Lexical Priming in Spoken English Usage

Transcription

1 Lexical Priming in Spoken English Usage

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3 Lexical Priming in Spoken English Usage Michael Pace-Sigge University of Eastern Finland, Finland

4 Michael Pace-Sigge 2013 Softcover reprint of the hardcover 1st edition All rights reserved. No reproduction, copy or transmission of this publication may be made without written permission. No portion of this publication may be reproduced, copied or transmitted save with written permission or in accordance with the provisions of the Copyright, Designs and Patents Act 1988, or under the terms of any licence permitting limited copying issued by the Copyright Licensing Agency, Saffron House, 6 10 Kirby Street, London EC1N 8TS. Any person who does any unauthorized act in relation to this publication may be liable to criminal prosecution and civil claims for damages. The author has asserted his right to be identified as the author of this work in accordance with the Copyright, Designs and Patents Act First published 2013 by PALGRAVE MACMILLAN Palgrave Macmillan in the UK is an imprint of Macmillan Publishers Limited, registered in England, company number , of Houndmills, Basingstoke, Hampshire RG21 6XS. Palgrave Macmillan in the US is a division of St Martin s Press LLC, 175 Fifth Avenue, New York, NY Palgrave Macmillan is the global academic imprint of the above companies and has companies and representatives throughout the world. Palgrave and Macmillan are registered trademarks in the United States, the United Kingdom, Europe and other countries ISBN ISBN (ebook) DOI / This book is printed on paper suitable for recycling and made from fully managed and sustained forest sources. Logging, pulping and manufacturing processes are expected to conform to the environmental regulations of the country of origin. A catalogue record for this book is available from the British Library. A catalog record for this book is available from the Library of Congress.

5 To Katie, with all my head, all my heart

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7 Contents List of Figures List of Tables Preface Acknowledgements xi xii xvi xvii 1 Introduction Where lexical priming came from Lexical priming in spoken use; or, redefining the notion of dialect: the example of Liverpool English Potential value of this work In respect of dialectology In respect of lexical priming in Spoken English The casual spoken Liverpool English Corpus: SCO and its comparators Structure of this book 7 2 Lexical Priming: The Theoretical Backbone Introduction Lexical Priming Where lexical priming came from Collocation Colligation Semantic prosody, preference and association Lexical Priming in Context A brief description of lexical priming Lexical priming and spoken language Lexical priming issues Priming M. Ross Quillian and the language learning machine Facilitating access to the semantic memory Semantic priming of the lexical memory Priming in spoken usage 40 vii

8 viii Contents Priming and how single words are embedded Compound Cues The issue of meaning The value of context Priming and the corpus Lexical Priming and Dialectology 53 3 Testing the Theory through Spoken-Corpus Evidence Building the Liverpool English Corpus (SCO) The use of Scouse as an example General overview of the Liverpool spoken corpus Restrictions Method of SCO compilation Comparing SCO with other spoken English corpora WordSmith concordancing Statistical testing in the research chapters 66 4 Spoken Differs from Written The Case of YES and YEAH The case of spoken usage YEAH Introduction of the term YEAH is not YES Comparison of YES and YEAH collocates Comparison of YES vs. YEAH clusters Comparison of YES vs. YEAH conclusion YEAH use in the Corpora YEAH collocates in the SCO and BNC/C corpora Most frequent YEAH clusters detailed use YEAH with BUT YEAH with OH Repetition clusters of YEAH YEAH with RIGHT Conclusions for YEAH 80 5 Referring to Oneself and Others in SCO and BNC/C Introduction to I I in the spoken corpora I collocates Differences in ranking Collocates with different proportional use I Usage and Nesting I two-word clusters 87

9 I two-word clusters: Areas of divergent use I two-word clusters: SCO more frequent than expected I two-word clusters: SCO less frequent than expected Longest-available clusters You know, what I, I mean two-word clusters form a longer meaningful cluster Conclusions of I usage in the corpora Third-party referents a difference in degree, not in usage 97 6 Use of Intensifiers and Discourse Particles in Casual Speech Uses of WELL Introduction WELL collocates WELL clusters: points of divergence WELL Conclusions VERY a comprehensive indicator VERY a signifier of speaker age in SCO? VERY differences are very absent VERY conclusions The use of REALLY in casual speech REALLY and how it occurs Occurrence differences found in the corpora I REALLY CAN T Repetition of REALLY Conclusions The Uses of JUST and LIKE JUST frequent with pronouns Collocates of JUST in SCO and BNC/C JUST clusters JUST 2w clusters JUST 3w clusters JUST Conclusions A view on the many uses of LIKE Comparison of the top collocates of LIKE LIKE usage: Divergence in 2w to 4w clusters w clusters w and 4w clusters LIKE and the personal pronoun THEY 133 ix

