Breaking Binaries Research Session on Coding and Analysis

This is the slide set for the Breaking Binaries Research Summer Session on Qualitative Coding and analysis delivered by Professor Katrina Pritchard and Dr Helen Williams

1. Summer Sessions Qualitative Research Support

2. About us Advanced Qualitative Methods Leadership Teaching UG, PGT & MBA Gendered expectations as & at work Podcast: Prefer not to say… Inequalities In Entrepreneurship Negotiating Difference At Work Based at Swansea University Exploring complex identities at work Research funding from Swansea University CIPD ISBE

3. The Coding and Analysis Process 2. What is coding ? What is a ‘code’? Introduction to coding techniques Coding exercise 1 Coding exercise 2 3. What is Analysis Overview of different analytic approaches Analytic Exercise (Reflexive Thematic Analysis) Importance of piloting and trying different approaches out What To Expect

4. Break-out discussion: Individually, note down three – five (or more) challenges you have with coding and analysis? As a group, discuss your common challenges and be prepared to share these with the room. The Coding and Analytic Process

5. Part 1: The Coding and Analytic Process

6. The Coding and Analysis Process Transcripts Contribution Data management, GDPR, security

7. Before you even begin the analytic stages of your research, a lot of ‘work’ needs to take place. Your analysis is only as good as the data you collect! There are many different forms of ‘data’! We tend to rely on textual data (but there are many other forms) Thinking About Your Data

8. This Photo by Unknown Author is licensed under CC BY-SA-NC A Useful Baking Analogy Much like baking a cake, a finished qualitative analysis is a combination of lots of different ingredients (data), skills and processes. The cake is not existent prior to it being baked! The cake will be different depending on how you choose to bake it. Braun & Clarke (2016 )

9. Quick Overview: Ordering Data Induction, deduction, and abduction are forms of (logical- ish ) reasoning that are used in every type of research (qualitative and quantitative alike) These forms of thinking are not concepts, nor are they methods or tools of data analysis, but means of connecting and generating ideas. T hey represent the intellectual building blocks of research. This Photo by Unknown Author is licensed under CC BY-NC

10. Part 2. Coding Data

11. Is it a Code or a Theme? Codes An analytic ‘unit’ Captures narrow observations or labels specific entities in your data (people, places, objects etc.) One-dimensional (mostly!) Thin on meaning Themes An analytic ‘basket’ Capture multiple aspects and facets Capture multiple “meanings” in your data (formed from codes) Help to organise aspects of data in ways to link to your research questions

12. Why Code? This Photo by Unknown Author is licensed under CC BY

13. Coding involves systematically reviewing data and searching for aspects that appear interesting, relevant, provoking – in relation to the (research) question – and then writing brief descriptions (codes) next to them. Coding provides a foundation for  insight because – when done well - it requires purposeful, critical engagement with the data.  C oding is a systematic interrogation of the data, identifying “meaning” and patterns across the dataset (this is often seen a means of achieving rigour). We must always recognise the role and subjectivity of the analyst! What is Coding?

14. Key question: Does this person take the time to get to know and understand others in order to build relationships with a broad range of people? Deductive Coding

15. What is coding inductively?

16. In (truly) inductive research often your coding is done around a central organising concept Often this is framed by your research question You are not coding to a predefined set of agreed patterns or indicators (often called a ‘codebook”). Inductive Coding

17. Frequency Repetition Juxtapositions/tensions/linguistic anomalies Use of metaphor(s) Sequences Absences Essentially you are looking at: 1) What is the individual talking about? 2) How is the individual talking about it? 3) Why is the individual talking about it in that way? Starting Off: What to look for?

18. Take look at Transcript 1. Now code the data with the following research question in mind: How do managers experiences loss at work? Coding Exercise

19. Part 3: Data Analysis

20. The Role of Research Positionality ©  2023 Breaking Binaries Research. All rights reserved. Realism Relativism Objectivism Subjectivism Pragmatism Critical Realism Interpretivism Constructivism Ontology Epistemology Qualitative Quantitative Phenomenology

21. Discourse/Discursive Approaches Narrative Approaches Reflexive Thematic Approaches Content Approaches* (often routed in positivist assumptions) Thematic Approaches Grounded Approaches (supposedly abductive) Phenomenological Approaches Types of Analysis

22. Stage Process 1 Familiarisation  2 Coding 3 Develop initial themes 4 Further develop and refine themes 5 Refine, define, label (name) themes 6 Writing up your work (tell the story of your participants) Reflexive Thematic Analysis (Braun & Clarke, 2021)

23. IPA’s Six-stage Analytic Process IPA’s six-stage analytic process (Eatough & Smith, 2017; Smith et al., 2022) Stage Process   1   Read and re-read transcripts to get to know the data 2 Make initial notes to systematically capture observations 3 Develop initial themes for each case 4 Search for connections across initial themes within the case 5 Move to next case 6 Identify connections and patterns across all cases (once above steps completed for each case)

24. ‘Doing’ Analysis (RTA)

25. Using free macros to support coding DOWNLOAD THE MACRO: Babbage, D. R., & Terry, G. (2023, April 19). Thematic analysis coding management macro. https://doi.org/10.17605/OSF.IO/ZA7B6 (ALWAYS CITE THIS IN YOUR WORK) WATCH OUR VIDEO WITH A STEP BY STEP GUIDE: https://wordpress.com/page/breakingbinariesresearch.wordpress.com/480 USE TRACK CHANGES COMMENTS IN WORD TO CODE AND ADD NOTES TO YOUR DATA RUN THE MACRO TO CREATE AN EXCEL SPREADSHEET OF YOUR CODES AND NOTES

26. Data triangulation? Member checking? Multiple coders may, however, be beneficial in a reflexive manner (e.g., to sense-check ideas, or to explore multiple assumptions or interpretations of the data). If analysis does involve more than one researcher, the approach should be collaborative and reflexive, aiming to achieve richer interpretations of meaning, rather than attempting to achieve consensus of meaning. Validity, Rigour , and Reliability?

27. Too many themes (which are focused on single units of meaning – i.e., codes being used as themes) Thin descriptions (often only capturing high-level semantic and/or literal meanings) One word themes Beware Analytic Foreclosure (Connelly & Peltzer , 2016)

28. @ProfKPritchard @HelenCWilliams @BreakBinaries [email protected] [email protected]