Qualitative_data_analysis

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REFERENCES 287 Sperber, Dan and Wilson, Deirdre (1986) Relevance, Communication and Cognition, Harvard University Press. Strauss, Anselm L. (1987) Qualitative Analysis for Social Scientists, Cambridge: Cambridge University Press. Strauss, Anselm L. and Corbin, Juliet (1990) Basics of Qualitative Research Grounded Theory Procedures and Techniques, London: Sage. Tesch, Renata (1990) Qualitative Research: Analysis Types and Software Tools, London and Philadelphia: Falmer Press. Tesch, Renata (1991) ‘Software for Qualitative Researchers: Analysis Needs and Programme Capabilities’ in Fielding, Nigel G. and Lee, Raymond M. (eds) Using Computers in Qualitative Research, London: Sage. Thomas, Philip (1991) ‘Let Him Have It’ in Empire The Monthly Guide to the Movies, November, pp. 82–86. Trow, M.J. (1992) ‘Let Him Have it Chris’: The Murder of Derek Bentley, Great Britain: Grafton. Varley, Helen (1983) Colour, London: Marshall Editions. Wilson, John Dover (1936) Hamlet, Cambridge: Cambridge University Press. Winter, Henry (1991) ‘Liverpool Require a New Forward Plan’, The Independent, 25th November. Wood, Victoria (1985) Up to You, Porky: The Victoria Wood Sketch Book, London: Methuen. Wood, Victoria (1990) Mens Sana in Thingummy Doodah, London: Methuen.
abstracting data 99, 116, 135; see also categories; classification academic literature see literature account, producing 86, 244–63, 272–6, 274; acceptability 257–63; developing a plan 248; function 248–2, 257–50; Hypersoft and 281; language 252–6, 254; materials and their selection 249–5; as objective of analysis 48, 53; reliability 258–3, 268; representativeness 268–3; traditional forms of publication 267; validity 258, 260–61; writing strategies 254–9; see also text advertising 34, 50 algorithms 259, 259, 260 Allen, Woody: humour used as example for analysis see individual processes; text of ‘If the Impressionists had been Dentists’ 276–72 annotating data see memos association between categories and variables 28, 48–51, 179–80, 200 audio material: computer and 57; transcription of 75 auditing analysis 246–40; use of computer for 62, 275 Index 288 Baxandall, M. 12 bar charts 216 Becker, H. 7, 8, 29, 53, 110, 232, 254 Bettelheim, B. 33, 34, 246, 253 bias 64, 91, 127, 232, 233, 235, 237, 241, 268; see also objectivity; subjectivity bits of data 18–19; classification see classification; coding see coding data; and connecting categories see connections between categories; and creation of categories see under categories; generation of 121–18, 127–1, 210, 211; and grounded theory 109; labelling 102, 127; and linking see linking; mapping used to indicate databits in chronological sequence 225–18; and recontextualization see categories, splitting and splicing; subdividing 146–9 Blalock, H.M. 11 Bliss, J. 5, 7, 53, 145, 166 Bogdan, R.C. 87 Bohm, D. 18, 19, 30, 249 boolean operators 152, 182, 235, 280 Brooks, C. 99 Brown, Andrew 73 Bryman, A. 5, 18, 229, 274 Burgess, R. 5, 40, 254 Burke, Edmund 86 Buzan, T. 86, 92, 200
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Qualitative data analysis Learning
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First published 1993 by Routledge 1
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Glossary 283 References 285 Index 2
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9.1 Categorizing data—1 120 9.2 C
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3.1 Personal ads 42 5.1 ‘The libr
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Preface A new book on qualitative d
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analyse humour from any number of p
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Q. What colour is snow? A. White. C
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INTRODUCTION 3 approaches, interest
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INTRODUCTION 5 qualitative methods.
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INTRODUCTION 7 First of all, I take
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INTRODUCTION 9 the purposes of anal
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WHAT IS QUALITATIVE DATA? 11 distan
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WHAT IS QUALITATIVE DATA? 13 contem
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WHAT IS QUALITATIVE DATA? 15 ‘ric
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classified. Take the example in Ill
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Figure 2.1 Describing a bit of data
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WHAT IS QUALITATIVE DATA? 21 home;
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Figure 2.4 Nominal variable with mu
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Figure 2.6 Interval variable with f
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ILLUSTRATION 2.2 EXAMPLE OF A GRADI
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WHAT IS QUALITATIVE DATA? 29 what a
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Chapter 3 What is qualitative analy
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Figure 3.2 Three aspects of descrip
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WHAT IS QUALITATIVE ANALYSIS? 35 co
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WHAT IS QUALITATIVE ANALYSIS? 37 en
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WHAT IS QUALITATIVE ANALYSIS? 39 Th
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CLASSIFICATION WHAT IS QUALITATIVE
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nature; photograph preferred but no
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WHAT IS QUALITATIVE ANALYSIS? 45 vi
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WHAT IS QUALITATIVE ANALYSIS? 47 Fi
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Figure 3.6 Formal and substantive c
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WHAT IS QUALITATIVE ANALYSIS? 51 ne
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WHAT IS QUALITATIVE ANALYSIS? 53 If
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Figure 3.10 Qualitative analysis as
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Chapter 4 Introducing computers ‘
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ecording of an index of information
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Figure 4.1 A link between text held
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Computer transformations • Search
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Chapter 5 Finding a focus A Zen sto
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FINDING A FOCUS 67 Sheila The solic
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FINDING A FOCUS 69 to reflect upon
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For example, here are some question
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Transposition: Doctor: ‘I’m afr
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Figure 5.2 Main themes for analysin
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Chapter 6 Managing data Piles of pa
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MANAGING DATA 79 setting, by source
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MANAGING DATA 81 Interviewer Maybe
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Figure 6.1 Case documents kept in a
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MANAGING DATA 85 ‘Show the full r
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Chapter 7 Reading and annotating Ac
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• Official/bureaucratic commitmen
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READING AND ANNOTATING 91 women wer
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Techniques for interactive reading
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we can write our comment on a separ
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Figure 7.1 Relating data to key the
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READING AND ANNOTATING 99 may retur
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CREATING CATEGORIES 101 types of ph
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CREATING CATEGORIES 103 conceptual
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CREATING CATEGORIES 105 Categorizat
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Table 8.1 Alternative category list
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This is only a starting point. Our
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CREATING CATEGORIES 111 undertaking
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Figure 8.2 Weighing up the degree o
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CREATING CATEGORIES 115 Although co
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CREATING CATEGORIES 117 for an adeq
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CREATING CATEGORIES 119 well as con
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Figure 9.2 Categorizing data—2 Fi
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are entitled to expect some consist
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ASSIGNING CATEGORIES 125 we ought t
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ASSIGNING CATEGORIES 127 the data.
