, 2008; Houck and Tatsuki, 2011; Ishihara and Cohen, 2010; Barraja-Rohan, 2011; Li, 2012; McCarthy and Clancy, 2019). In this chapter we aim to add to this ongoing conceptualisation and transfer to the classroom. In particular, corpus pragmatics, as a thematic thread through this book, will be explored in terms of how corpora can inform classroom materials and lesson design in relation to teaching pragmatics.

9.2 IMPLICIT VERSUS EXPLICIT PRAGMATIC INSTRUCTION One of the key questions in relation to teaching pragmatics is whether it should be overtly taught or whether it is something that learners have to intuit from their interactions and experience(s) with language, both in the classroom and beyond (e.g. on a study-abroad programme). This question of how learning takes place (implicitly or explicitly) also applies to many other aspects of language acquisition and cognition in general. To learn explicitly means that the teacher brings overt attention to a teaching point and engages instructionally with the learner so as to consciously achieve a learning outcome. To learn implicitly is to do so subconsciously. Fostering implicit learning requires a subtle approach in the classroom whereby the aim is to raise awareness without bringing overt attention to the teaching point (Ellis, N.C., 2015; Ellis, R., 2016). In the context of pragmatics instruction, for example, this might be done through a meaning-based focus on a speech act within the context of a roleplay activity or within a Content and Language Integrated Learning (CLIL) approach. Many argue that this model offers a rich opportunity for the implicit learning of speech acts

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and formulaic routines, for example, in relation to questioning routines; requesting information; issuing directives (Dalton-Puffer and Nikula, 2006; Nikula 2008); negotiating disagreements and misunderstandings (Nikula, 2008), as well as subject specific-language use (Nikula, 2012). Let us briefly consider how the implicit versus explicit learning debate (often referred to as the Interface Debate) relates to teaching pragmatics. Imagine the scenario where a language student consciously learns a sociopragmatic norm (through overt teaching input) in their target language. Will this conscious learning become procedural and ultimately automatised knowledge (i.e. part of the learner’s fluent subconscious store of language knowledge and competence)? Within the ongoing debate, many argue that because it was consciously learnt, this knowledge will remain as conscious knowledge (at best) and never become automatised (in line with a Chomskyan position). Others argue the opposite position – that, in theory, forms of overt teaching can lead to learning whereby this knowledge can become part of the learner’s subconscious store that can be drawn upon automatically when required by the learner. For the teaching of pragmatics this is an important issue because it relates to how pragmatics is best taught and also how correction and feedback in the classroom should be approached (if at all). As you read work on the teaching of pragmatic competence, it is important to appraise the stance of the author(s) on explicit versus implicit approaches to how/whether feedback should be given to learners.

TASK 9.1 EXPLICIT VERSUS IMPLICIT FEEDBACK Imagine you are an English teacher of an A2 Elementary level (CEFR). You have presented and practised some examples of invitations1 in the class textbook with the students. Then, by way of follow-up, you set up a paired roleplay task. The task involves one student inviting another student to their house for a birthday party. Now, consider the following interaction (modelled on learner data) between two of the students: Alex and Sarah. Alex is given a prompt card (Figure 9.1) and Sara is his roleplay partner. Your birthday is on Saturday! You are having a party in your house at 6 p.m. Invite a friend to your party.

Figure 9.1 Role card for Alex

This is how the roleplay begins: Alex: I’m having a birthday party on Saturday at 6 p.m. and please you must come! Sara: Yes, thank you. I would like to go. Where is your house? If you were the teacher, would you see a need to address anything about Alex’s use of language in his invitation? Would you:

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1)

2)

Explicitly: tell Alex that saying I am having a birthday party on Saturday at 6 p.m. and please you must come! is too direct as an invitation and suggest alternatives, then practise these and redo the roleplay task. Implicitly: after the roleplay, show all the learners some more authentic examples of invitations and then ask them to undertake their roleplay again (and pay close attention to how invitations are performed).

The question of whether the classroom is a place where pragmatic competence can be taught or learnt is researched in various ways (see Basturkmen and Nguyen, 2017). Some studies conduct observations while others use the classroom to test, through quasi-experimental means, different ways of teaching pragmatics (through ‘interventions’). Within this body of work there have been mixed outcomes, and this is not surprising given the complexity of the task of ‘measuring’ the teachability and learnability of pragmatic competence. Some observational studies conclude that the classroom is not the most ideal place to teach pragmatics because it involves a power asymmetry between teacher and students that is at odds with the conversational conditions of non-classroom-based interactions (Bardovi-Harlig, 2001). Others, especially those working within a Vygotskyan perspective, argue that because the teacher interacts with the students and students interact with each other, this in itself offers opportunities for incidental (implicit) learning of pragmatic norms. Many studies explore the language-learning classroom in terms of the opportunities for implicit learning through processes of peer-to-peer interaction and socialisation (Ochs, 1996; Kanagy, 1999; Cekaite, 2017). Takeyama (2019) offers succinct syntheses of work in this area, and longitudinal research, such as Cakaite (2017), provides invaluable contextualised insights into the learning process of migrant children immersed in host country schools (in this case, two Kurdish learners in a Swedish immersion classroom). Given the number of migrant children faced with acute changes in what constitutes a classroom and the norms therein (not to mention life outside the classroom), this type of research becomes all the more vital. Viewed within a sociocultural perspective, Ohta (1997) sees the classroom as a place where pragmatic competence can be fostered, especially through peer-to-peer interactions. Ohta (2001) recorded the classroom interactions of two L2 Japanese learners’ development of acknowledgement and alignment expressions. Across the period of study, Ohta was able to identify a link between the developmental patterns of these expressions and classroom-specific experiences (teacher instruction or peer-to-peer talk).

TASK 9.2 IMPLICIT LEARNING OPPORTUNITIES Can you think of classroom interactions where a learner might pick up (or intuit) pragmatic norms of the target language? For example, requests: a classmate asking to borrow an eraser. Make a list of possible learning opportunities.

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Plonsky and Zhuang’s (2019) meta-study brings together 50 studies on pragmatics instruction, conducted up until 2016. This extends the work of Jeon and Kaya (2006) and offers us some important summative points from studies to date. These findings provide a useful contextualisation for this chapter: • • • • •

•

Explicit instruction in pragmatics is found to be more effective than implicit instruction; Instruction with feedback is more effective than instruction without feedback; Instruction that allows for opportunities for practising a pragmatic teaching point is more effective; Adding textual enhancement (e.g. highlighting a language item through bold text) has only a minimal effect; Length of instruction has a positive effect: hence more sustained teaching of pragmatics, distributed over a longer period, can lead to greater gains in pragmatic knowledge and enhanced retention over time; Learners with a higher proficiency level benefit most from pragmatics instruction and so it is more effective to teach pragmatics at intermediate level, and above, when learners have a greater lexical and grammatical repertoire.

9.3 TECHNOLOGY-BASED OPPORTUNITIES FOR PRAGMATIC LEARNING Computer-Mediated Communication (CMC) and Technology Enhanced Learning (TEL) Computer-Mediated Communication (CMC), gaming, virtual environments and language corpora are but a few of the possible digital means available to language teachers in the ever-developing context of Technology Enhanced Learning (TEL). CMC refers to any person-to-person communication supported by digital technologies that enables both realtime synchronous and asynchronous interaction across different modalities (see Sauro, 2013). Many areas of pragmatic learning have been examined in relation to the use of CMC in the language classroom (see Cunningham (2019) for a useful overview). Not surprisingly, speech acts have received much attention, especially in the context of email requests (see e.g. Hartford and Bardovi-Harlig, 1996; Chen, 2001, 2006; Biesenbach-Lucas, 2007; Alcón-Soler, 2015). One of the obvious boons of TEL for pragmatics instruction (and language teaching in general) is that it allows learners to have virtual face-to-face interactions with L1 speakers. This gives rise to a natural need to use certain speech acts. Morollón Martí and Fernández (2016) explored sociopragmatic awareness of speech acts that arose naturally in synchronous video interactions between Danish learners of Spanish and L1 speakers of Spanish in Spain. They looked at greetings, compliments, offers, invitations and leave-taking, and found that exchanges in the CMC prompted discussion of Spanish speech acts during class time and this allowed for the student-led need to learn more about how these speech acts manifest in Spanish so that they were better equipped for ongoing CMC sessions. Working with learners of German who engaged in audio-visual teleconferencing with German native

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speakers in professional contexts, Cunningham and Vyatkina (2012) looked at requests and compared the learners with native speakers. Focusing on peer-to-peer learning, Tang (2019) reports on an interesting study on the pragmatic development of Chinese modal verbs within a cohort of 30 learners (high elementary to intermediate level) across two different instructional modes. Half of the participants completed tasks via CMC (using the written chat facility within the learning management system Moodle). Pairs were positioned far apart from each other, in different rooms in some cases. The other half of the cohort completed the same tasks in a face-to-face format (FTF). Pre-tests, post-tests and delayed post-tests were used to measure the learning outcomes in terms of the frequency and pattern of modal verb use. Results show that the FTF group outperformed the CMC group. The FTF group were found to produce modal verbs more frequently during the tasks. Tang (2019) concludes that FTF appears to be more beneficial for task-based pragmatics learning. This study raises the interesting question as to why it might be that interlocutors in a face-to-face situation use more modal verbs. As Tang notes, it may relate to the need for more self-repair, compared to the written chat mode. Although using a different research design, Ajabshir (2019) found results that counter those of Tang (2019) in a study involving 106 Iranian EFL learners designed to explore the effect of CMC, in comparison to traditional face-to-face instruction, on the acquisition of pragmatic competence across modes (mostly in relation to requests). The participants completed one of three instruction types for eight sessions during an intensive extracurricular programme: synchronous (Syn), asynchronous (Asyn) or face-to-face (FTF). All participants completed a written DCT as a pre-test and post-test. As Ajabshir (2019) describes, in each of the treatment sessions, the participants (1) received the metapragmatic instruction; (2) watched computerised video clips on requests; and then (3) were paired with a partner to discuss some prescribed questions and to create their own dialogues based on the given situations. During phase 3, participants engaged in one of the following: synchronous textbased chat, asynchronous text-based chat, or face-to-face discussion, based on their group assignment. The results showed the CMC-oriented instruction to be more successful than the FTF instruction. While no significant difference was found between the Syn and Asyn groups in their post-test performance, they performed differently on some measures of pragmalinguistic and sociopragmatic competences. Both the Syn and Asyn groups generated roughly similar frequencies of indirect speech acts. The Asyn group tended to use syntactic and lexical modifiers more frequently, while the Syn group tended to vary their request strategies more in accordance with the levels of imposition. The findings, Ajabshir (2019) argues, have pedagogical implications for EFL teachers, practitioners and courseware designers to use CMC affordances for delivering pragmatics instruction.

