Qualitative_data_analysis

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our reasons for making decisions and not simply putting them into effect without explanation. Justice must not only be done—it must be seen to be done. Assigning links • Look out for link words in the data • Only identify links pertinent to the analysis • Stay as close as possible to the data • Use caution in inferring links • Specify ‘rules’ governing link decisions The mechanics of linking data should be as straightforward as those of categorizing. Once each bit of data has been selected and a link chosen, the computer should be able to do the rest. It should be possible to link data prior to categorizing, while categorizing or after categorizing. What do we produce through linking databits? In practical terms, the computer can store for each databit any information about links we have made between it and other databits, and what those links are called. The particular format used does not matter, so long as the computer stores the relevant information in a practical way. This should allow us, on analysing our databits, to go directly from a databit to any other databit linked to it. When we come to analysing databits, therefore, we can display information not just about the categories to which they belong, or the context from which they are drawn, but also the other databits to which they relate. Earlier we looked at an example of the information which might be held by the computer for our first databit. We can now extend this to include information about the links with other databits (Illustration 11.2). It doesn’t matter how the databit is indexed—I have just taken the first three words of each databit as an index —so long as the computer can use the index to locate any linked databits. There should be no practical limit to how many links we can record for any particular databit. ILLUSTRATION 11.2 INFORMATION HELD ON LINKED DATABITS Index Mrs Sol Schwimmer Databit Mrs Sol Schwimmer is suing me Categories Transposing Occupation Case Letter01 LINKING DATA 173
174 QUALITATIVE DATA ANALYSIS DataRef1 Vincent DataRef2 Theo Date 1.4.91 Analyst Ian Dey Comment Is ‘occupation’ assigned correctly? Links Explains ‘Will life never’ Explained by ‘Because I made’; ‘Now she’s upset’; ‘I tried forcing’; ‘But it sticks’; ‘Still I find’ From an empirical point of view, we can weave a complex web of links between different bits of data. How does this help us conceptually? I shall consider this question in more detail in the next chapter. Meantime, let us conclude by noting two contributions which linking data can make to our analysis. One way linking can help our analysis is in the description of singularities. By recording each link in a chain of events, we can observe chronological or causal sequences, making it easy to extract from the data a series of events and the relationships between them. Linking thereby allows us to give a dynamic account of what has happened. Let us take another of Vincent’s letters as an example. Dear Theo I think it is a mistake to share offices with Gauguin. He is a disturbed man. He drinks Lavoris in large quantities. When I accused him, he flew into a rage and pulled my D.D.S. off the wall. In a calmer moment, I convinced him to try filling teeth outdoors and we worked in a meadow surrounded by greens and gold. He put caps on a Miss Angela Tonnato and I gave a temporary filling to Mr Louis Kaufman. There we were, working together in the open air! Rows of blinding white teeth in the sunlight! Then a wind came up and blew Mr Kaufman’s toupee into the bushes. He darted for it and knocked Gauguin’s instruments to the ground. Gauguin blamed me and tried to strike out but pushed Mr Kaufman by mistake, causing him to sit down on the high speed drill. Mr Kaufman rocketed past me on a fly, taking Miss Tonnato with him. The upshot, Theo, is that Rifkin, Rifkin, Rifkin and Meltzer have attached my earnings. Send whatever you can. Vincent. In Figure 11.11, this incident out-of-doors is presented through a number of links in a chain of events which again culminate in litigation. To elucidate this simple episode, I have used only two links, conditional and causal, but obviously more links might be required to identify relationships within a more complex sequence of
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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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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 166 and 167: If we want to make this change, it
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 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
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
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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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