As you work through your data, often the exact meaning of a code or theme often evolves, as different people have different perspectives on the same thing. After all, I know what I mean, right? However, there is often a need for self-communication – a note to your self that acts as an aide-mémoire to how a code should be used, through a dynamic process that might take months. It may feel that creating a formal codebook isn’t necessary when there is just one person doing the analysis, as there isn’t an immediate need to communicate what the codes are with someone else. However, it’s just as helpful for grounded theory or emergent analysis, although here it will be constantly updated with new codes and themes as they are identified in the data. Often the concept of codebooks is connected to framework analysis, or analytical techniques where most of the codes are decided in advance. In qualitative coding, the codebook has a similar function: collecting useful meta-information about the codes that is more than the code name itself. The term codebook actually comes from quantitative statistics, where a codebook is used to keep metadata such as variable names, valid ranges, data types etc. A codebook doesn’t include the extracts of data themselves, but a detailed description of the codes, how they should be used, their relationship to each other, what should be included and excluded in each code. Often, the researcher will use hundreds of codes to do this, and the list of codes, themes or topics that are used to analyse the data is called the coding framework, and a codebook describes them. Many people undertaking qualitative analysis will use some form of coding to help explore and categorise their data.
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