Corpora and pragmatics teaching and learning Pragmatic insights for the classroom Using corpora in the classroom through data-driven learning (DDL) has long been an approach which aims to bring authentic language to learners, and meta-studies have shown that DDL has an overall positive effect size (see Boulton and Cobb, 2017; Lee et al., 2018;

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Chen and Flowerdew, 2018). Bardovi-Harlig et al. (2017) offer a study of DDL in relation to the teaching of pragmatic routines used for agreement, disagreement and clarification in academic English discussion. Their two test groups were given different treatments: one used teacher-developed corpus-based materials, while the other engaged in hands-on corpus searches in class. MICASE was used for noticing and production activities. Compared to the control group, the study found that both treatment approaches led to a significant increase in the oral production of pragmatic routines. The corpus materials group showed an increase in the clarity of speech acts while the hands-on corpus search group noted that they engaged in self-directed searches outside the classroom. As discussed in Chapters 2 and 3 and elsewhere, corpus linguistics research offers many insights into areas of pragmatics, enhancing descriptions of speech acts and other pragmatic phenomena, such as pragmatic markers and stance. In the context of pragmatics teaching, the findings from such work can inform how and what we teach. However, the transfer from research findings to language materials is slow (Bardovi-Harlig et al., 2017), as discussed above. In this section, we sample some corpus linguistics studies and try to reflect on why they are important to materials design and pragmatics instruction. Mindful that there is a need to broaden our focus to areas of L2 pragmatics beyond speech acts to areas such as discourse organisation, stance and pragmatic markers (Staples and Fernández, 2019), the studies we look at show how results from corpus-based pragmatics research can be applied in the classroom as language tasks. The Michigan Corpus of Upper-level Student Papers (MICUSP) and the Michigan Corpus of Academic Spoken English (MICASE) (see Appendix) are two important corpora in the context of bridging the gap between corpus linguistics and language teaching. Neiderhiser et al. (2016) used the MICUSP to explore the under-researched area of imperatives in research papers. Methodologically, Neiderhiser et al.’s (2016) study was supplemented by text-based interviews with faculty members across the main disciplinary contexts represented in the corpus. They found that the following imperatives were used most frequently across the disciplines of physics, philosophy, economics, mechanical engineering, and linguistics, though in quite varied ways (Table 9.1). Table 9.1 The most frequent imperative verbs in the MICUSP across the disciplines of physics, philosophy, economics, mechanical engineering and linguistics, in descending order (Neiderhiser et al., 2016). note let see consider suppose

notice recall assume refer call

take install imagine define compare

Figure 9.2 illustrates the verbs notice and assume functioning as imperatives in physics and philosophy reports. Findings from the interview data gathered by Neiderhiser et al. (2016) suggest that successful and experienced student writers begin sentences with imperatives ‘as a potentially high-risk strategy’ for various strategic purposes that are

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discipline-specific. Neiderhiser et al. (2016) note that such insights have implications for writing instructors and materials designers in both L1 and L2 contexts. We explore this further in Task 9.3.

Figure 9.2 Two examples of high-frequency imperatives in the MICUSP

TASK 9.3 IMPERATIVES IN ACADEMIC WRITING Consider Figure 9.3, which illustrates the results for the verb note in the MICUSP (per 10,000 words2) across all of the disciplines represented in the corpus (with the disciplines in Neiderhiser et al.’s (2016) study shaded): Choose any two of the disciplines and examine a sample of instances of note: 1) 2) 3)

What percentage of the uses of note in your sample is imperative? How many are at the beginning of a sentence? What is the impact of note at the beginning of a sentence? What other non-imperative uses of note do you find?

Figure 9.3 Frequencies per 10,000 words of note in the MICUSP. The results for Physics, Philosophy, Mechanical Engineering, Economics and Linguistics are highlighted, as these were used in Neiderhiser et al.’s (2016) study.

While conducting Task 9.3, you have been engaged both consciously and subconsciously with an activity that focused on a form that carries pragmatic force in the context of academic writing. You may have subconsciously intuited or overtly noticed (perhaps with the aid of a peer or instructor) that its force can vary depending on where (and how) it is used in the sentence. This offers an insight into the conscious and subconscious processes that corpus-based tasks offer in the classroom.

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TASK 9.4 CONSCIOUS AND SUBCONSCIOUS LEARNING OPPORTUNITIES Return again to the list of imperative verbs from Neiderhiser et al. (2016) shown in Table 9.1. 1) 2) 3)

Take any one of the verbs and explore its use more closely in the MICUSP. Note your observations and prepare a mini-presentation on it. Consider how this kind of information could be used to develop classroom materials and how it might aid conscious or subconscious learning. Using the Academic genre component of COCA, design a task for advanced learners of English based on some of these verbs.

Let us now consider another example from corpus research that offers interesting insights, namely the multi-functional multi-word unit I think. Much of its multi-functionality relates to its pragmatic deployment. It can be used in expressing certainty/uncertainty; managing discourse; mitigating or boosting, among other functions. Zhang and Sabat’s (2016) study offers an interesting way of looking at I think across three spoken academic datasets: one from MICASE, and one each from Chinese learners and Persian learners of English. Instead of staying within the orthodox paradigm of comparing L2 use with a (normative) L1 baseline so as to identify over-, under- or misuse use of language forms, they describe how I think is used across the datasets. Their data comprised: • • •

Six hours from American English speakers from MICASE (51,403 words); Seven hours of matching data from Chinese learners of English (51,263 words); Seven hours of matching data from Persian learners of English (51,344 words).

A crucial variable in relation to I think is its clausal position: initial, medial or final. Therefore, while on the one hand it can be said that all speakers used I think most commonly in the clause-initial position, they report results from different cohort variables, for example: Chinese speakers used I think: • • •

In the initial position about five times more frequently than the American speakers and about four times more frequently than the Persian speakers; In medial position about two times more than the American speakers and about three times more than the Persian speakers; In final position seven times more than the American speakers and three times more than the Persian speakers.

As discussed above and in other studies, I think is multi-functional and can be used as a stance adverbial, an epistemic stance marker and a pragmatic marker (e.g. marking discourse,

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hedging, boosting). Zhang and Sabat’s (2016) findings confirm this multi-functionality in their data but, crucially, they avoid viewing their results through a ‘standard language ideology’ lens (Lippi-Green, 2011). Instead they describe the elasticity of I think across variables of frequency, position and multi-word patterns (Zhang and Sabat, 2016: 348–349). Within this variationist view, for example, a number of observations can be made. 1) 2)

3)

Frequency: there may be variation across relative frequency when comparing L1 and L2 speakers and within differing L2 cohorts; Position: There may be variation in where I think is positioned (in terms of the clause) and this choice on the part of the speaker serves differing pragmatic functions (e.g. expressing certainty; uncertainty; managing discourse; expressing tentatively; mitigating or boosting); Multi-word units: There may be variation in how I think forms patterns with other words. For example, the unit it + that (complementiser) is used much more frequently by Persian speakers; native speakers have a preference for I don’t think + affirmative statement and avoid I think + negative statement. These multi-word unit patterns may reflect sociopragmatic norms and values. For example, L1 speakers use I think I over I think we to place the focus on themselves, while the reverse is the case with Persian speakers who seem to use I think we to deflect from individual focus.

Zhang and Sabat’s (2016) model for interpreting the variation found across L1 and L2 use of I think showcases the benefit of viewing learner language in a non-deficit manner. Through a more flexible model, we are able to see how underlying pragmatic norms may be at play. This is a study that could be replicated for other L2 cohorts and other language forms. The results from this study also lend themselves to application in classroom tasks, as we will explore in Task 9.5 (on written academic English) and Task 9.6 (on spoken academic English):

TASK 9.5 THE USE OF I THINK IN WRITTEN ACADEMIC ENGLISH Using the MICUSP, conduct a search for I think across disciplines and note any frequency differences (across per 10,000 word results). 1) 2)

3)

Looking at examples, find instances of I think in clause initial, medial and final position and discuss their function. Make observations about the multi-word unit patterns of I think across disciplines. (Tip: note what words typically come before or after it; do you notice any consistent patterns? Are these specific to particular disciplines?). Search for I think in another academic corpus (e.g. COCA). Note any observations in relation to clause position and multi-word unit patterning and prepare a mini-presentation.

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TASK 9.6 THE USE OF I THINK IN SPOKEN ACADEMIC ENGLISH Using MICASE, conduct a search for I think across two different speech events types (e.g. lecture, dissertation defence or colloquium). 1) 2)

3) 4)

How is I think used differently across user roles (i.e. lecturers and students)? What are the multi-word unit patterns of I think (i.e. examine the most common word(s) to the right or left of I think). Do these vary across speech events (or discipline)s? What do you notice about the clause position of I think? Prepare a mini-presentation based on your main observations.

As we will discuss below and in Section 9.4, other pragmatic markers can be explored through corpus searches and corpus-based materials.

Pragmatics across proficiency levels As noted above, meta-studies tell us that learners with a higher proficiency level were found to benefit most from pragmatics instruction. As a result, it has been advised to teach pragmatics from intermediate level and higher, on the basis that, by then, learners will have an enhanced lexical and grammatical repertoire (Jeon and Kaya, 2006; Plonsky and Zhuang, 2019). However, a counterpoint to this view is that the more embedded and integrated pragmatics is within a syllabus from the beginning, the better for learners. We argue that, even for beginner-level learners, it is important to know a word or a grammatical pattern in terms of when, how and with whom to use it. Therefore, we advocate an integrated approach to building language awareness (which includes pragmatics). We see this as essential to curricular change. Also essential to the process of transfer and change is the need for pragmatics researchers to be mindful that language curricula are differentiated for level of proficiency, and so syllabi, teaching points and materials are graded accordingly. To enhance the possibility of augmenting the focus on pragmatics in the language classroom, the more the research community can assist in describing learners’ needs and competencies across the span of proficiency levels the better, both for spoken and written language. In other words, corpus pragmatics researchers play a key role in providing differentiated empirical findings to inform syllabi. Many studies based on corpora have been calibrated by level of proficiency, and the results from these can offer much to curriculum, syllabus and materials design. Staples et al. (2013), for example, use data from a corpus comprising TOEFL iBT written responses (see Biber and Gray, 2013; Biber et al., 2016) to examine learners’ use of lexical formulaic sequences in English for Academic Purposes writing. The data used in this study was subdivided into three proficiency levels (low, medium and high). The results show that, overall, lower level learners used more lexical bundles3 (see Chapter 1) and

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many of these were also found in the task prompts. However, while the functional analysis of the bundles shows that, across all three levels of proficiency, there was a similar use of bundles for stance and discourse organising purposes, the learners used very few referential bundles (e.g. referring to physical or abstract entities). This kind of appraisal of a gap in learners’ pragmatic repertoire is very valuable for materials writers in the context of English for Academic Purposes. The English Grammar Profile4 (EGP), an online database resource, was developed as part of the English Profile project to identify the grammar that learners know or ‘can do’ at each of the six competency levels of the CEFR based on written learner exam data in the Cambridge Learner Corpus (CLC) (see O’Keeffe and Mark, 2017; see also Appendix). While its focus is on grammar, pragmatic information is also logged as an integral component of developing complexity and competence. In all, the EGP comprises over 1200 searchable entries across 19 superordinate grammar categories (e.g. adjectives, adverbs, the past, the present). While some superordinate categories relate specifically to pragmatics (e.g. modality and focus), pragmatic information is part of all forms. For example, the future simple affirmative form with will is something that A1 Beginner-level learners are competent at. This develops at A2 Elementary level in terms of the use of the negative and interrogative forms. As learners progress up the levels of proficiency, they also acquire competence in how to use these forms pragmatically. Even at A1 (Beginner) and A2 (Elementary) levels, evidence of pragmatic competence was noted (see examples in Table 9.2 from EGP).

