Qualitative_data_analysis

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MAKING CONNECTIONS 199 a consequence of the imbalance in power arising from their respective social roles. In this way we can try to establish and account for the causal connection between the two categories. Finally, what of the connection between incongruity and cathartic humour? The causal mechanism connecting these two categories (via ‘temperament’ and ‘suffering’) centres on the dentist-patient relationship. However, we also have to consider whether the categories may be connected in other ways. For example, does cathartic humour which focuses on fears of the patient role depend for its effectiveness—as humour —#8212;on the creation of incongruous images and absurd behaviour? Is there a necessary connection between the two? Is there a contingent relation, such that we laugh more readily at suffering in an incongruous context, but we might laugh all the same? Do we laugh more readily at incongruity, when catharsis adds a certain spice to the proceedings? Or is there no connection between the two at all? Having established that there are some connections between transpositions of temperament and patient suffering, these are issues which we can explore through a thorough qualitative assessment of the data. To offer one example, consider the connection between Vincent being ‘like a nervous young dental student again’ and his ‘dropping swabs and mirrors’ in Claire’s mouth. Does the incongruous image of Vincent as a nervous young dental student make it easier for us to enjoy a laugh at the unfortunate result for Claire? I think it does: if this incongruous image is removed, the event is less obviously humorous. This interpretation is further reinforced by another incongruous image, for Vincent exaggerates to the point of absurdity in claiming to drop impossibly large objects into Claire’s mouth. The lack of realism reassures us that this episode did not occur as narrated, and this makes it easier to find it funny. Now suppose Vincent had dropped his swabs and mirrors on the floor, rather than in Claire’s mouth. Once again, we may doubt whether this would have a similarly humorous effect. The cathartic element seems important in giving a comic edge to the incident, at least as it is narrated on paper. Now imagine a film version of this event. On screen, it would be impossible (without special effects) to drop swabs and mirrors into Claire’s mouth. However, the floor may do just as well, for on screen we may identify more fully with Vincent and empathise more readily with his embarrassment and clumsy gaucherie towards Claire. Here too, the effectiveness of the humour may reside in its cathartic effect in relation to our own fears of embarrassment and humiliation. The technique we have used to explore this example is not unfamiliar— we discussed ‘transposing data’ as a technique to enhance the interactive reading of text. The same techniques can contribute to elucidating the existence and character of connecting mechanisms.
200 QUALITATIVE DATA ANALYSIS Each of the procedures we have considered in this chapter depends on combining evidence of empirical association between categories with a conceptual appraisal of connecting mechanisms. The difference between them lies mainly in precedence and priority. The procedure for analysing association between categories puts regularity first on the agenda, but then requires conceptual appraisal of the data to confirm whether or not connnecting mechanisms are operating. The procedure for analysing categories connected through linked data puts the conceptual appraisal of connecting mechanisms first, and then requires some assessment of the regularity with which these occur in the data. While neither approach has a monopoly of virtue, connecting categories through linking data has advantages worth noting. First of all, it allows for information about possible connections between bits of data to be observed directly during the initial analysis of the data, rather than trying to identify these post hoc following observed association between categories. Secondly, it allows this evidence to be recorded systematically, so that it can retrieved and analysed thoroughly and comprehensively. By comparison, to go beyond observations of associations between categories without the evidence of linked data, we may once again have to fall back on impressionistic and unsystematic procedures characteristic of more traditional analysis.
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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
Page 164 and 165: Figure 10.2 Initial relationships b
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Page 168 and 169: Figure 10.5 Reassessing relationshi
Page 170 and 171: SPLITTING AND SPLICING 155 Although
Page 172 and 173: Figure 10.8 Comparing subcategories
Page 174 and 175: Figure 10.9 Shifting the analytic e
Page 176 and 177: Chapter 11 Linking data Categorizin
Page 178 and 179: Figure 11.2 Multiple hyperlinks bet
Page 180 and 181: example, we may ask what it is abou
Page 182 and 183: Figure 11.5 Linking and categorizin
Page 184 and 185: Figure 11.7 An explanatory link bet
Page 186 and 187: Table 11.2 Multiple links between d
Page 188 and 189: our reasons for making decisions an
Page 190 and 191: Figure 11.11 Conditional and causal
Page 192 and 193: Chapter 12 Making connections Imagi
Page 194 and 195: Figure 12.1 The difference between
Page 196 and 197: Table 12.1 Concurrence between cate
Page 198 and 199: Table 12.4 Boolean operators for ca
Page 200 and 201: From Table 12.6 we can tell that mo
Page 202 and 203: Notice how this cross-tabulation co
Page 204 and 205: substantive connections between cat
Page 206 and 207: Figure 12.5 Following a trail of di
Page 208 and 209: Figure 12.7 Retrieving chronologica
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Page 212 and 213: MAKING CONNECTIONS 197 Table 12.10
Page 216 and 217: Chapter 13 Of maps and matrices A n
Page 218 and 219: Table 13.1 Comparing information ac
Page 220 and 221: OF MAPS AND MATRICES 205 [In a calm
Page 222 and 223: Table 13.5 Data indices by case and
Page 224 and 225: Table 13.7 Recoding data to express
Page 226 and 227: Table 13.11 Cross-tabulating ‘occ
Page 228 and 229: Figure. 13.4 The history of the uni
Page 230 and 231: Figure 13.7 Incorporating detail by
Page 232 and 233: Figure 13.10 Comparing differences
Page 234 and 235: Figure 13.13 Adjusting scope of mos
Page 236 and 237: Figure 13.17 Comparing strength of
Page 238 and 239: Figure 13.20 Identifying positive a
Page 240 and 241: OF MAPS AND MATRICES 225 undercurre
Page 242 and 243: 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
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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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