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S522 Lecture 4 February 17, Grounded theory. “Thick description” Geertz 1973.

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Presentation on theme: "S522 Lecture 4 February 17, Grounded theory. “Thick description” Geertz 1973."— Presentation transcript:

1 S522 Lecture 4 February 17, Grounded theory

2 “Thick description” Geertz 1973

3 Charmaz “Grounded theory coding requires us to stop and ask analytic questions of the data we have gathered. These questions not only further our understanding of studied life but also help us direct subsequent data- gathering towards the analytic issues we are defining”

4 “ Grounded theory coding consists of at least two phases; initial and focused coding. During initial coding we study fragments of data - words, lines, segments and incidents - closely for their analytic import.,,, While engaged in focused coding, we select what seems to be the most useful initial codes and test them against extensive data”

5 2 questions: What is the person (or source) that is reporting DOING IN the account? What is the person DOING WITH the account? What are they communicating?

6 Gerunds, eg Doing Asking Feeling Disagreeing Suffering Judging Justifying

7 Objectivist versus constructivist

8 “Data are narrative constructions. They are reconstructions of experience; they are not the original experience itself. Whether our respondents ply us with data in interview accounts they recast for our consumption, or we record ethnographic stories to reflect experience as best we can recall and narrate, data remain reconstructions” Charmaz 2010 p 196

9 “ [E]arly grounded theory texts imply that categories and concepts inhere within the data, awaiting the researcher’s discovery….. Instead, a constructivist approach recognizes that the categories, concepts, and theoretical level of an analysis emerge from the researcher’s interactions within the field and questions about the data” Charmaz, 2010, p 206 [italics added]

10 Grounded theory is about theory development not theory testing

11 Breaking the data up into their component parts or properties Defining the ACTIONS on which they rest Looking for tacit assumptions Explicating implicit actions and meanings Crystallizing the significance of the points Comparing data with data Identifying gaps in the data

12 Memo-writing “Memos chart, record and detail…. We start by writing about our codes and data and move upward to theoretical categories and keep writing memos throughout the research process. Memo-writing prompts you to analyze your data and codes early in the research process”

13 Charmaz: grounded theory Initial coding Focused coding Axial coding Theoretical sampling

14 Coding: Stick closely to the data Show actions Indicate how dilemmas arise - eg around disclosure Coding defines WHAT IS HAPPENING in the data - the ELEMENTS of emergent theory

15 Remain open to all possible theoretical directions indicated by the reading of the data Try to understand participants’ standpoints and situations as well as their actions within the setting Coding impels us to make our participants’ language problematic to render an analysis of it The use of gerunds maintains a focus on action (eg perceiving, feeling)

16 In vivo Codes General terms that flag condensed meaning Participants’ innovative term that captures meaning Insider shorthand terms specific to a particular group

17 Second phase of coding: Collecting data together into one category Finding new ways of thinking about the data

18 Axial coding: Overall organization of categories Helps provide framing process and the ordering of categories

19 Theoretical sampling: What is it and what it is NOT

20 Problems which may arise while coding Coding at too general a level Identifying topics instead of actions and processes Overlooking how people construct actions and processes Attending to disciplinary or personal concerns rather than participants’ concerns Coding out of context Using codes to summarize but not to analyze

21 Questions to ask oneself: How does my coding reflect the incident or described experience? Do my analytic constructions begin from this point? Have I created clear, evident connections between the data and my codes? Have I guarded against rewriting, and therefore recasting, the experience in academic language rather than the language of the participants?


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