Thematic Analysis - An Introduction

https://youtu.be/5zFcC10vOVY - Victoria Clarke

Notes:

• Familiarise yourself with the data. Read and re-read. Do not advance immediately to theme generation.
• It's not about being an expert data analyst, or an inexperienced data analyst.
• It's a process of time and reflection that has to unfold
• Reflexive TA thinks of codes as things - analytic entities. Coding produces little things and then themes are generated from those clustered codes.
• A code is a label that captures something interesting in the data. Avoid one word and really get into data. Code labels need to work independently from the data - they need to evoke data and be clear, when the data is not present.
• Go through systematically and go through each data item individually. Then view subsequent data items through the lens of the first.
• Codes can get bigger and then break up into different codes
• It's a flexible and organic process and therefore a couple of coding sweeps are recommended.
• The main distinction around codes is the idea of codes are either semantic or latent. Semantic codes are capture obvious or surface meanings. Latent codes capture ideas that are underlying. It tries to capture implicit meaning. Some codes capture both.
• Semantic codes - participant communicates meaning conveyed directly and intentionally to the interviewer. Latent codes unfold and capture assumptions, underpinning the surface meanings As critical scholars we consider the social context we live in.
• The data analyst (critical researcher) becomes a cultural commentator, reflecting on the cultural landscape that the interviewer and the participants reside within. Starting to think about the social values, norms and assumptions that allow what people are saying to make sense.
• End this phase with a list of codes and all the data relevant to each code collated