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have annotated this data. Suppose w
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ASSIGNING CATEGORIES 131 suddenly t
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• What generally constitutes a
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Databits Categories 5. Now she is u
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Chapter 10 Splitting and splicing T
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Using Hypertext linking, whenever n
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SPLITTING AND SPLICING 141 databits
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Category Subcategories Suffering Di
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Figure 10.1 Levels of subclassifica
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ILLUSTRATION 10.5 SUBDIVIDING DATAB
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Figure 10.2 Initial relationships b
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If we want to make this change, it
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Figure 10.5 Reassessing relationshi
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SPLITTING AND SPLICING 155 Although
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Figure 10.8 Comparing subcategories
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Figure 10.9 Shifting the analytic e
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Chapter 11 Linking data Categorizin
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Figure 11.2 Multiple hyperlinks bet
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example, we may ask what it is abou
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Figure 11.5 Linking and categorizin
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Figure 11.7 An explanatory link bet
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Table 11.2 Multiple links between d
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our reasons for making decisions an
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Figure 11.11 Conditional and causal
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Chapter 12 Making connections Imagi
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Figure 12.1 The difference between
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Table 12.1 Concurrence between cate
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Table 12.4 Boolean operators for ca
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From Table 12.6 we can tell that mo
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Notice how this cross-tabulation co
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substantive connections between cat
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Figure 12.5 Following a trail of di
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Figure 12.7 Retrieving chronologica
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This approach is very exploratory,
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MAKING CONNECTIONS 197 Table 12.10
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MAKING CONNECTIONS 199 a consequenc
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Chapter 13 Of maps and matrices A n
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Table 13.1 Comparing information ac
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OF MAPS AND MATRICES 205 [In a calm
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Table 13.5 Data indices by case and
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Table 13.7 Recoding data to express
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Table 13.11 Cross-tabulating ‘occ
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Figure. 13.4 The history of the uni
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Figure 13.7 Incorporating detail by
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Figure 13.10 Comparing differences
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Figure 13.13 Adjusting scope of mos
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Figure 13.17 Comparing strength of
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Figure 13.20 Identifying positive a
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OF MAPS AND MATRICES 225 undercurre
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Chapter 14 Corroborating evidence
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CORROBORATING EVIDENCE 229 There is
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CORROBORATING EVIDENCE 231 describe
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CORROBORATING EVIDENCE 233 of these
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Figure 14.1 Concurrence between cat
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Page 258 and 259: CORROBORATING EVIDENCE 243 research
Page 260 and 261: Chapter 15 Producing an account ‘
Page 262 and 263: PRODUCING AN ACCOUNT 247 An analysi
Page 264 and 265: Figure 15.2 The whole is greater th
Page 266 and 267: Figure 15.3 Tree diagrams represent
Page 268 and 269: PRODUCING AN ACCOUNT 253 associatio
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Page 272 and 273: Figure 15.5 Different writing strat
Page 274 and 275: PRODUCING AN ACCOUNT 259 the vibrat
Page 276 and 277: Figure 15.7 Procedures for assignin
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Page 280 and 281: Table 15.1 Databits assigned to cat
Page 282 and 283: Table 15.3 Distribution of response
Page 284 and 285: PRODUCING AN ACCOUNT 269 To be subj
Page 286 and 287: PRODUCING AN ACCOUNT 271 analysts t
Page 288 and 289: Figure 16.3 Analysis as an iterativ
Page 290 and 291: CONCLUSION 275 empirical analysis o
Page 292 and 293: Appendix 1 ‘If the Impressionists
Page 294 and 295: APPENDIX 1 279 though it had been o
Page 296 and 297: Appendix 2 Software The reader look
Page 298 and 299: Glossary Associating categories the
Page 300 and 301: References Allen, Woody (1978) ‘I
Page 304 and 305: Capra, F. 29, 64, 99 case studies 1
Page 306 and 307: Galtung, J. 14 Geer, B. 7, 8, 29, 5
Page 308 and 309: connections; description qualitativ
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