10 x Contents LIKE and past tense use LIKE with vague terms Conclusions about the use of LIKE The Most Frequent Clusters Found in Casually Spoken English Corpora Introduction Selecting Suitable Clusters Frequent cluster groups in SCO A broad comparison of SCO s most frequent clusters with those in BNC/C A closer comparison: How do the occurrences appear? The KNOW Group Most frequent KNOW group clusters in SCO compared The MEAN Group SCO most frequent MEAN group clusters compared to BNC/C The most frequent MEAN group clusters The LIKE Group Comparing the most frequent like group clusters in SCO and BNC/C The characteristic use of LIKE group clusters The THINK Group Clusters using DON T THINK negation SCO distinctive use within the THINK group The TO Group SCO TO group clusters less preferred SCO TO group clusters more preferred The HONEST Group Conclusions on comparing SCO with BNC/C clusters Comparing Liverpool and London Speakers Conclusions 177 Appendices 181 Notes 192 Bibliography 202 Index 217

11 List of Figures 2.1 Adapted from Stubbs (2008a: 179) Adapted from Hoey (2005: 13) Linear Unit Grammar features. After Sinclair & Mauranen (2006: xviii) Known economic background of 45 of the SCO informants Background of the Informants, to determine whether they and/or their families have always lived in Liverpool That s right yeah selection of SCO concordance lines I don t know whether concordance lines in SCO you know what I mean concordance lines in SCO (excerpt) do you know what I mean concordance lines in BNC/C (excerpt) All Well I concordance lines in SCO really single word multiple repetition as found in the BNC/C (excerpt) just listen to concordance lines in SCO All just listen to concordance lines in BNC/C like post-positioned in SCO You go like in SCO You go like in BNC/C (total number of occurrences) and stuff like that all SCO concordance lines and stuff like that selection of BNC/C concordance lines All occurrences of honest in SCO All occurrences of to be honest with you in the BNC/C All I mean I concordance lines in SCO Selection of I mean I concordance lines in LDN-H 175 xi

12 List of Tables 2.1 Results of Ellis (2006a) summarised Direct comparison of yeah and yes proportional frequencies and collocate patterns in SCO, BNC/C and BoE. Written BNC (BNC/W) figures as comparison yeah and yes top clusters compared in five corpora yeah top 10 collocates comparison of SCO and BNC/C Most frequent two to four-word SCO yeah clusters yeah with but in SCO and BNC/C yeah with oh clusters in SCO and BNC/C yeah repetition clusters compared yeah 3w clusters with right compared I use in three spoken corpora: Liverpool (SCO), BNC Conversation, Bank of English (BoE) and London Hackney speakers (LDN) most frequent collocates to SCO I compared to BNC/C occurrences Collocates with highest difference in SCO: BNC/C comparison Chunks with I amongst CANCODE top 20 2w chunks Most frequent 2w clusters (chunks) with I in SCO and BNC/C. Percentages are of the total respective occurrences of I SCO 2w I clusters more frequent than expected I 2w clusters SCO less frequent Longest I clusters in SCO and BNC/C equivalents you know, I mean and what I occurrence percentages in the BNC/C compared to SCO The most frequent discourse markers in SCO, comparative frequencies in the BNC/C Statistical testing of well occurrence Ten most frequent well collocates in SCO compared to BNC/C equivalents Key 2w well clusters in SCO compared to BNC/C Divergence of use in well 2 3w clusters SCO compared to BNC/C 108 xii

13 List of Tables xiii 6.6 very top collocates in SCO and the figures for those collocates in BNC/C Most divergent 2w very clusters in SCO and BNC/C really in SCO, MAC and BNC/C occurrences Top 12 collocates for really in SCO and BNC/C equivalents Occurance pattern of multiple single-word repetition of really SCO and BNC/C Just most frequently occurring collocates in SCO and BNC/C. ( percentages relative to the total number of just Most frequent just 2w clusters where there is no divergence between the corpora Most frequent divergent SCO just 2w clusters and their BNC/C equivalents Most frequent 3w clusters incorporating I just in SCO and BNC/C. Percentages as of total JUST occurrences Most frequent divergent SCO just 3w clusters and their BNC/C equivalents Statistical testing of like use Top collocates of like in SCO and BNC/C in their respective ranking order (percentages, apart from top-line, are in relation to the total occurrences of the core term like) Top 12 2w like clusters in SCO and their BNC/C equivalents Divergent long like clusters in SCO and their BNC/C equivalents a like with they top clusters in SCO and the BNC/C equivalents b like with they top clusters in SCO and equivalent figures for the BNC/C (with examples) was like cluster comparison (percentages proportional to LIKE total) in SCO and BNC/C Comparative use like with vagueness markers in SCO and BNC/C a SCO selection of most frequent 3w to 5w clusters b BNC/C and LDN-H 5 most frequent 3w clusters and the most frequent 4w cluster w to 5w SCO cluster keyness when compared to BNC/C clusters 147