Table 9.2 Sample of A1 Beginners and A2 Elementary entries for future simple relating to pragmatic competence taken from the English Grammar Profile (O’Keeffe and Mark, 2017) A1

A2 A2

A2

USE: PLANS AND INTENTIONS WITH ‘WILL’ Can use ‘will’ and “ll’ to talk about plans and intentions. USE: PLANS AND INTENTIONS WITH ‘WILL’ Can use ‘will’ to ask about plans and intentions. USE: REQUESTS WITH ‘WILL’ Can use ‘will’ to make requests. USE: WILLINGNESS WITH ‘WILL’ Can use ‘will’ to express willingness.

I will try to come to see you tomorrow. (A1; 2009; Romanian) Will you come by train? (A2; 2009; Spanish) Will you come tomorrow at 6.35 pm to my house? (A2; 2009; Italian) … and my elder sister will help us too. (A2; 2006; Bengali)

As O’Keeffe and Mark (2017) note, pragmatic competence is part of the bigger picture of competence across all levels of proficiency. As they assert, the EGP database results show many instances where learners acquire a form at an early stage (A1 or A2) and, progressively, develop more pragmatic competence in terms of how to use it. The past simple tense offers one of many further examples of this development (see Table 9.3). Learners acquire the past simple affirmative form at A1 and use it with greater pragmatic dexterity as they progress up the levels. For example, by B1, learners can use it to express regret with I wish (that) and at B2, they can use the verbs wonder and want in the past simple as a politeness structure in thanking and requesting (e.g. I also wanted to know if there is a gym in the hotel?).

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PRAGMATICS AND LANGUAGE TEACHING Table 9.3 A sample of entries from the English Grammar Profile (EGP), illustrating the use of the affirmative form of the past simple at A1, and tracking some of the pragmatic competence developments at B1 and B2 level Level

Can-do statement

Learner example

A1

FORM: AFFIRMATIVE

My grandmother lived in a village and I often went there. (A1; 2007; Polish)

B1

Can use the affirmative form with a limited range of regular and irregular verbs. USE: REGRET Can use the past simple with ‘wish (that)’ to express regret that things are not different. USE: POLITENESS: ‘I WONDERED’ AND ‘I WANTED’

B2

Can use the past simple with I wondered and I wanted as politeness structures when making polite requests and thanking.

I wish that you were here, cycling with us. (B1; 2003; Portuguese) I wanted to know if the rooms are single or double, if they have showers and if there is room service? Secondly, I also wanted to know if there is a gym in the hotel? (B2, 1997: Spanish)

Looking at spoken language across proficiency levels, Jones et al. (2018) built an experimental Speech Act Corpus of English (SPACE) (see Appendix). The data for SPACE was elicited from learners (at B2 level) and native speakers using an avatar within virtual roleplays (based on Halenko, 2013) to elicit requests and apology data. Raters were used to grade the learner data in terms of whether they were ‘appropriate’ or ‘very appropriate’ in the dataset (see Jones et al., 2018). In other words, the non-native speaker data comprised what was rated as pragmatically successful language use in terms of performing the speech act. In their analysis of pragmatic competence across the native and non-native speaker requests and apologies, they were able to broaden the notion of successful use. Their model moves away from using native speaker speech act manifestations as an absolute baseline and takes a variational view where learners can be seen to competently perform speech acts, sometimes in slightly different but nonetheless successful ways. This is explored in Task 9.7.

TASK 9.7 SUCCESSFULLY PERFORMING SPEECH ACTS Consider the examples of elicited responses to a request task based on booking a study room in a university context from the SPACE corpus in Figure 9.4 (taken from Jones et al., 2018: 145). A) B)

Typical non-native speaker (B2 Upper-Intermediate level) response: I want to find out how to book a study room please. Can you help me? Typical native speaker response: Hi. Could you help me book a study room please?

Figure 9.4 Examples of elicited responses to a request task based on booking a study room in a university context (SPACE corpus) (taken from Jones et al., 2018: 145)

1) 2)

How do the two requests differ? Are they both successful?

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Figure 9.5 An example of a B2 (Upper-Intermediate) level resource based on findings from research into the Trinity Lancaster Corpus6 (Gablasova et al., 2019)

As illustrated in Figure 9.4 (Task 9.7), in the head act, the non-native speakers tended to use I want as a direct request. This was avoided by native speakers who mostly opted for the past form of could in the head act. However, Jones et al. (2018) found that non-native speakers were also sensitive to the pragmatic force of want (negative politeness) because they typically mitigated the directness of I want with a modification which included please

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(e.g. Can you help me please?). Jones et al. (2018) show similar variation in terms of how native and non-native speakers performed apologies. Work such as this which enhances our understanding of what constitutes successful speech act performance in an oral exam context is very welcome. From their corpus-based analyses, Jones et al. (2018: 163ff.) were able to ‘flesh out’ both pragmalinguistic and sociopragmatic descriptors within the CEFR for B1, B2 and C1 levels, and this offers many insights for both syllabus, assessment and materials design. Another exam-based learner corpus, the Trinity Lancaster Corpus (TLC) (see Appendix), is based on oral interview data from Trinity College London’s Graded Exams in Spoken English (GESE) across B1 to C2 levels on the CEFR (Gablasova et al., 2019). Apart from advancing our understanding of oral interview assessments, crucially, the project aims to devise enhanced resources, not least of all in relation to pragmatic competence. What is laudable about the TLC project is that it offers an example of how a corpus, calibrated by proficiency level, has the power to generate robust research results that can then be used to directly inform resources for use in the classroom. Because the data is from oral exams, many of the aspects on which the researchers focus are of a pragmatic nature (expressing agreement/disagreement; opinion; checking understanding; using interactional markers and hesitation devices, and using response tokens to show listenership, to name a few5). One of many examples is the bottom-up analysis of response tokens across proficiency levels (see Gablasova, 2014; Gablasova et al., 2019). This showed that the listener behaviour of the more successful test-takers was characterised by a higher number and wider variety of response token types. For test administrators, these speakers are perceived as taking a more active role in the conversation even when holding the floor. It was also noted that response tokens play a role in moving the conversation forward more effectively than silence or a repetition of a previously used token. Classroom resources, differentiated by proficiency level (such as Figure 9.5), have been designed based on the corpus findings, and the corpus data is used to aid noticing within these materials.

9.4

DEVELOPING CLASSROOM MATERIALS

Teaching aspects of positive politeness Positive politeness is about showing people that we respect and value them (see Chapter 5), and it is something that most teachers and course books address to some degree. What we say when we greet or address someone is crucially important in both spoken and written interactions. In Table 9.4 we collate a summary of the typical formulaic language which we can introduce to our students at different stages and through different types of materials. Activities such as roleplays and simulations, as well as structured and semi-structured dialogues, listening activities and task-based work can assist in learners both noticing and making salient these formulaic language forms.

PRAGMATICS AND LANGUAGE TEACHING Table 9.4 Formulaic address in different speaking and writing contexts Spoken contexts Relational context

Example exponents

Addressing/greeting someone you know face to face

Hi Hi [first name], how are you? Hi [first name], great to see you again.

Addressing/greeting someone you do not know face to face

Hello Hello [title + surname]. Pleased to meet you. Hello. Nice to meet you.

Addressing/greeting someone you know on the telephone

Hi Hi [first name], how are you?

Addressing/greeting someone you do not know on the telephone

If you receive the call: Hello, [first name + surname] speaking If you make the call: Hello, my name is [first name + surname]

Addressing a customer in a shop or restaurant

May I help you? May I take your order sir/madam? Shall I take your coat madam?

Addressing a customer at a hotel desk

Here is your room key Mr Collins. Have a pleasant stay.

Asking someone for directions or other requests (e.g. the time)

Excuse me, could you tell me how to get to Markham Street? Excuse me, could I ask you the time?

Addressing/greeting someone you know in informal writing (e.g. email)

Hi [first name] Hi there Hiya

Other social politeness formulae: When someone is going on a trip When someone is ill When you want to thank someone for a gift When you want to wish someone luck before an exam Just before you start a meal

Have a safe trip/bon voyage [in a get-well card] Get well soon. [in a thank-you card] Thank you for your wonderful gift. Best of luck in your exam. Bon appetite/enjoy your meal (formal) Okay, tuck in/eat up/get stuck in (informal)

Written contexts Addressing someone in a formal letter or email when you do not know the name of the addressee(s) Signing off

To whom it may concern

Addressing someone in a formal letter or email when you do know their name and title Signing off

Dear Prof. Rice,

Yours faithfully,

Yours sincerely,

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PRAGMATICS AND LANGUAGE TEACHING Table 9.4 Continued Written contexts Relational context

Example exponents

Addressing someone you know well but who is not a close friend in an informal letter or email (e.g. at work). Signing off

Hi there [First name] (on its own, e.g. John)

Addressing someone you know and are very friendly with in an informal letter or email

Hi [first name] Hiya [first name] Hey Cheers Lots of love

Signing off

All the best Best wishes Best (used as a short form of Best wishes) Cheers

The important pragmatic points from the introduction of the formulaic language shown in Table 9.4 are the following: • •

Language varies according to the social relationship between speaker and listener, and writer and reader, and we need to be ever-sensitive to these contextual variables; Language varies according to context and mode of communication, and we need to build up an awareness of how to show, in an appropriate way, that we respect and value our listener or reader through what we say or write.

We will now look at some sample tasks which might be used to consolidate the language in Table 9.4.

