Qualitative_data_analysis

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If we want to make this change, it is not enough to change the place of categories on the map. We must also change the name of the categories assigned to the data. The category ‘occupation’ must now be assigned to all the databits, including those previously assigned only to the category ‘task’. The category ‘other than task’ must be assigned to all the databits which were previously assigned to ‘occupation’. Fortunately the computer can facilitate this task by automatically finding the relevant databits and renaming the categories assigned to them. This should be as easy to accomplish as our initial categorization, or we may be encouraged by technical constraints to be less flexible than we should be in the subsequent development of our analysis. In other words, it should be as easy to correct our mistakes as it was to make them in the first place! Although we have clarified our distinction conceptually, we may still doubt its empirical value. Does it distinguish usefully between our databits? To compare the categories, we must look at the databits which we have assigned to each category (Illustration 10.6). Here we may receive some reassurance from the fairly even distribution of the data between the two categories. This suggests that differing conceptions of task are more central to the analysis than the various other occupation characteristics which we have rather crudely lumped together under the ‘other than task’ category. At this point, we may decide that it would be worthwhile discriminating more effectively amongst these databits, perhaps dividing occupational characteristics into such aspects as recruitment, remuneration, retirement etc. where expectations clearly differ as between dentists and artists! On the other hand, the empirical power of our category ‘task’ may encourage us to focus on this data instead and set aside (at least for the moment, and possibly for good) any further differentiation amongst other occupational characteristics. At any rate, we may want to retain the category and not collapse it into a less differentiated category such as occupation. ILLUSTRATION 10.6 COMPARING DATABITS BETWEEN CATEGORIES Other than task Task 1. I can’t work to order like a common tradesman. 2. (Cézanne) is old and infirm and unable to hold the instruments and they must be tied to his wrists. SPLITTING AND SPLICING 151 1. I made her bridge as I felt it and not to fit her ridiculous mouth! 2. I decided her bridge should be enormous and billowing, with wild, explosive teeth flaring up in every direction like fire!
152 QUALITATIVE DATA ANALYSIS Other than task Task 3. Once again I am in need of funds I know what a burden I must be to you. but who can I turn to? I need money for materials! 4. I have not even a penny left for Novocaine! 5. (Gauguin) is a fine dentist who specializes in bridgework 6. (Gauguin) was very complimentary about my work on Mr Jay Greenglass 7. Greenglass was adamant and we went to court. There was a legal question of ownership, and on my lawyer’s advice, I cleverly sued for the whole tooth and settled for the filling. 8. Well, someone saw it lying in the corner of my office and he wants to put it in a show! They are already talking about a retrospective! 9. (Toulouse-Lautrec) longs more than anything to be a great dentist, and he has real talent 10. (Toulouse-Lautrec is) too short to reach his patients’ mouths and too proud to stand on anything. 3. I find it beautiful She claims she can’t chew! What do I care whether she can chew or not! 4. I took some dental X-rays this week that I thought were good. Degas saw them and was critical. He said the composition was bad. All the cavities were bunched in the lower left corner. 5. I explained to him that’s how Mrs Slotkin’s mouth looks, but he wouldn’t listen! He said he hated the frames and mahogony was too heavy. 6. I completed her mouth out of obligation but I couldn’t bring myself to sign it. 7. I am working almost exclusively with dental floss now, improvising as I go along, and the results are exciting! 8. I filled his lower seven, then despised the filling and tried to remove it. 9. my old friend Monet refuses to work on anything but very very large mouths 10. Seurat, who is quite moody, has developed a method of cleaning one tooth at a time until he builds up what he calls ‘a full fresh mouth.’ It has an architectural solidity to it, but is it dental work? So far we have considered in the light of our retrievals whether and how to divide these categories. Now we may want to consider what kind of relationship holds between them. We can look at all the databits which we have assigned, not just to one or the other, but to both categories. We can do this by inspecting the databits assigned to each category to see whether there are any duplicates. With substantial amounts of data, this process would be very time-consuming and we may use the
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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
Page 116 and 117: CREATING CATEGORIES 101 types of ph
Page 118 and 119: CREATING CATEGORIES 103 conceptual
Page 120 and 121: CREATING CATEGORIES 105 Categorizat
Page 122 and 123: Table 8.1 Alternative category list
Page 124 and 125: This is only a starting point. Our
Page 126 and 127: CREATING CATEGORIES 111 undertaking
Page 128 and 129: Figure 8.2 Weighing up the degree o
Page 130 and 131: CREATING CATEGORIES 115 Although co
Page 132 and 133: CREATING CATEGORIES 117 for an adeq
Page 134 and 135: CREATING CATEGORIES 119 well as con
Page 136 and 137: Figure 9.2 Categorizing data—2 Fi
Page 138 and 139: are entitled to expect some consist
Page 140 and 141: ASSIGNING CATEGORIES 125 we ought t
Page 142 and 143: ASSIGNING CATEGORIES 127 the data.
Page 144 and 145: have annotated this data. Suppose w
Page 146 and 147: ASSIGNING CATEGORIES 131 suddenly t
Page 148 and 149: • What generally constitutes a
Page 150 and 151: Databits Categories 5. Now she is u
Page 152 and 153: Chapter 10 Splitting and splicing T
Page 154 and 155: Using Hypertext linking, whenever n
Page 156 and 157: SPLITTING AND SPLICING 141 databits
Page 158 and 159: Category Subcategories Suffering Di
Page 160 and 161: Figure 10.1 Levels of subclassifica
Page 162 and 163: ILLUSTRATION 10.5 SUBDIVIDING DATAB
Page 164 and 165: Figure 10.2 Initial relationships b
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
Page 210 and 211: This approach is very exploratory,
Page 212 and 213: MAKING CONNECTIONS 197 Table 12.10
Page 214 and 215: 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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