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Data Analysis: A Grounded Theory Approach

INFO 272. Qualitative Research Methods. Data Analysis: A Grounded Theory Approach. The Iterative Model. 1) research topic/questions. 2) ‘corpus construction’. 3) data gathering. Field work. 4) analysis. 4) more analysis. Desk work. 5) write-up. From Analysis to Write up.

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Data Analysis: A Grounded Theory Approach

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  1. INFO 272. Qualitative Research Methods Data Analysis: A Grounded Theory Approach

  2. The Iterative Model 1) research topic/questions 2) ‘corpus construction’ 3) data gathering Field work 4) analysis 4) more analysis Desk work 5) write-up

  3. From Analysis to Write up 5) draft writing 4) memo-writing Granularity 3) theoretical coding 2) focused coding 1) Initial coding

  4. Grounded Theory • Constructing analytic codes and categories from data • Simultaneous involvement in data collection and analysis (or very rapid iteration) • ‘Sampling’ aimed toward theory construction • Lit review after analysis

  5. Coding… • …is attaching labels to segments of data that depict what each segment is about • …is the bones of your analysis • …forces you to interact with your data (again and again)

  6. Coding: Key concepts • Granularity varies • Word-by-word, line-by-line, incident-to-incident • observational data vs. interviews • Ideas, categories, concepts must ‘earn their way’ into your analysis • ‘in vivo’ codes (close attention to language) • Constant comparative method • Are provisional! (code quickly)

  7. Warning! • Be careful with the language of intention, motivation, strategy • Don’t impute • Treat social reality as what is apparent, presented to you (not underlying, secret motives)

  8. What does coding do to data? • Condenses • Disaggregates

  9. Remain open • Stay close to the data • Keep codes simple and precise • Construct short codes • Preserve actions [gerunds – i.e. shifting, interpreting, avoiding, predicting] • Compare data with data • Move quickly through the data 1) Initial coding

  10. Take most frequent and analytically interesting codes from the initial coding • Tying emerging concepts to the data (verification process) 2) focused coding 1) Initial coding

  11. Timesavers and Shortcuts • Moving along quickly to ‘focused coding’ • Do ‘initial’ coding on a selection of the data (the early data, the most rich material) • Software (for searching especially) – NVivo or even MS OneNote

  12. After Coding: Some Heuristics • Sorting and Diagramming • Concept charting • Flow diagrams • Lofland and Lofland and Charmaz have many suggestions

  13. Memo-Writing • Transitioning between codes and write up • Could be blog entries

  14. An Example

  15. Henry:If your original idea was – if the target group was women, the poor women, why weren’t these phones strictly earmarked for them? Jenna:I don’t know cause there was someone I talked to who was talking about how great it was that 80% of village phone operators are women… Henry: The operators were women but they were not the owners. Henry:Here in Uganda the owners most of the owners were men actually 90% of the phones were owned by men… Jenna:So they were making themselves small amounts, but big profits were going to the owners?...[women] were not the entrepreneurs? Julius:And even men, men who bought them, women who had them as closest to being owners it’s their husbands who facilitated them.

  16. Diagramming Phone Gifting and Sharing

  17. A Coding Exercise

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