Sample task A Look up the Business Letter Corpus (Appendix). Select the personal letters corpus using the drop-down menu. Use this to help you find phrases to write an email to a friend for her first wedding anniversary. For example, use search words such as anniversary, congratulations, wish you, together, happy.

Sample task B In which of the following contexts would you say or write the expressions in the grid below? (a) When you thank someone for a gift; (b) When someone is unwell;

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(c) Just before you start a meal; (d) When someone is going on holiday; (e) When you want to wish someone luck before an exam.

Say it or write it?

Context?

Have a great time. I wish you a speedy recovery. Thank you so much. It was so thoughtful of you… Best of luck! Bon appetite!

Sample task C Here is an email from a student to a professor asking her for more time to finish an assignment. Identify what is wrong about the way the student has addressed the professor and how she has ended the email. Write a corrected version. Message From: Maria Vitale [mailto:[email protected]] Sent: 17 June 2009 10:38 To: Sharon Miles Subject: class essay Professor Sarah I need more time for my essay. Can I give it to you on Friday? Your student Maria

Teaching aspects of negative politeness The second aspect of politeness which can be addressed consistently by language teachers is that of directness, or perhaps more precisely indirectness. The importance of making what you say or write less direct so as not to sound too forceful is core to negative politeness (see Chapter 5). This cuts across areas such as modal verbs, vocabulary and grammatical structures. Here we break down the notion of negative politeness into teachable areas and provide some sample classroom activities. Some of these samples are based on language corpora and thus can provide models for other, similar tasks. Table 9.5 illustrates, in broad terms, how negative politeness can be categorised in spoken language across hedging, vague language and approximation and pragmatic marking (which includes discourse markers, interactional markers and response tokens). This is based on the corpus-derived framework of Carter and McCarthy (2006).

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PRAGMATICS AND LANGUAGE TEACHING Table 9.5 Ways in which we make what we say less direct (marked in bold) (based broadly on Carter and McCarthy, 2006) Feature

Example

Vague language and approximation

There were lots of dirty dishes and saucepans and that kind of thing. We’ll be there at about eight.

Pragmatic markers

Hedging It was too expensive at least that’s what I think. Discourse markers Anyway, she’s decided not to apply for the job… Response tokens A: I’ve decided to take a year off work to travel. B: Really!

The features shown in Table 9.5 will now be discussed in greater detail.

Vague language and approximation As we discussed in Chapters 7 and 8, vague language is a natural and an integral part of everyday discourse (see Channell, 1994; Biber et al., 1999; Carter and McCarthy, 2006; Rühlemann, 2007). In this section, we offer examples of materials to promote noticing and awareness of vague language use through inductive activities.

Sample task D Make these spoken statements vague by using one of the items below: or whatever, and so on, sort of, like, kind of, -ish, a bit about around or something a) b) c) d) e)

It’s cold in here. This exercise is difficult. It was a blue car. I’ll see you at five. Would you like tea?

Approximation, especially when talking about numeric values, is a key feature of vague language. For example, in Extract 9.1 (part of a museum society meeting from the BNCweb), a speaker is referring to an area on a map from World War II: (9.1) And these little spots denote some kind of bomb or landmine. And that is only within about two miles you know and area of about two miles square. (BNCweb : File D90PS007)

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Sample task E Figure 9.6 shows the results for a search for approximately in COCA, using the CHART function. 1) 2)

Note your observations about the use of approximately across registers and over time, based on Figure 9.6. Use COCA to explore approximately and find out what words typically collocate with it in academic data.

Figure 9.6 Frequency results for approximately charted across genre and time in COCA

Within academic data, you can explore the frequency of approximately across disciplines by entering the following search (Figure 9.7) and then clicking on ACADEMIC (indicated with the circle below in Figure 9.8). This will show you how the word is used across academic disciplines.

Figure 9.7 COCA interface search settings to explore approximately in ACADEMIC data

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Figure 9.8 Profile of approximately in ACADEMIC data across disciplines

3)

Compare how different disciplines use approximately by clicking on the bars under the discipline category to bring you to concordance lines and then share your findings.

Pragmatic markers The second area shown in Table 9.5 is pragmatic markers, and here we explore it in the context of hedging, discourse markers and response tokens (for detailed coverage see Aijmer, 2015, and Chapter 7, this volume).

Hedging Hedging is pervasive in both spoken and written English and has been shown to vary in terms of type and degree (Biber et al., 1999; Carter and McCarthy, 2006). It is of particular concern in teaching English for Academic Purposes and can take many forms from adjectives, adverbs, modal and mental (or emotive) verbs as well as conjunctions (see e.g. Hinkel, 1996, 1997, 2004; Hyland, 1998, 1999a, 1999b, 2018). Here are some examples of hedging from PhD theses: The second criterion suggests that it is necessary for members to gather together to actively pursue their goals, and that the members, as a collective, jointly negotiate these goals. However, we consider that this sample can allow us to identify whether the strategies chosen in the soap opera dialogues correspond to the ones found in casual conversation. If these statements were not hedged, they would look something like this:

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The second criterion states that members gather together to actively pursue their goals, and that the members, as a collective, jointly negotiate these goals. However, this sample will identify whether the strategies chosen in the soap opera dialogues correspond to the ones found in casual conversation. The unhedged examples are still grammatically correct but they impose the ideas of the author more forcefully than is the norm for a PhD thesis or academic research paper. The hedges provide a polite deferential buffer between the writer and the reader, and this is what is pragmatically expected in English academic writing. A summary of the forms commonly used to hedge are listed in Table 9.6.

Table 9.6 A summary of hedging forms (broadly based on Carter and McCarthy, 2006) Form Modals verbs can, could, may, might, should, would, etc.

Verbs with modal meaning appear, assume, believe,consider, estimate, suppose, seem, suggest, suspect, think, tend, indicate, propose, speculate

Nouns assumption, claim, possibility, estimate, suggestion

Adverbs actually, apparently, arguably, broadly, evidently, frequently, generally, just, only, really, likely, maybe, necessarily, normally, partially, probably, quite, relatively, roughly, seemingly, surely, typically, usually Prepositional phrases in a way in some/many respects generally/broadly/roughly speaking in most cases in the majority of cases more or less in principle in a sense in some senses

Example Part completion may be considered. Other options could be explored. Future research should take these factors into consideration. This practice is believed to have originated in Ancient Rome. Tools tended to be very rudimentary. McCann (2008) proposes that … This research suggests four options… Based on the assumption that the rate of flow will remain constant… Our claim is that this will result in greater efficiency and productivity… This is arguably the most important finding in relation to this process… It is likely that more software of this kind exists… This is just one possible cause of the MRSA superbug’s rampant spread. Broadly speaking, this new policy document has been welcomed. It has more or less been established that …

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Sample task F Figure 9.9 shows the frequency results for modal verbs may and should (per 10,000 words) in the MICUSP across disciplines7 (in the bar chart) and across types of writing (in the pie chart). 1) 2)

Compare the results for may and should. What are your main observations? Choose two disciplines and further investigate how may and should are used in these disciplines and across types of writing in the MICUSP. Prepare a mini-presentation to share your findings.

MAY

SHOULD

Figure 9.9 Frequency results for may and should across all disciplines in MICUSP

Sample task G Figure 9.10 is an extract from a journal article by Beard (2008). 1) 2)

Identify the language the author has used to hedge his assertions. Discuss the impact of these hedges on the reader. One example has been done for you.

PRAGMATICS AND LANGUAGE TEACHING

Example In the first sentence of the extract, we see the use of the hedged reporting verb suggest and the modal verb may. Although prior research suggests advertising humor may be associated with offense when it is used in advertisements for certain products and services or combined with potentially offensive themes, this has not been confirmed empirically.

Although prior research suggests advertising humor may be associated with offense when it is used in advertisements for certain products and services or combined with potentially offensive themes, this has not been confirmed empirically. For instance, researchers conclude that humor is used infrequently for products and services that are serious, intimate and high-involvement (Bauerly, 1990; Beard, 2006; Burnett et al., 1987; Fugate et al., 2000; Madden and Weinberger, 1984; McCullough and Taylor, 1993; Weinberger and Spotts 1989). Conversely, humor is believed to be most appropriate for low-involvement and low-risk consumer goods and services (Alden and Hoyer, 1993; Alden et al., 1993; Spotts et al., 1997; Toncar, 2001; Weinberger et al., 1995). Thematically, Weinberger and Gulas (1992) note that, ‘‘Some forms of humor, such as satire, sexual humor, and other forms of aggressive humor, may generate strong positive feelings in some audience members while eliciting strong negative feelings in others’’ (p. 57). Fugate (1998), however, suggests humor might enhance the persuasiveness of advertising for some unsought and controversial services by distracting consumers and reducing perceptual defenses. Other research similarly suggests humor might be effective when used to advertise uncomfortable products (McCullough and Taylor, 1993) or even reduce the likelihood of an offensive response, especially among men and younger audiences (Advertising Standards Authority, 2002). Figure 9.10 Extract from Beard (2008)

Sample task H Compare the two emails A and B: 1) 2) 3)

Which one is more polite? What hedge words and phrases make it more polite? Which would you prefer to receive and why?

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EMAIL A From: xxxxx Sent: 27 April 2009 15:29 To: Melissa Ryan Subject: Chapters to print Dear Melissa Whenever you have a chance, could you print two copies of the attached documents and send one set of copies to McHales Ltd? Would you mind stapling them separately and sending me a copy as well if possible by Friday. Thanks a million. Lynn

EMAIL B From: xxxxx Sent: 27 April 2009 15:29 To: Melissa Ryan Subject: Chapters to print Dear Melissa Please print two copies of the attached documents and send one set of copies to McHales Ltd. Staple them separately and send a copy as well by Friday. Regards, Lynn

Teachers may wish to curate authentic examples of hedging in specific contexts, and this could be done by searching for some of the forms listed in Table 9.6 in a corpus (e.g. would you in hedged requests in formal business contexts would be examined in the Business Letter Corpus (see Appendix) so as to provide examples for materials design as illustrated in Figure 9.11).

Discourse markers In the language classroom, discourse markers (DMs) are given reasonable coverage in terms of formal written contexts (see Biber et al., 1999; Carter and McCarthy, 2006). Typically, items such as evaluative, viewpoint and linking adverbs feature in textbook material for English for Academic Purposes (EAP), with a particular focus on linking adverbs.

PRAGMATICS AND LANGUAGE TEACHING

Figure 9.11 The first 20 results from the Business Letters Corpus search for would you

Evaluative adverbs: strangely, oddly Viewpoint adverbs: personally, professionally Linking adverbs: however, consequently The main macro-function of discourse markers is to organise stretches of text or conversation. They have many micro-functions of which learners can be made aware. Table 9.7 illustrates some of the core functions of discourse markers in speaking (discourse markers are marked in bold).

