Once the interviews were completed, we wrote instructions to guide the qualitative causal coding of the transcripts, in a radical zero-shot style: without giving a codebook or any examples. The assistant was told not to give a summary or overview but to list each and every causal link or chain of causal links and to ignore hypothetical connections (for example, “if we had X we would get Z”). We told the AI to produce codes or labels following this template: 'general concept; specific concept'. We gave no examples, but expected the AI to produce labels like: “economic stress; no money to pay bills”. We call the combination of both parts a (factor) label.

The assistant was told also to provide a corresponding verbatim quote for each causal chain, to ensure that every claim could be verified. Codings without a quote which matched the original text were subsequently rejected, thus reducing the potential for “hallucination”.