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Thinking about the Coding Process in Qualitative Data Analysis
Open accessAbstract
Coding is a ubiquitous part of the qualitative research process, but it is often under-considered in research methods training and literature. This article explores a number of questions about the coding process which are often raised by beginning researchers, in the light of the recommendations of methods textbooks and the factors which contribute to an answer to these questions. I argue for a conceptualisation of coding as a decision-making process, in which decisions about aspects of coding such as density, frequency, size of data pieces to be coded, are all made by individual researchers in line with their methodological background, their research design and research questions, and the practicalities of their study. This has implications for the way that coding is carried out by researchers at all stages of their careers, as it requires that coding decisions should be made in the context of an individual study, not once and for all.
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Metadata
- Authors
- Elliott, V.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- Elliott, Victoria
- ORCID
- Elliott, Victoria
- Venue
- The Qualitative Report
- Publisher
- Nova Southeastern University
- Published
- 2018-11-24
- ISSN
- 1052-0147 (ISSN-L)
- 2160-3715
- OpenAlex
- W2902680660
- Cited by
- 746
- References
- 34
- Citations by year
- 2026: 47 · 2025: 110 · 2024: 110 · 2023: 136 · 2022: 113 · 2021: 126 · 2020: 82 · 2019: 21 · 2018: 1
- FWCI
- 186.36
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc-sa
- Locations
- The Qualitative Report (publishedVersion, cc-by-nc-sa)
- NSUWorks (Nova Southeastern University) (submittedVersion, cc-by-nc-sa)
- Topics
- Social Sciences › Education › Qualitative Research Methods and Applications
- Social Sciences › Sociology and Political Science › Qualitative Research Methods and Ethics
- Social Sciences › Sociology and Political Science › Data Analysis and Archiving
- Keywords
- qualitative data analysis, coding process, research design, research questions, research training
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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