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Example from a corpus

Marking openings

[Context: At the beginning of a politics lecture] A: Okay so. Anybody paying any attention to the US election? B: Yeah. A: Yeah? Any news so far?

Marking closings

[Context: The end of a radio phone-in call. A is the caller and B is the presenter] A: …here’s another one of these tourists coming again you know give them a wide berth and perhaps we’d be nice nicer to them you know. B: Right okay. Okay all sorts of spin-off benefits okay listen Brian thank you very much indeed for talking to us. A: Right you are Marian. B: All the best cheers bye bye. (LCIE)

Marking the introduction of a new topic

[Context: Referring to the refrigerator] A: No fresh meat goes on the bottom. B: So are you working on the tapes now at the moment? C: Yeah. This is my second one.

(LIBEL)

(LCIE) Marking a to move to a new part of a story or argument

[Context: Two friends chatting] A: …she has a sister do you know what happened her sister? B: No A: The sister was doing all the same subjects that Kathryn is doing except the sister was made do biology instead of accounting as Mrs Finn has a thing that everyone has to do a science subject right. B: Right. A: So anyway her sister hated biology blah blah blah anyway her sister is now working as an accountant but she hasn’t got her degree in accounting so she going to school at night time you know to become an accountant … (LCIE)

Focusing on or emphasising a topic

[Context: A student asking a question in an accountancy class] A: Oh is that it I thought you said to direct. So you’re changing the direct debit from our account to the company account? (LIBEL)

To mark a return to an earlier topic after an aside, interruption or digression

[Context: A family talking. A is the daughter, B is the father and C is the mother] A: That’s the tart Dad. Will you have some of that now? I’ll give you some of that with your tea so. B: Oh no. I won’t have any of it. No. C: Did you ever have blueberries Jim? B: Never. C: You did. Anyway I got them in Roches. B: Why did you ask me so?

PRAGMATICS AND LANGUAGE TEACHING Table 9.7 Continued Function

Example from a corpus C: Cos I thought you would have long ago. Would they not grow on the bushes? B: Oh them kind of berries? Blackberries you mean? C: No they’re blueberries. B: I don’t know like. I haven’t a clue like. C: I’m only asking you. B: I don’t remember them. C: Anyway they’re nice. I got them there for a recipe in a book. (LCIE)

Marking the sequence of items in a list

[Context: A caller to a radio phone-in programme near the end of his call] A: And finally I think that we have to recognise that the main bottle necks in Irish society today are bottle necks in Irish government. The government is responsible for the road services … (LCIE)

Response tokens As discussed above in Section 9.3 and in Chapter 7, response tokens refer to the short utterances, such as mm, oh, yeah, oh really, that’s a pity, etc., and non-verbal surrogates, such as head nods and shoulder shrugs used by listeners to respond to what a speaker is saying, without taking over the turn. Their importance for oral fluency cannot be underestimated (see McCarthy, 2002; O’Keeffe et al., 2007; Carter and McCarthy, 2017; Gablasova et al., 2019). As discussed earlier (see Section 9.3), they have been identified by Gablasova et al. (2019) as a key resource for oral exam interviews to keep the conversation going and to show that a candidate is actively listening, using the TLC, worksheet resources have been developed based on this (see Figure 9.5). Using response token items from corpus studies, we illustrate some possible activities to develop awareness here.

Sample task I 1)

Use some of the following words and phrases in response to what is said below in examples a) to e).

great news! absolutely me too! too bad! gosh

a) b) c) d) e)

how about that! great sure exactly lovely

how scary! cool true wow really

perfect definitely wonderful excellent

This weather is just great! My sister is getting married next week. I love this soup. There was a terrible accident here last year. He’s been offered a new job.

of course certainly lucky for you! fine

right sounds great! oh no! good

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2)

Write three true statements about yourself that your classmates do not know. In pairs, tell each other something new about each other, based on your list. Practise using an appropriate response token in each case.

Sample task J Look at the following extracts from real conversations from LCIE. What is the function of the following responses in each extract: That’s a lot, That’s amazing, Oh that’s awful, That’s bad. Extract A [Context: A mother and daughter talking about a local lottery draw] Daughter: How much did you say the Lotto was worth this week, Mom? Mother: Nearly a hundred. Daughter: That’s a lot. Extract B [Context: Two friends chatting. Cherry Orchard is a football club] A: …and ah Cherry Orchard are able to go out and have trials at the start of the year they could have forty or fifty coming to trials and pick the best twenty so+ B: That’s amazing. A: +for us to take a team like that is unreal really. Extract C [Context: Two friends talking about a car accident] A: B: C: B: A: B: A: B:

And did he die? No the child the baby girl died. Oh she was lovely. She was in the car with him? Yeah she was. No she was in the other car. Oh and the mother of that child that died is pregnant again is it? Yeah sure it’s little consolation now. Oh that’s awful.

Extract D [Context: Two friends gossiping about another friend’s boyfriend] A: … he’s such a miserable fella. He’d get her to pay if they stayed in a hotel and she paid her half of the hotel and he paid his half. B: That’s bad. A: He wouldn’t pay the hotel.

PRAGMATICS AND LANGUAGE TEACHING

Sample task K Using the BNCweb, conduct a (case-sensitive) query for That’s in audio files (see Figure 9.12 for interface settings). Listen to some examples of That’s patterns used as response tokens. 1) 2)

What are your observations about the different patterns of That’s used in response tokens? What are your observations about the response tokens in the flow of conversational turns?

Figure 9.12 BNCweb query interface setting for search of That’s. Note the need to put a space between That and ’s in the search query box.

Bringing learners’ attention to the prosody and function of these items in conversation is crucial (see also Chapter 5). The ability to hear the sound files in the BNCweb makes it a really useful and authentic resource.

9.5

CONCLUSION

Meta-analyses of pragmatics instruction show us that a vibrant seam of research is continuously amassing (Plonsky and Zhuang, 2019). Research is diversifying and is increasingly enriched by being theorised from different perspectives (Basturkmen and Nguyen, 2017). To date, pragmatics research, in general, has provided us with a depth of empirical knowledge. And yet, the impact of all of this on language curricula, language materials and language classrooms is relatively minimal. In reality, pragmatic competence is still not seen as core to communicative competence when it comes to actual classroom practice.

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While it is heartening that research into how to teach pragmatics is ongoing, more studies that explore more variables across ‘contexts of learning’ are needed. In tandem with this, greater rigor in the detailing and recording of methodological treatments, especially in terms of quasi-experimental studies in the classroom, is called for (Plonsky and Zhuang, 2019). The more that we can aggregate in terms of what works, in what contexts, with which learners, undertaking which types of instruction and tasks while teaching pragmatics, the better. These details might seem small when describing an intervention but contextual information such as the types of materials used, the approach taken (implicit or explicit, inductive or deductive, corrective feedback or implicit feedback, enhanced input details, etc.) can be invaluable when aggregated. More studies across more outcome variables (e.g. across age, gender, foreign language versus immersion contexts, CLIL contexts, and so on) will add further to our understanding and will offset some of the imbalances described hitherto (see Plonsky and Zhuang, 2019). Pragmatics is also a neglected area in learner corpus research. It is only since 2000 that pragmatic features have received a consistent focus (Paquot and Plonsky, 2017), especially in relation to learner speech (due to the paucity of corpora of spoken learner language). In their sample of 378 Learner Corpus Research studies from 1991 to 2015, Paquot and Plonsky (2017) note that only 10 per cent of the studies looked at pragmatics. There is also scope for experimental work on the teaching of pragmatics, especially in relation to the interface debate and implicit/explicit approaches (see Section 9.2). Further exploration of CMC and TEL in relation to pragmatics instruction across more variables is also needed (e.g. age, gender, level of proficiency, prior experience with technology, mode of instruction, software application used, interface details, role of the teacher, role of peers, type of meta-pragmatic instruction, degree of corrective feedback, statistical measures, and so on). Also in this chapter we have noted that works such as Jones et al. (2018) and Zhang and Sabat (2016), among many others, promote a more inclusive model for assessment and pedagogy by describing learner language in a more variationist manner. In doing so, these studies take into account the fact that users of English, from different L1 and cultural backgrounds, have different ways of doing things with language. In an assessment context, there is a need to measure language use in terms of whether it is successful over whether it accurately reflects how or what a native speaker would say or write in the same situation. Overall, this chapter shows opportunities and advances in pragmatics teaching. The main challenge remains as to how to promote the connection between research findings and classroom practice, via curriculum designers, syllabus/materials writers and classroom practitioners. Throughout this chapter, we have aimed to showcase the usefulness of corpora in and for pragmatics instruction. We stress the importance of gaining more differentiated insights into learner pragmatics through learner corpora based on proficiency-level data. These insights have a far better chance of transferring to the classroom, as exemplified through the TLC examples discussed in Section 9.5. To finish, we note that at the core of this chapter (and this book) is corpus pragmatics. It is our belief that corpora will be the biggest driver of change in both foregrounding and addressing pragmatic competence in language teaching. We hope that through the sample corpus tasks, and in all of the chapters in this book, we are playing our part in this process by offering models for both self-study and classroom practice.

PRAGMATICS AND LANGUAGE TEACHING

9.6

FURTHER READING

Basturkmen, H. and T.T.M. Nguyen, 2017. Teaching pragmatics. In A. Barron, G. Steen and Y. Guo (eds), The Routledge Handbook of Pragmatics. Abingdon: Routledge, pp. 563–574. A wide-ranging survey of the ongoing issues, debates and sub-fields relating to the teaching of pragmatics is provided. This chapter is an excellent starting point for anyone interested in getting a succinct overview across a range of areas relating to pragmatics instruction. Gablasova, D., V. Brezina and T. McEnery, 2019. The Trinity Lancaster Corpus: Applications in language teaching and materials development. In S. Götz and J. Mukherjee (eds), Learner Corpora and Language Teaching. Amsterdam: John Benjamins, pp. 8–28. This chapter details the insights based on a corpus of oral exam interviews in the Trinity Lancaster Corpus and many of these relate to pragmatic competence in spoken interaction. Importantly, the chapter illustrates how robust corpus findings were used to develop materials. Jones, C., S. Byrne and N. Halenko, 2018. Successful Spoken English: Findings from Learner Corpora. Abingdon: Routledge. This book brings together communicative competence and corpus linguistics in a comprehensive and inclusive description of oral exam interview data. It gives particular focus to pragmatic competence and challenges the notion of native speaker sociopragmatic and pragmalinguistic norms. Through empirical data, it shows how successful spoken English can be performed in different ways. It also includes an interesting sub-study using an avatar to build a speech act corpus. One of the important outputs of the book is a model for an enhanced description of linguistic, strategic, discourse and pragmatic competence using corpus data. Plonsky, L. and J. Zhuang, 2019. A meta-analysis of second language pragmatics instruction. In N. Taguchi (ed.), Routledge Handbook of SLA and Pragmatics. New York: Routledge, pp. 287–307. This chapter offers a summative view of the status of research on pragmatics instruction across a range of variables so as to appraise the main focus of research in the field, the effect sizes of quasi-experimental studies, and so on. Apart from offering an excellent insight into the area as a whole, it also brings to light areas that need to be addressed and methodological lacunae. Zhang, G.Q. and P.G. Sabat, 2016. ‘Elastic “I think”: Stretching over L1 and L2.’ Applied Linguistics, 37(3), 334–353. This paper provides another way of looking at language use across native and non-native speakers. Patterns of use of I think are described and viewed in terms of how they vary across Chinese, Persian and American users of English, and this allows for the use of certain underlying pragmatic norms to interpret some of the variations in use. It moves away from a binary native–non-native speaker view where the non-native language is characterised with reference to under-, over- or incorrect use relative to the native speaker baseline.

