🌻 Inductive coding with AI.
Chapter Contents.
Causal coding is fascinating but can take a lot of time. Using AI to help you is pretty easy, especially if you provide a codebook of factor labels which the AI has to use: Intro -- deductive auto-coding.
But what happens if you do not provide a codebook? You will end up with thousands of different labels which probably overlap a lot in meaning. This chapter explains how to handle that.
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Transforms Filters – Soft Recode with Magnetic Labels
You have already coded your dataset, manually or using AI, and now you want to relabel.
Using genAI to generate labels for clusters for use as magnets
If we are going to use some set of labels as magnets, we face a tension:
- on the one hand want them to express the generality we intend: the label should express the fact that this is a group, like 'health behaviours'; we are expressing the fact that we do NOT expect the raw labels to express this generality but to express specific examples.
- but this will make them perform worse as actual magnets because the best magnets should remain in single-case formulations and not try to generalise.