# Scalable Qualitative Coding with LLMs: Chain-of-Thought Reasoning Matches Human Performance in Some Hermeneutic Tasks. (arXiv:2401.15170v...


Qualitative coding, or content analysis, extracts meaning from text to discern
quantitative patterns across a corpus of texts. Recently, advances in the
interpretive abilities of large language models (LLMs) offer potential for
automating the coding process (applying category labels to texts), thereby
enabling human researchers to concentrate on more creative research aspects,
while delegating these interpretive tasks to AI. Our case study comprises a set
of socio-historical codes on dense, paragraph-long passages representative of a
humanistic study. We show that GPT-4 is capable of human-equivalent
interpretations, whereas GPT-3.5 is not. Compared to our human-derived gold
standard, GPT-4 delivers excellent intercoder

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