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NOTES 1 If you would like more detailed research-based information on invitations (among other speech acts) and related teaching resources, see the webpage of the Center for Advanced Studies on Language Acquisition (University of Minnesota) (https://carla.umn. edu/speechacts/descriptions.html). 2 The MICUSP has two options for results: raw actual figures or normalised figures which are calculated to ‘per 10,000 words’. Normalised results need to be used when comparing frequencies across disciplines. Simply check the ‘raw’ or ‘per 10,000 words’ option at the top of the webpage interface. 3 Lexical bundles are recurrent non-idiomatic sequences or patterns of words. They have been found to be register-specific and much work has been done on their use in academic writing in particular (see Biber et al., 2004). While lexical bundles come under the general umbrella of multi-word units (see Chapter 1), it is important to understand their definition. Biber et al. (1999) define them as structural/grammatical sequences of four-, five- or six-word sequences that occur at least ten times per million words in a given register across at least five different texts. 4 See www.englishprofile.org/english-grammar-profile/egp-online. 5 For access to free downloadable resources, go to www.trinitycollege.com/site/?id=3662. 6 See www.trinitycollege.com/site/?id=3662 for more resources. 7 Biology (BIO); Civil and Environmental Engineering (CEE); Economics (ECO); Education (EDU); English (ENG); History and Classical Studies (HIS); Industrial and Operations Engineering (IOE); Linguistics (LIN); Mechanical Engineering (MEC); Natural Resources and Environment (NRE); Nursing (NUR); Philosophy (PHI); Physics (PHY); Political Science (POL); Psychology (PSY); Sociology (SOC).

Appendix

CORPUS DETAILS Corpus name

Size (words)

Description

The Birmingham Blog Corpus

628.5 million

The Birmingham Blog Corpus consists of blog texts (both formal and informal). It can be accessed at http://wse1. webcorp.org.uk/home/blogs.html.

The British Academic Spoken English Corpus (BASE)

1.6 million

The BASE corpus was collected in two UK universities between 2000 and 2005. It consists of 160 lectures and 40 seminars across 4 broad disciplinary groups – each group is represented by 40 lectures and 10 seminars (see Nesi and Thompson, 2006).

The British Academic Written English Corpus (BAWE)

6.5 million

The BAWE corpus was collected in three UK universities between 2004 and 2007. The corpus contains over 2,500 student assessments across 4 broad disciplinary areas and 4 levels of study, from undergraduate to taught Master’s level (see Heuboeck et al., 2010).

The British National Corpus (BNC)

100 million

The BNC is a corpus of 90 million words of written language and 10 million words of spoken language. The samples were collected from a wide range of sources, designed to represent a cross-section of British English (see www. natcorp.ox.ac.uk).

The BNCweb

100 million

The BNCweb is a web-based interface for searching the British National Corpus (BNC). The interface facilitates access to audio files. Register at http://bncweb.lancs.ac.uk/ bncwebSignup/user/register.php.

The BNC Baby

4 million

The BNC Baby is a four-part sample corpus of the BNC. It consists of four one-million-word samples of fiction, newspapers, academic writing and spontaneous conversation (see Burnard, 2008).

The Business Letter Corpus

1 million

Business letters from the US and the UK. For information see www2.fgw.vu.nl/resources/corpora/detail.php?idnr=27. To access the corpus interface go to www.someya-net.com/ concordancer/.

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APPENDIX (Continued) Corpus name

Size (words)

Description

The Cambridge and Nottingham Corpus of Discourse in English (CANCODE)

5 million

CANCODE is a corpus comprising spoken language from Britain and Ireland. The data was collected across five relationship types – transactional, professional, pedagogical, socialising and intimate – and three goal-types – information provision, collaborative task and collaborative idea (see McCarthy, 1998).

The Cambridge Learner Corpus (CLC)

55.5 million

The CLC contains written exam data from the Cambridge English suite of international exams, spanning 17 years, over 200,000 exam scripts, 140 first languages and 200 countries. In all, 33 million words of the CLC are coded for errors. It is owned by Cambridge University Press. A sample Open CLC of 2.9 million words from over 10,000 students, from 60 countries, across a range of 7 L1s, is available through Sketch Engine.

The Cambridge Limerick and Shannon corpus (CLAS)

1 million

The CLAS comprises spoken academic data from a range of different academic contexts within a BSc in International Hotel Management, Shannon College of Hotel Management, Ireland. The corpus contains data from both L1 and L2 speakers of English in a variety of different pedagogic contexts. The CLAS forms part of the Cambridge International Corpus, owned by Cambridge University Press (see Healy and Onderdonk-Horan, 2012).

The Corpus of Contemporary American English (COCA)

560 million

The COCA is an online corpus interface of American English data, from 1990 to 2012, divided evenly across the following genres: spoken, fiction, magazines, newspapers and academic papers (Davies, 2010). Access corpus at www. english-corpora.org/coca/.

The Corpus of Historical American English (COHA)

400 million

The COHA contains historical texts from the 1810s to 2000s and is balanced by genre decade by decade. The interface (www.english-corpora.org/coha/) facilitates a search by decade.

The English Web Corpus (enTenTen)

48 billion

The enTenTen corpus family of internet texts is available for more than 30 languages, all collected using the same sampling frame. Within the English family there are five sets. The latest of these (at the time of writing) is the enTenTen15, which contains 15 billion words. All enTenTen corpora are currently available through the online corpus interface Sketch Engine. See www.sketchengine.eu/ ententen-english-corpus/.

The Hong Kong Corpus of Spoken English (HKCSE)

907,657

The HKCSE contains spoken English in Hong Kong. Its online interface allows for (free) searches and more details are available on purchasing the prosodic version (see http:// rcpce.engl.polyu.edu.hk/HKCSE/default.htm).

The International Corpus of English: Ireland component (ICE-Ireland)

1 million

The ICE-Ireland is a written and spoken corpus collected in the Republic of Ireland and Northern Ireland between 1990 and 2005 (see Kallen and Kirk, 2008).

APPENDIX Corpus name

Size (words)

Description

The Limerick Corpus of Irish English (LCIE)

1 million

The LCIE is a corpus of naturally occurring spoken Irish English (for more details see Farr et al., 2004). The corpus is designed to parallel CANCODE.

The Limerick Corpus of Intimate Talk (LINT)

600,000

The LINT is a subcorpus of LCIE consisting of conversations between family members and close friends (see Clancy, 2016).

The Limerick and Belfast Corpus of Academic Spoken English (LIBEL)

1 million

The LIBEL corpus consists of spoken data collected in two universities on the island of Ireland; one in the Republic of Ireland and one in Northern Ireland (see Walsh et al., 2008). It is owned by Cambridge University Press.

Corpus of Meetings of English Language Teachers (C-MELT)

40,000

C-MELT is a corpus of English-language teachers recorded in different settings (see Vaughan, 2007).

The Michigan Corpus of Academic Spoken English (MICASE)

1.8 million

MICASE was collected in a US university between 1997 and 2002. It contains a wide variety of speech events, including lectures, seminars, lab sections and advisory sessions (see https://quod.lib.umich.edu/m/micase/).

The Michigan Corpus of Upper Level Student Papers (MICUSP)

2.6 million

MICUSP is a collection of A-grade student papers collected between 2004 and 2009. The corpus contains texts from four broad disciplinary areas (see http://micusp.elicorpora. info/).

The Nottingham Multi-Modal Corpus (NMMC)

250,000

The NMMC consists of video-recorded academic supervision meetings and lectures. The transcribed interactions are fully aligned with the video recordings in a multimodal interface (see Knight et al., 2009).

The Nottingham Health Communication Corpus (NHS Direct component)

61,981

The National Health Service (NHS) Direct corpus is a subcorpus of the Nottingham Health Communication Corpus and comprises recordings of phone calls made to the UK National Health Service phone line (see Adolphs et al., 2004).

The Open American National Corpus (OANC)

15 million

The OANC is a spoken and written corpus of contemporary American English. The corpus is designed to be comparable across genres to the BNC (see www.anc.org/).

The Santa Barbara Corpus of Spoken American English (SBCSAE)

249,000

The SBCSAE comprises naturally occurring spoken language from a variety of users, context types and geographical locations in the United States. It forms part of the US component of the International Corpus of English (ICE). Metadata and sound files are available from the project homepage (www.linguistics.ucsb.edu/research/ santa-barbara-corpus).

The Speech Act Corpus of English (SPACE)

33,712

The data for the SPACE was elicited from learners (at B2 level) and native speakers using an avatar within virtual roleplays (based on Halenko, 2013) to elicit requests and apology data. Raters were then used to grade the learner data in terms of whether they were ‘appropriate’ or ‘very appropriate’ in the dataset (see Jones et al., 2018).

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APPENDIX (Continued) Corpus name

Size (words)

Description

SPICE-Ireland

600,000

SPICE-Ireland is a pragmatically and prosodically tagged corpus of spoken language collected in the Republic of Ireland and Northern Ireland (see Kallen and Kirk, 2012).

The Spoken BNC2014

11.5 million

The spoken component of the BNC2014 contains transcripts recorded between 2012 and 2016. It comprises 1,251 conversations between speakers in primarily informal settings (see Love et al., 2017).

The TED_en corpus

3.4 million

A corpus of TED talks in English collected from 2006 to 2013. The corpus is available through Sketch Engine.

The Trinity Lancaster Corpus

3.5 million

A collaboration between Trinity College London and the Centre for Corpus Approaches to Social Science (CASS), Lancaster University, the TLC comprises 300 hours of transcribed speech, from the Trinity College London’s Graded Exams in Spoken English (GESE). The data comprise 1,500 L2 speakers, across 3 CEFR proficiency levels, 9 linguistic and cultural backgrounds, across a wide age range (see Gablasova et al., 2019). See www.trinitycollege.com/ site/?id=3329 and http://cass.lancs.ac.uk/tag/trinitylancaster-spoken-learner-corpus/.