14 xiv List of Tables 8.3 SCO highest frequency clusters compared to BNC/C frequencies a Highest frequency KNOW Group clusters in SCO and BNC/C b Highest frequency KNOW Group clusters by occurrence rank Statistical testing of KNOW Group clusters; SCO in relation to BNC/C a Highest frequency MEAN Group clusters in SCO and BNC/C b Highest frequency MEAN Group clusters in SCO and BNC/C Highest frequency MEAN group clusters in SCO and BNC/C ordered by cluster and rank Statistical testing of MEAN Group clusters; SCO in relation to BNC/C a Highest occurring LIKE Group clusters in SCO and BNC/C b Highest occurring LIKE Group clusters in SCO and BNC/C in direct comparison Statistical testing of KNOW Group clusters; SCO in relation to BNC/C Five highest frequency THINK Group clusters in with occurrence rank Don t think cluster occurrence in SCO compared to BNC/C SCO THINK Group occurrence patterns significantly different a Highest frequency TO Group clusters SCO and BNC/C b Highest frequency TO Group clusters in SCO directly compared to BNC/C occurrence (ranking given before each cluster) TO Group clusters which are less frequently found in SCO TO Group clusters which are more frequently found in SCO (arranged by word groups) Highest frequency HONEST Group 3 5w clusters by occurrence rank Areas of strongest divergence where SCO and BNC/C honest clusters are compared 171

15 List of Tables xv 8.18 Comparison of the clusters found most significantly divergent compared to BNC/C with their use of Hackney (London) speakers 174 Full version of following tables are in Appendices 8.1(a) SCO top 50 most frequent 3 5w clusters (Appendix V.1) (b) SCO top 50 most frequent 3 5w OF clusters (Appendix V.2 ) (b) 3 5 word SCO cluster Keyness when compared to BNC/C clusters (Appendix V.3) (c) Highest frequency LIKE Group clusters in SCO and BNC/C respectively (Appendix V.4 ) (b) Highest frequency THINK Group clusters in with occurrence rank. (SCO frequency ranking 1 9 as lead) (Appendix V.5) 190

16 Preface Corpus Linguistics is becoming an increasingly important branch of language research, and interest in computer-based analysis has spread noticeably beyond the confines of academia, fuelled by applications like text-predicting software for use in mobile phones and by search engines like Google. Hoey (2002, 2003a,b,c, 2004, 2005) presented a theory that provides a set of rules that are possibly underpinning why Corpus Linguistics works as a way of analysing language. Lexical priming can be seen as an explanation of why collocations (words that are found in the company of each other) exist. A listener will recognise a word more quickly when a related word is given (e.g. surgeon heart). However, the theory is dependent on evidence of psycholinguistic and cognitive science claims. We cannot modify an approach to teaching language unless we are confident that we have sound evidence. Since lexical priming will have implications for both the learning and the teaching of language, this book, firstly, presents a range of arguments to support lexical priming as a linguistic theory and, to an extent, provides material to supplement Hoey s 2005 book. Secondly, the book aims to expand the reach of what lexical priming applies to. While all the original research is based on written texts, this book offers statistically significant evidence that lexical priming is also found in everyday spoken conversations. To this end, proportional frequencies and occurrence patterns of frequent lexical items are investigated. As to the material employed for an in-depth case study, transcribed recordings of Liverpool speakers are compared with evidence found in the BNC/Spoken/Conversation corpus. In addition, more recent data collected in London are presented. xvi

17 Acknowledgements It is a long time since I sat in a postgraduate seminar at the University of Liverpool on a Wednesday afternoon in 2003 and listened to a presentation about lexical priming. Michael Hoey appeared to give, with his theory, a lot of answers that traditional grammar seemed unable to provide for me. One of the results of that afternoon is the present book, which looks at where the theory came from, examines its roots, and points to one direction in which it can be taken describing spoken language forms. There are a lot of people who need to be acknowledged, all of them crucial to the process of making this publication possible. Thanks in the first instance must go to Michael Hoey: without his lexical priming theory I might not have been inspired enough to undertake this work. Thanks are also due to Andrew Hamer, whose inspiration, enthusiasm and support awakened my interest in researching Liverpool English, the variant commonly referred to as Scouse, and Mike Scott, without whose WordSmith (versions 4 6) and ready advice with regard to the software my corpus-based research would not have been possible. My thanks too to the colleagues who gave valuable material and advice: Siobhan Chapman, Costas Gabrielatos, Paul Kerswill, Ramesh Krishnamurthy, Tony McEnery, Anne O Keefe, Ute Römer, Geoff Thompson, Clive Upton and Kevin Watson. Many thanks also go to my editor, Olivia Middleton, to the two anonymous reviewers of the original script and also to my proofreaders, Katie Patterson and Jess Pope, for their most valuable advice for the final edit. Finally, beyond the realm of academe, credit must go to the woman who never stopped believing in me my mother. xvii