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Using CAQDAS in lexical searching and narrative analyses Graham R Gibbs University of Huddersfield.

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Presentation on theme: "Using CAQDAS in lexical searching and narrative analyses Graham R Gibbs University of Huddersfield."— Presentation transcript:

1 Using CAQDAS in lexical searching and narrative analyses Graham R Gibbs University of Huddersfield

2 Research Methods Festival U. Oxford, 1 st – 3 rd July 2004 Qualitative data analysis Concerned with the careful organisation and management of research Concerned with interpretation The organisation and management of research is an important aspect of analysis that contributes to the quality of analytic work.

3 Research Methods Festival U. Oxford, 1 st – 3 rd July 2004 Qualitative data analysis 2 Interpretation is the preserve of the human analyst But, other aspects of analysis can be enhanced by the use of CAQDAS. Especially if used as a heuristic device

4 Research Methods Festival U. Oxford, 1 st – 3 rd July 2004 Text search facility in CAQDAS Use as a way of building up coded text (= a way of preserving the results of diverse searches in one place) To get to know your data To find particular language use, such as metaphors, accounts and narrative moves. To look for negative cases.

5 Research Methods Festival U. Oxford, 1 st – 3 rd July 2004 Example Text Search Search for discussions about using informal networks to get jobs. Search for words like friend, mate, relative. Will get some finds that are relevant. Some based on spurious finds (e.g. relatively) Some that use the words but are not about informal networks.

6 Research Methods Festival U. Oxford, 1 st – 3 rd July 2004 Atlas.ti and MAXqda words found are displayed in context. just code the relevant ones only to a new code. NVivo and N6, finds are automatically coded to a new node. To see in context, either, Expand text viewed when browsing the finds, or Spread found text to e.g. 50 character either side of the word/phrase found or, In NVivo, use the Coder to highlight the found text (shown nodes coding this document) and/or show coding stripes. Uncode any that aren't relevant as search will already have coded all the finds.

7 Research Methods Festival U. Oxford, 1 st – 3 rd July 2004 Build up the codes iteratively You may not find all the relevant terms and passages at once. Repeat the searches with other related terms and add further finds to the coded text. Merge the results of new searches with relevant previous codes created from searches

8 Research Methods Festival U. Oxford, 1 st – 3 rd July 2004 Build a glossary of additional terms Read passages found by searching & look for other terms used to search for. E.g. terms about fatalism about looking for work. Reading turned up the following terms "give up, pointless, in the trap, trapped, plodding on, cant handle any more, desperation, just luck, way it goes on the day" Use a thesaurus (e.g. in Word) to find synonyms (or antonyms). Keep this in a memo and use cut and paste.

9 Research Methods Festival U. Oxford, 1 st – 3 rd July 2004 Build a glossary of additional terms 2 Use a concordance program to generate a list of words used. Inspect this for 1. unusual words or, 2. missing words or, 3. unusually infrequent words. Use either a separate program like WordSmith, Concordance and Conc or MAXdictio – add-on module for MAXqda.

10 Research Methods Festival U. Oxford, 1 st – 3 rd July 2004 Look for thematic content & narrative moves. Imagery, metaphor etc. Need to read some text to start identifying these words. But once found, search for others. The appeal to certain aspect of identity, by using terms like speaking as a fireman…, in my experience as a grandmother… or what all us cyclists agree on is…. Search for the terms, speaking as, in my experience as and all… agree on and other similar ones to find these narrative moves.

11 Research Methods Festival U. Oxford, 1 st – 3 rd July 2004 Thematic content Sub-stories, introductions to sub-stories, e.g. change of tense, or use of terms like, "That reminds me when…" or "It was like when…" Use of emotive language, talk about emotions and feelings. E.g. Weaver and Atkinson (1994) suggest the following root terms to search for related to the idea of conflict…

12 Research Methods Festival U. Oxford, 1 st – 3 rd July 2004 Conflict terms Accus* Ang* Antag* Argu* Battl* Bawl* Bitch* Blab* Blam* Competit* Contempt* Critic* Curs* Cruel* Disagree* Defen* Fight* Hostil* Insult* Object* Mad* Punish* Refus* Rile* Shout* Stir* Troubl* Upset* Uncooperat* Unfair* Unpardonabl* Unreasonabl* Violen* Wrong*

13 Research Methods Festival U. Oxford, 1 st – 3 rd July 2004 Coding lite Coding is used here not to support thematic analysis, followed by hypothesis testing or pattern analysis (e.g. is text coded about X also coded about Y) BUT As a support for the reading of a text and as a way to compare readings (between or within cases). It is less important that all text about Z is coded as Z Purpose is to support narrative interpretation of the text.

14 Research Methods Festival U. Oxford, 1 st – 3 rd July 2004 Little call for searching or retrievals This cuts up the text and decontextualises (and relies on comprehensive coding). Rather, Use coding of passages when reading the text, to give a background to interpretation. Use coding of single passages. "Once only" codes. Just to highlight e.g. a phase in narrative (e.g. turning point, event, episode) In NVivo use such once only codes to order events/episodes chronologically

15 Research Methods Festival U. Oxford, 1 st – 3 rd July 2004 Contribution to the quality of analysis. Activities supported by CAQDAS contribute to the reliability and validity of narrative analyses. Searching complements reading. Humans get tired etc. and may miss things. Computer searching never tires. Search for negative cases and aberrant cases ensures that analysis is as comprehensive as possible and that such cases are explained. Encourages consideration of whole data set. Avoids analysis based on subset of data. Computers are not captured by the exotic or unusual.

16 Using CAQDAS in lexical searching and narrative analyses Graham R Gibbs University of Huddersfield


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