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Index

Note: Page numbers in italic refer to figures and page numbers in bold refer to tables. address, terms of 107–108, 169 Ädel, A. 53, 56 adjacency pair 175–176 Adolphs, S. 5, 28, 61, 62, 68, 135, 142, 146, 156, 159, 165, 168, 170, 181, 231 advisives 142 Aijmer, K. 47, 49, 51, 57, 110, 130, 134, 139, 146, 154, 157, 161, 162, 216 Ajabshir, Z.F. 201 analytical frameworks 3–5 anaphoric references 72, 75, 84 Anglo-American school 1–2 annotation, pragmatic 37–40, 42–44, 57–58, 59–60 apologies: form-to-function approach 51–52; native and non-native speakers 210; roleplay study 31–32; sampling 53–55; using IFIDs 63–64 Archer, D. 17, 43, 44, 57 attested data 22–23 Austen, J. 190–191 Austin, J.L. 1, 21, 125, 127, 129, 130 backchannels 147–148 Bardovi-Harlig, K.S. 28, 62, 150, 196, 197, 199, 200, 202 Barron, A. 27, 33, 145, 146, 197 BASE see British Academic Spoken English (BASE) Basturkmen, H. 196, 199, 225 BAWE see British Academic Written English (BAWE) Biber, D. 7, 8, 14, 37, 69, 72, 78, 112, 155, 173, 174, 206, 214, 216, 220 Birmingham Blog Corpus (BBC) 64, 229 BNC Baby 91, 92, 93, 229 BNCweb 40–41, 214, 225, 229

Bousfield, D. 114, 115 briefing documents 25 British Academic Spoken English (BASE) 126, 157–158, 160, 161, 162, 163, 229 British Academic Written English (BAWE) 87, 112, 155, 155, 156, 229 British National Corpus (BNC) 5, 6, 229; BNC Baby 91, 92, 93, 229; BNCweb 40–41, 214, 225, 229 see also Spoken BNC1994; Spoken BNC2014 broad transcription 37–39 Brown, P. 18, 100, 101, 103, 104, 105, 106, 109, 110, 137, 139; criticism of 113–114 Business Letter Corpus 221, 229 C-MELT (Corpus of Meetings of English Language Teachers) 106, 117, 183, 184, 186, 187, 188, 231 Cambridge and Nottingham Corpus of Discourse in English (CANCODE) 7, 61, 62, 78, 146, 147, 150, 230 Cambridge Learner Corpus (CLC) 207, 230 Cambridge Limerick and Shannon corpus (CLAS) 43, 44, 230 can you? vs. could you? 130–131 CANCODE see Cambridge and Nottingham Corpus of Discourse in English (CANCODE) Carter, R. 13, 69, 111, 150, 154, 156, 159, 164, 168, 169, 213, 214, 216, 217, 220, 223 cataphoric references 72, 75, 84 cheers: collocates for 169–170; frequency 165–167 Cheng, W. 39, 164 Chilton, K. 178, 179 Clancy, B. 5, 37, 47, 49, 55, 79, 91, 94, 95, 106, 122, 145, 146, 154, 162, 164, 165, 176, 182, 192, 197

256

INDEX CLAS (Cambridge Limerick and Shannon corpus) 43, 44, 230 CLC (Cambridge Learner Corpus) 207, 230 CLIL (Content and Language Integrated Learning) approach 197–198 closed roleplays 32 CMC (Computer-Mediated Communication) 200, 201, 226 COCA see Corpus of Contemporary American English (COCA) coding time (CT) 82 COHA (Corpus of Historical American English) 66, 230 colligation 13 collocation 14; apologies 63–64; have 10; oops 65; thanks, thank you, cheers 167–170 commissive speech acts 127–128, 129, 136 compliments 66–67 Computer-Mediated Communication (CMC) 200, 201, 226 concordance lines 8–15; 183; can you? 131; could you? 131; inhales 193; sound of till 192; have 9–13; maybe + we 188; Sherlock Holmes corpus 189; so 52; sorry 52; sort 185; suggest 126; that bloke 92–93; that fella 93–94; um 151; we + have 12; well 153; why don’t we? 137; why don’t you? 137; would you? 221 consent forms 25 constatives 125, 126–127 Content and Language Integrated Learning (CLIL) approach 197–198 contextual variables 2–3 Continental European school 1–2 conversation analysis (CA) 174, 175–177; pragmatics and 177–180; pragmatics, corpus linguistics and 181–184; transcription model 40–41 cooperative principle (CP) 132–134 corpus data: construction of 35–44; vs, DCTs 50, 51 corpus linguistics 47, 82, 99, 147, 154; language patterns and 14; pragmatics, conversation analysis and 181–184 corpus mark-up 191–193 Corpus of Contemporary American English (COCA) 13, 56, 65–66, 67, 69–70, 80, 82, 91, 94–95, 162, 215, 230 Corpus of Historical American English (COHA) 66, 230 Corpus of Meetings of English Language Teachers (C-MELT) 106, 117, 183, 184, 186, 187, 188, 231

corpus pragmatics 4, 5, 47–67; form-to-function 51–56; function-to-form 56–67; key research considerations 48–51; software tools 5–17, 43–44 Coulthard, M. 140, 141 critical discourse analysis 4 Culpeper, J. 17, 43, 44, 57, 114, 115, 116, 118, 123 Culpeper, J.D. 118, 123 Culpeper, M. 128 cultural bias 113–114 DART 58 data-driven learning (DDL) 201–202 DCTs see discourse completion tasks (DCTs) definition of pragmatics 1–2 deictic centre 76–78; non-egocentric 77–78 deixis 72–76; basic categories of 78–91; discourse 84–87; empathetic 89–91; person 78–80; place 80–81; referential categories 75–76; social 87–89; time 82–84 Demeter, G. 31–32 design matrix, building a spoken corpus 36–37 Deutschmann, M. 63–64 direct speech acts 130–131 directives 43, 60, 127, 136, 141, 142 discourse analysis 4; speech act classification in 140–143 discourse completion tasks (DCTs) 26–30, 62; vs. corpus data 50, 51; multiple-choice task (MCT) questionnaires 29–30 discourse deixis 84–87 discourse markers 154; teaching materials on 220–223 discursive politeness 119–122 dispreferred response 176, 177 documentation for empirical research 24–26 Drew, P. 177, 178, 179 Drummond, K. 178 Economidou-Kogetsidis, M. 28 ELAN 42 elicitation acts 141 elicitation of language 23; building on existing research 61–63; research methods for 26–34 emotional deixis 91 empathetic deixis 74, 89–91, 190; use of that 91–95 empirical approach 3–5; to pragmatics research 21–26 endophoric references 72, 74 English Grammar Profile4 (EGP) 207–208 English Web Corpus (EnTenTen) 6, 9, 230

INDEX ethics 24–26 ethnographic approach 4; to recording language data 24, 34–35 ethnomethodology approach 4 see also conversation analysis (CA) exophoric references 72, 74 experimental approach 4 explicit performatives 125 extralinguistic information 191–193 face-saving approach to politeness 103–113; face-threatening acts (FTAs) 103–105; negative politeness 109–113; positive politeness 105–109 face-threatening acts (FTAs) 103–105; impoliteness and 114; mitigation of 107, 108 felicity conditions 127–129 Félix-Brasdefer, J.C. 31, 32, 33, 45, 196 Fernández, S.S. 200 Fillmore, C. 78, 82, 86 Finegan, E. 174 first order politeness 101–102 Flöck, I. 50, 62 floor-grabbing function 148, 152 floor-yielding function 148, 152 form-to-function 17, 47–48, 49, 51–56; breadth vs. contextual depth 50–51; frequency-based listing 56; one-to-one searching 53; sampling 53–55 frames 138–139 frequency-based listings 56 see also word and multi-word frequency lists function-to-form 17–18, 47–48, 49–50, 56–67; breadth vs. contextual depth 50–51; one-toone searching 56–60; sampling, searching and sifting 60; solutions for larger corpora 63–67; using existing research findings as ‘seeds’ 61–63 Gablasova, D.V. 209, 210, 223 Garcia-McAllister, P. 60, 142 gathering language data 22–26 gaze direction, analysis of 42 Geluykens, R. 50, 62 genre theory 138–139 gestural deixis 74 Goffman, E. 103, 139 Google Ngram Viewer 165 Grainger, K. 35 grammatical or lexical features, searches of 66 gratitude, expressions of 28, 62–63; collocation of thanks, thank you, cheers 167–170; frequency over time of thanks, thank you, cheers 165–167 Grice, H.P. 132, 175

Han, J. 28, 29 Haugh, M. 128 have: collocates of 10; concordance for 8–13; frequency of words to right of we + 12 have a nice day 98, 101 hedging 110–113; teaching materials on 216–220 Hong Kong Corpus of Spoken English (HKCSE) 39, 230 hooks, lexical 165 see also illocutionary force identifying devices (IFIDs) Hopper, R. 178 I think 204–206 I want 209–210 ICE-Ireland (International Corpus of English: Irish component) 99, 100, 230 idiomatic expressions 103, 134 illocutionary force identifying devices (IFIDs) 17, 53, 53, 63–65, 125, 127, 135; thanks, thank you, cheers 165–167 imperatives in research papers 202–203 implicit vs. explicit pragmatic instruction 197–200 impoliteness 114–119 indirect speech acts 130–131; cooperative principle and 132–134 initiating acts 141 insults 119 integrity 24–26 intentional impoliteness 115, 116 interface debate 197–200 International Corpus of English: Irish component (ICE-Ireland) 99, 100, 230 interviews 33–34 intralingual pragmatic variation 146–147 introspection 21 intuitive: approaches to research 21–26; knowledge 21, 22 Jeon, E.-H. 197, 200, 206 Jones, C.S. 208, 209, 210, 226 Jucker, A.H. 1, 3, 21, 22, 23, 63, 65, 66, 67 Kallen, J. 57 Kasper, G. 28, 30, 33, 133 Kaya, T. 197, 200, 206 Kehoe, A. 50, 64, 65 Kellogg, D. 28 keyword analysis 15–17; registers 184–188 Kirk, J. 57, 58, 59 Kohnen, T. 65 Lakoff, G. 91 Lakoff, R. 110, 122

