Scaling Hermeneutics: A Guide to Qualitative Coding with LLMs for Reflexive Content Analysis

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# Description

Qualitative coding—and the wider practice of content analysis—is a reflexive, interpretive craft that shapes research questions, deepens theoretical insight, and surfaces subtle social dynamics rather than simply labeling text.

As large language models grow more adept at nuanced language work, we present a hybrid workflow that preserves hermeneutic value while scaling code application across corpora too large for manual review. The process retains traditional codebook development while iteratively adapting definitions for machine comprehension before handing off categorization tasks to the model.

We demonstrate how to rewrite code descriptions for LLM interpretation, structure prompts, and elicit chain-of-thought explanations that improve fidelity. A socio-historical case study highlights how frontier models can reliably interpret paragraph-length passages, all while centering ethical considerations, researcher reflection, and continued human interpretive leadership.