Qualitative_data_analysis

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3.1 Personal ads 42 5.1 ‘The library’ 66 5.2 Comments on feminist humour 70 6.1 ‘Two attendants at a Turkish Bath’ 78 6.2 Recording data fully but inefficiently 80 6.3 Filing reference information—questions and sources 81 6.4 Data filed efficiently 82 7.1 ‘In the Office’ 89 7.2 Using memos to open up lines of enquiry 94 7.3 Linking memos and data 95 8.1 Preliminary definitions of categories 109 8.2 Developing a more extensive category list 113 9.1 Two ways of identifying ‘bits’ of data 123 9.2 Overlapping bits of data 124 9.3 A preliminary category list 126 9.4 Checking memos prior to categorizing data 129 9.5 Contrasting definitions of the category ‘temperament’ 130 9.6 Inferring an emotional state from behaviour 130 9.7 Data stored following categorization of a databit 132 9.8 Categorizing Vincent’s first letter 134 10.1 Comparing databits assigned to different categories 138 10.2 Databits assigned to the category ‘suffering’ 138 10.3 Subcategories of ‘suffering’ 142 10.4 Subcategorized databits for the category ‘suffering’ 146 10.5 Subdividing databits between subcategories 147 10.6 Comparing databits between categories 151 11.1 Possible links 165 11.2 Information held on linked databits 173 TABLES 3.1 Implicit classifications in everyday life 42 8.1 Alternative category lists 107 11.1 Result of linking and categorizing two databits 170 11.2 Multiple links between databits 171 11.3 Linking non-sequential databits 171 12.1 Concurrence between categories 181 12.2 Comparing databits between the different cells 182 12.3 List of indexed databits 182 ix
x 12.4 Boolean operators for category retrievals 183 12.5 Retrieval based on categories assigned to proximate bits of data 184 12.6 Retrieval based on categories ‘temperament’ and ‘suffering’ assigned to184 proximate bits of data 12.7 Categories analysed as case variables 186 12.8 Cross-tabulating categories as case variables: ‘temperament’ and ‘suffering’ in Vincent’s letters (N=0) 186 12.9 Identifying connections between categories for databits assigned to 195 category ‘suffering’ and databits linked to these by the link ‘caused by’ 12.10 Connecting ‘X’ categories ‘transposing’ and ‘temperament’ to ‘Y’ category ‘suffering’ through causal links between the databits 197 13.1 Comparing information across cases 203 13.2 Matrix with non-exclusive values 203 13.3 Using a matrix to explore variation in the data 204 13.4 Databits by case and category 206 13.5 Data indices by case and category 207 13.6 The number of assignations of each category by case 207 13.7 Recoding the data to express more meaningful values 209 13.8 Analysing subcategories as separate variables 209 13.9 Recategorizing variables as values of ‘suffering’ 210 13.10 Frequencies for the variable ‘suffering’ 210 13.11 Cross-tabulating ‘occupation’ and ‘suffering’ 211 15.1 Databits assigned to categories ‘active’ and ‘passive’ 265 15.2 ‘Passive’ and ‘active’ responses by gender 266 15.3 Distribution of responses by case 267
Page 2 and 3: Qualitative data analysis Learning
Page 4 and 5: First published 1993 by Routledge 1
Page 6 and 7: Glossary 283 References 285 Index 2
Page 8 and 9: 9.1 Categorizing data—1 120 9.2 C
Page 12 and 13: Preface A new book on qualitative d
Page 14 and 15: analyse humour from any number of p
Page 16 and 17: Q. What colour is snow? A. White. C
Page 18 and 19: INTRODUCTION 3 approaches, interest
Page 20 and 21: INTRODUCTION 5 qualitative methods.
Page 22 and 23: INTRODUCTION 7 First of all, I take
Page 24 and 25: INTRODUCTION 9 the purposes of anal
Page 26 and 27: WHAT IS QUALITATIVE DATA? 11 distan
Page 28 and 29: WHAT IS QUALITATIVE DATA? 13 contem
Page 30 and 31: WHAT IS QUALITATIVE DATA? 15 ‘ric
Page 32 and 33: classified. Take the example in Ill
Page 34 and 35: Figure 2.1 Describing a bit of data
Page 36 and 37: WHAT IS QUALITATIVE DATA? 21 home;
Page 38 and 39: Figure 2.4 Nominal variable with mu
Page 40 and 41: Figure 2.6 Interval variable with f
Page 42 and 43: ILLUSTRATION 2.2 EXAMPLE OF A GRADI
Page 44 and 45: WHAT IS QUALITATIVE DATA? 29 what a
Page 46 and 47: Chapter 3 What is qualitative analy
Page 48 and 49: Figure 3.2 Three aspects of descrip
Page 50 and 51: WHAT IS QUALITATIVE ANALYSIS? 35 co
Page 52 and 53: WHAT IS QUALITATIVE ANALYSIS? 37 en
Page 54 and 55: WHAT IS QUALITATIVE ANALYSIS? 39 Th
Page 56 and 57: CLASSIFICATION WHAT IS QUALITATIVE
Page 58 and 59: nature; photograph preferred but no
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WHAT IS QUALITATIVE ANALYSIS? 45 vi
Page 62 and 63:
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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CORROBORATING EVIDENCE 237 possibil
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CORROBORATING EVIDENCE 239 that the
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CORROBORATING EVIDENCE 241 seductiv
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CORROBORATING EVIDENCE 243 research
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Chapter 15 Producing an account ‘
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PRODUCING AN ACCOUNT 247 An analysi
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Figure 15.2 The whole is greater th
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Figure 15.3 Tree diagrams represent
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PRODUCING AN ACCOUNT 253 associatio
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worrying unduly about the connectio
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Figure 15.5 Different writing strat
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PRODUCING AN ACCOUNT 259 the vibrat
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Figure 15.7 Procedures for assignin
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PRODUCING AN ACCOUNT 263 consistent
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Table 15.1 Databits assigned to cat
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Table 15.3 Distribution of response
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PRODUCING AN ACCOUNT 269 To be subj
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PRODUCING AN ACCOUNT 271 analysts t
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Figure 16.3 Analysis as an iterativ
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CONCLUSION 275 empirical analysis o
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Appendix 1 ‘If the Impressionists
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APPENDIX 1 279 though it had been o
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Appendix 2 Software The reader look
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Glossary Associating categories the
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References Allen, Woody (1978) ‘I
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REFERENCES 287 Sperber, Dan and Wil
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Capra, F. 29, 64, 99 case studies 1
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Galtung, J. 14 Geer, B. 7, 8, 29, 5
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connections; description qualitativ
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