257

258

INDEX language data: eliciting 26–34; gathering 22–26; inside/outside 22; recording 34–44 language teaching and pragmatics 196–226; across proficiency levels 206–210; classroom materials 210–225; corpora and pragmatics teaching and learning 201–210; future research 225–226; implicit vs. explicit pragmatic instruction 197–200; technologybased opportunities 200–201 language variation 145–172; intralingual pragmatic 146–147; levels of 145–146; pragmatic markers 154–159; response tokens 147–154; speech acts and 165–170; vague language and 159–164 Lazzaro-Salazar, M. 34–35, 45 learner corpus research 19, 226 Levinson, S. 18, 75, 78, 81, 82, 83, 87, 103, 104, 105, 106, 109, 110, 128, 132, 133, 137, 138, 142; criticism of Brown and 113–114 lexical bundles 7, 206, 226n3 lexical hooks 165 see also illocutionary force identifying devices (IFIDs) lexical or grammatical features, searches of 66 Liang, G. 28, 29 Limerick and Belfast Corpus of Academic Spoken English (LIBEL) 15, 38, 222, 231 Limerick Corpus of Intimate Talk (LINT) 160, 161, 163, 183, 231 Limerick Corpus of Irish English (LCIE) 6, 70, 71, 76, 78, 79, 83, 84, 85, 86, 90, 91, 92, 94, 102, 104, 108, 111, 113, 116, 121, 122, 126, 131, 139, 146, 150, 155, 156, 157, 158, 163, 183, 185, 186, 187, 189, 192, 222, 223, 231 linguistic politeness 98–102 locational deixis see place deixis Locher, M. 120 Lutzky, U. 50, 64, 65 Lyons, J. 75, 76, 77, 78, 83, 89 macropragmatics 1 mandatives 142 mark-up, corpus 191–193 materials, developing classroom 210–225; discourse markers 220–223; negative politeness 213–214; positive politeness 210–213; pragmatic markers 216–225; response tokens 223–225; vague language and approximation 214–216 maybe + we 188 McCarthy, M. 13, 19, 47, 69, 111, 145, 147, 149, 150, 154, 164, 176, 177, 182, 197, 213, 214, 216, 217, 220, 223

McEnery, T. 192 metacommunicative expression analysis 66–67 Michigan Corpus of Academic Spoken English (MICASE) 81, 88, 105, 136–137, 202, 204, 206, 231 Michigan Corpus of Upper-level Student Papers (MICUSP) 202–203, 205, 218, 231 micropragmatics 1 migrant children 199 Milà-Garcia, A. 60 mock impoliteness 115, 116–117 Morollón Martí, N. 200 multi-word units (MWUs) 6–8, 14, 155, 156, 158, 188–191; Austen’s novels 190–191; I think 204–206; Sherlock Holmes and Shakespeare’s plays 188–190 multimodal transcription 41–42, 142 multiple-choice task (MCT) questionnaires 29–30 narrow transcription 39 negative face 103, 109, 110 negative impoliteness strategies 115 negative politeness 109–113; teaching aspects of 213–214 Neiderhiser, J.A. 202, 203, 204 Nguyen, T. 196, 197, 199, 225 NHS Direct see Nottingham Health Communication Corpus (NHS Direct component) NMMC (Nottingham Multi-Modal Corpus) 136, 140, 141, 231 nodes 9 non-egocentric deictic centre 77–78 non-phoric references 75–76 Nottingham Health Communication Corpus (NHS Direct component) 124, 133, 134, 180, 181, 185, 186, 231 Nottingham Multi-Modal Corpus (NMMC) 136, 140, 141, 231 NVivo software 34 OANC see Open America National Corpus (OANC) observer’s paradox 35 Ogiermann, E. 27, 28, 29, 45 O’Keeffe, A. 5, 7, 8, 15, 16, 19, 23, 47, 50, 51, 57, 78, 79, 108, 146, 158, 159, 164, 165, 181, 207, 223 one-to-one searching 53, 56–60 Open America National Corpus (OANC) 109, 112, 148, 149, 151, 152, 231 open roleplays 32 oral discourse completion tasks 32

INDEX oral report of a conversation 35 origo see deictic centre Paquot, P. 226 peer-to-peer classroom interactions 199, 201 performatives 125–126 person deixis 78–80 place deixis 80–81 please 99–100 Plester, B. 35 Plonsky, L. 197, 200, 206, 225, 226 pluricentric language 146 politeness 98–123; choice of strategy 113; criticisms of Brown and Levinson 113–114; discursive 119–122; face-saving approach 103–113; impoliteness 114–119; linguistic 98–102; negative 109–113; positive 105–109; teaching aspects of negative 213–214; teaching aspects of positive 210–213 politic behaviour 120–122 positive face 103, 105–106 positive impoliteness strategies 115 positive politeness 105–109; teaching aspects of 210–213 power difference 113 pragmalinguistic competence 196, 197 pragmatic annotation 37–40, 42–44, 56–57, 58–59 pragmatic markers (PM) 154–159; teaching materials on 216–225 preferred response 176 process and protocol 48–50 proficiency levels, pragmatics across 206–210 promises 127–128 pronouns 70, 77, 78–80 receiving time (RT) 82 recording of language 24; research methods for 34–44 redress 105 reference 69–97; basic categories of deixis 78–91; corpus 14, 15; deictic centre 76–78; deixis 72–76; in use 91–95 referential: categories 75–76; items 70–72 register 173–195; comparability at level of turns 174–184; methods for comparing, using a corpus 184–191; variations at level of 173–174 relational work 18, 120, 122 Reppen, R. 37, 53, 56 representativeness 37 requests, felicity conditions for 127–129 research briefing document 25 researcher interference vs. researcher control 23

researching pragmatics 21–46; from intuitive to empirical approaches 21–26; methods for eliciting language data 26–34; methods for recording language data 34–44 response tokens 147–154, 181, 182, 210; teaching materials on 223–225 Roever, C. 30 role enactment 31 roleplays 30–33 routinised language 134–135 Rühlemann, C. 2, 5, 23, 40, 41, 42, 47, 49, 56, 57, 70, 75, 78, 79, 88, 89, 91, 94, 143, 146, 151, 165, 175, 176, 190, 214 Sabat, P.G. 204, 205, 226 Sacks, H. 150, 174, 175 sampling 53–55, 60 Santa Barbara Corpus of Spoken English (SBCSAE) 151, 231 Schauer, G. 28, 50, 61, 62, 68, 165, 168, 170 Schegloff, E. 148, 150, 174, 178 schema 138–139 Schneider, K.P. 21, 27, 28, 30, 33, 45, 145, 146, 197 Searle, J. 57, 127, 129, 130, 131, 135, 138 second order politeness 101–102 ‘seeds,’ using existing research findings as 61–63 seem 112 semantic: preference 13; prosodies 13 semi-structured interviews 34 Shakespeare, W. 188–189 Sherlock Holmes 188–190 short-circuited implicature 134 sifting 55, 60 simulation 31 Sinclair, J. 9, 11, 13, 122, 140, 141 SITCO (Storytelling Interaction Corpus) 42 so 52 social deixis 87–89 social distance 113 sociopragmatic competence 196, 197, 200 software tools 5–17, 43–44 sorry 51–52, 52, 64 see also apologies sort 185 spatial deixis see place deixis speaker: change 175–176, 177–178; information sheets 25 Speech Act Corpus of English (SPACE) 208, 231 Speech Act Theory 125–135; direct and indirect speech acts 130–131; felicity conditions 127–129; indirect speech acts and cooperative principle 132–134; semantics

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INDEX and pragmatics 134–135; speech act classification 129–130 speech acts 124–144; annotation 56–57, 60; classification in discourse analysis 140–143; context 138–140; frames 138–140; genre theory 138–139; identifying and analysing in a corpus 50, 135–138; initiating acts 141; language variation and 165–170; related to conflict and disagreement 28–29; searches of lexical or grammatical features associated with 66; suggestions 135–138 speech events 138, 138–139 speech situations 138 SPICE-Ireland corpus 57, 129, 232 Spoken BNC1994 58, 59, 63, 88, 89, 90, 93, 118, 156, 158, 159, 165, 166, 167, 168, 170, 181, 189, 232 Spoken BNC2014 62, 72, 73, 74, 81, 83, 96, 98, 99, 100, 110, 118, 128, 151, 153, 166, 167, 168, 169, 170, 175, 176, 177, 232 spoken corpus, building a 36–44; design matrix 36–37; pragmatic annotation 42–44; transcription of spoken data 37–42 Staples, S. 202, 206 Storytelling Interaction Corpus (SITCO) 41 structured interviews 34 suggest 126 suggestions 135–138 symbolic deixis 74 Taavitsainen, I. 3, 62, 65, 66, 67 tags 43, 44, 191–193 Tang, X. 201 TART 58 technology-based opportunities for pragmatic learning 200–201 Technology Enhanced Learning (TEL) 200, 226 TED_en corpus 6, 9, 10, 11, 12, 232 terms of address 107–108, 169 thank 121–122 thanks, thank you, cheers: collocation 167–170; frequency 64, 165–167 that 91–95; bloke 92–93; fella 93–94 Thomas, J. 196 time deixis 82–84 TOEFL 2000 Spoken and Written Academic Language Corpus (T2K-SWAL) 60 transcription of spoken data 37–42; challenges of 16–17; codes 38–40; conversation

analysis (CA) 40–41; conversation multimodality 41, 142; time it will take 36 Trinity Lancaster Corpus (TLC) 209, 210, 223, 226, 232 Trump, D. 160 Tsui, A. 137, 141, 142 turn initial items 182, 183 turn sequences 175–176, 177–178 um 150–153 vague category markers (VCMs) 56, 160–164; adjunctive 160–162; disjunctive 163–164 vague language 159–164; teaching materials on 214–216 variables, contextual 2–3 Vaughan, E. 16, 37, 56, 79, 95, 107, 117, 122, 146, 160, 164, 165, 182, 192 video, alignment of transcription and 42 Walsh, S.A. 55, 160 Warren, M. 7, 8, 14, 39 Watts, R. 101, 114, 120 we 79–80; + have 12–13; maybe + 188 Weisser, M. 17, 19, 44, 57, 58 well 150–153 Whalen, M.R. 177, 178 why don’t we? 136–137 why don’t you? 136–137 word and multi-word frequency lists 5–8, 165; Austen’s corpus 191; NHS Corpus and Spoken BNC1994 181; pronouns 70, 78; referential items 70–71; response tokens 149–150; to right of we + have 12–13; Shakespeare’s corpus 189; Sherlock Holmes corpus 189; thank in service encounters 121–122; thanks, thank you, cheers 165–167; time 82–83; turn initial items 183; VCMs 161, 162, 163, 164; word clusters 155–159 word clusters 155–159 would you? 221 written corpora, construction of 35 Yoon, Y.B. 28 Zhang, G.Q. 204, 205, 226 Zhuang, J. 197, 200, 206, 225, 226 Zimmerman, D.H. 177, 178