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- 1. What is data analysis?
- 2. A grounded theory approach to data analysis
- 3. Processing your data in preparation for analysis
- 4. Coding interview transcripts and other data
- 5. Analysis in a collaborative context
- 6. Critically evaluating your data: reflexive data analysis
- 7. Summary
- 8. Feedback Survey
4. Coding interview transcripts and other data
Coding is a form of data analysis that involves labelling and organizing data to reduce your data to a manageable size. Coding allows you to conceptually organize your data but it does not provide an explanatory framework to interpret or draw conclusions from your data.
Coding can be used in an exploratory, inductive way such as in grounded theory (in which you generate theories from empirical data), or it can be used to support a theory in a more deductive manner.
How to code data:
- Code your interview by extracting
- Give labels to items that seems to share a similar theme and that you think may be of theoretical
- The coding should flow from the questions but should also reflect what is said which may drift away from the focus you
- Develop master categories that relate to the data (some data may fall on more than one category). Then you can have sub- master categories . For example, ‘class’ can be divided into working and middle
- Emic codes / in vivo codes are codes those used by your
- Etic codes/ analytic codes are those assigned by the researcher and tend to be more theoretically
- When you think you have finished coding you can develop a codebook – a list of all the codes. It can include descriptive codes and analytic
- You may have more than 100 codes so you then start to cluster codes into For example, common issues faced by interviewees, characteristics of interviewees, identities, memories, representations, places, etcetera. You may end up discarding some codes.
- Go through your data again once you have a code book and recode the
Data can be transcribed, annotated and coded manually. Manual coding allows you to become very familiar with your data. There are also computer software programs available for managing and processing data, which can be particularly useful for managing large volumes of data and connecting datasets in different formats.
Reference
Peake, L. 2018. Presentation at the ‘Workshop in Urban Feminist Research: Ethnographic Research Tools’, Ramallah, Palestine, July 2018.