Qualitative_data_analysis

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APPENDIX 1 279 though it had been only four days.) Theo, she drives me mad! Wild with desire! Her bite! I’ve never seen such a bite! Her teeth come together perfectly! Not like Mrs Itkin’s, whose lower teeth are forward of her uppers by an inch, giving her an underbite that resembles that of a werewolf! No! Claire’s teeth close and meet! When this happens you know there is a God! And yet she’s not too perfect. Not so flawless as to be uninteresting. She has a space between lower nine and eleven. Ten was lost during her adolescence. Suddenly and without warning it developed a cavity. It was removed rather easily (actually it fell out while she was talking) and never replaced. ‘Nothing could replace lower ten’ she told me. ‘It was more than a tooth, it had been my life to that point.’ The tooth was rarely discussed as she got older and I think she was only willing to speak of it to me because she trusts me. Oh, Theo, I love her. I was looking down into her mouth today and I was like a nervous young dental student again, dropping swabs and mirrors in there. Later I had my arms around her, showing her the proper way to brush. The sweet little fool was used to holding the brush still and moving her head from side to side. Next Thursday I will give her gas and ask her to marry me. Vincent. Dear Theo Gauguin and I had another fight and he has left for Tahiti! He was in the midst of an extraction when I disturbed him. He had his knee on Mr Nat Feldman’s chest with the pliers around the man’s upper right molar. There was the usual struggle and I had the misfortune to enter and ask Gauguin if he had seen my felt hat. Distracted, Gauguin lost his grip on the tooth and Feldman took advantage of the lapse to bolt from the chair and race out of the office. Gauguin flew into a frenzy. He held my head under the X-ray machine for ten straight minutes and for several hours after I could not blink my eyes in unison. Now I am lonely. Vincent. Dear Theo All is lost! Today being the day I planned to ask Claire to marry me, I was a bit tense. She was magnificent in her white organdy dress, straw hat, and receding gums. As she sat in the chair, the draining hook in her mouth, my heart thundered. I tried to be romantic. I lowered the lights and tried to move the conversation to gay topics. We both took a little gas. When the moment seemed correct, I looked her directly in the eye and said, ‘Please rinse’. And she laughed! Yes, Theo! She laughed at me and then grew angry! ‘do you think I could rinse for a man like you!? What a joke!’ I said, ‘Please, you don’t understand’. She said, ‘I understand quite well! I could never rinse with anyone but a licensed orthodontist! Why, the thought I would rinse here! Get away from me!’ And with that she ran out weeping. Theo! I want to die! I see my face in the mirror and I want to smash it! Smash it! Hope you are well.
280 QUALITATIVE DATA ANALYSIS Vincent. Dear Theo Yes, it’s true. The ear on sale at Fleishman Brothers Novelty Shop is mine. I guess it was a foolish thing to do but I wanted to send Claire a birthday present last Sunday and every place was closed. Oh, Well. Sometimes I wish I had listened to father and become a painter. It’s not exciting but the life is regular.
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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
Page 244 and 245: CORROBORATING EVIDENCE 229 There is
Page 246 and 247: CORROBORATING EVIDENCE 231 describe
Page 248 and 249: CORROBORATING EVIDENCE 233 of these
Page 250 and 251: Figure 14.1 Concurrence between cat
Page 252 and 253: CORROBORATING EVIDENCE 237 possibil
Page 254 and 255: CORROBORATING EVIDENCE 239 that the
Page 256 and 257: CORROBORATING EVIDENCE 241 seductiv
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
Page 270 and 271: worrying unduly about the connectio
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
Page 278 and 279: PRODUCING AN ACCOUNT 263 consistent
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 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 302 and 303: REFERENCES 287 Sperber, Dan and Wil
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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