Qualitative_data_analysis

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Transposition: Doctor: ‘I’m afraid I can’t diagnose your complaint. I think it must be drink.’ Patient: ‘All right then, I’ll come back when you are sober.’ Pun play: A man was worried about his sex life. ‘How often should I have sex, doctor?’ he asked. ‘Infrequently,’ said the doctor. ‘Is that one word or two?’ asked the man. The references to health and sex in the above examples raise another theme. Catharsis—which we can think of as humour giving an outlet to repressed emotions —is another often-cited aspect of humour. Laughter giving emotional release can act as a social as well as a psychological safety valve. Topics which tend to be anxiety laden or taboo—sex, race, work, health, death—provide excellent sources of comic material. The more sensitive or sacrosanct the subject, the greater the effect. This is the province of the ‘sick’ joke, which may gratify even as it appalls us. But cathartic humour can also have a more positive aspect. ‘Is sex dirty? Only when it’s done right’ (Woody Allen) FINDING A FOCUS 73 ‘Don’t knock masturbation—it’s sex with someone I love’ (Woody Allen) Criticism is another ingredient we can readily recognize in humour. This aspect is emphasized in Merrill’s discussion of women’s comedy. Humour can deflate, or denigrate. It can puncture pretensions. In the form of subversive satire, it can mock the vanity and ridicule the vice of the powerful. Lives have been lost because of witticisms ‘out of season’. But humour can also function as a means of oppression, of maintaining the status quo. Merrill (1988:270) cites a study by Rose Laub Coser of jokes in a psychiatric institution, which found a hierarchy of humour: those with power could publicly enjoy a joke at the expense of those without—but not vice versa. Nor is it always the powerful who seek to confirm the position of the powerless. Telling jokes against oneself can be a form of social defence, through which one denies any threat of disruption to established order. Merrill (1988:273) goes on to discuss comediennes whose humour is based on self deprecation, ridiculing and demeaning themselves and other women. Who are the targets or victims of criticism? Andrew Brown (1991) reports that the wave of humour currently (i.e. in 1991) sweeping southern England has as its target the ‘Essex Girl’ (and ‘Essex Man’), apparently representative of a newly emergent stratum of the working class with high household incomes.
74 QUALITATIVE DATA ANALYSIS • How can you tell the difference between Essex Girl and a supermarket trolley (the supermarket trolley has a mind of its own). • How does an Essex Girl turn on the light afterwards? She kicks open the car door. • What did the Essex Girl ask when told she was pregnant? ‘How do you know it’s mine?’ This humour has a savage streak, and Brown comments that these are jokes which ‘no one would dare to tell’ against traditional targets of humour. As social mores change, so do social scapegoats. A recent example was an intended joke made by a panellist on a satirical TV programme when asked to explain the difference between four people, one of whom was black. The comment ‘Well, one of them is coloured’ was greeted with a stony silence on all sides, and the panellist had to be rescued from his embarrassing predicament. Colour is no longer a ‘funny’ issue. Despite its penchant for disrupting expectations, humour may function to confirm rather than undermine stereotypes. Women as a butt of humour often involves confirmation of male conceits: the female as sexually avaricious, the wife as a pain in the neck. The Essex girl is stereotyped as brainless, promiscuous, and incredibly stupid. The doctor is typecast as a drunk. Men with white socks are stereotyped as unreliable, untrustworthy and prone to vaseline jokes. Humour trades in such stereotypes, affirming rather than subverting existing values. Finally, we can ask how humour treats its victims. Are we invited to laugh at them, or laugh with them? Is there, as Merrill suggests, a ‘distance between empathy and judgement’, such that criticism is softened by empathy? Or are the victims subjected to unmitigated ridicule? Is comedy self-critical without being selfdeprecating? Is humour critical without being cruel? Main themes in <strong>analysis</strong> of humour • Disrupting expectations: incongruity • Releasing emotions: catharsis • Affirming or subverting values • Laughing with or at victims • Trading in stereotypes We have identified a number of themes which can form the main threads of our <strong>analysis</strong> (Figure 5.2). Now we can consider how these can be woven together. For example, we could distinguish between style and substance in humour, drawing a contrast between
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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;
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
Page 60 and 61: WHAT IS QUALITATIVE ANALYSIS? 45 vi
Page 62 and 63: WHAT IS QUALITATIVE ANALYSIS? 47 Fi
Page 64 and 65: Figure 3.6 Formal and substantive c
Page 66 and 67: WHAT IS QUALITATIVE ANALYSIS? 51 ne
Page 68 and 69: WHAT IS QUALITATIVE ANALYSIS? 53 If
Page 70 and 71: Figure 3.10 Qualitative analysis as
Page 72 and 73: Chapter 4 Introducing computers ‘
Page 74 and 75: ecording of an index of information
Page 76 and 77: Figure 4.1 A link between text held
Page 78 and 79: Computer transformations • Search
Page 80 and 81: Chapter 5 Finding a focus A Zen sto
Page 82 and 83: FINDING A FOCUS 67 Sheila The solic
Page 84 and 85: FINDING A FOCUS 69 to reflect upon
Page 86 and 87: For example, here are some question
Page 90 and 91: Figure 5.2 Main themes for analysin
Page 92 and 93: Chapter 6 Managing data Piles of pa
Page 94 and 95: MANAGING DATA 79 setting, by source
Page 96 and 97: MANAGING DATA 81 Interviewer Maybe
Page 98 and 99: Figure 6.1 Case documents kept in a
Page 100 and 101: MANAGING DATA 85 ‘Show the full r
Page 102 and 103: Chapter 7 Reading and annotating Ac
Page 104 and 105: • Official/bureaucratic commitmen
Page 106 and 107: READING AND ANNOTATING 91 women wer
Page 108 and 109: Techniques for interactive reading
Page 110 and 111: we can write our comment on a separ
Page 112 and 113: Figure 7.1 Relating data to key the
Page 114 and 115: 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
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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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