The Qualitative Laboratory: Theory Prototyping and Hypothesis Generation with Large Language Models

the-qualitative-laboratory:-theory-prototyping-and-hypothesis-generation-with-large-language-models

The Qualitative Laboratory: Theory Prototyping and Hypothesis Generation with Large Language Models

[Submitted on 25 Nov 2025 (v1), last revised 12 Nov 2026 (this version, v2)]

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Abstract:The use of Large Language Models (LLMs) to simulate social actors has garnered attention for its implications for the epistemic status of discourses generated through such means. This paper considers the more modest question of whether sociological role-playing can serve as a heuristic instrument in the generation of qualitative hypotheses. We take as a case study the development of four divergent fictional characters using a theoretically informed Matrix of Climate Reception. These characters are asked to respond to a series of discourse frames covering two topics: a proposed ban on the sale of new gasoline-powered cars, and the inclusion of climate justice in the school curriculum. We then analyse the 32 model-generated responses for their commonalities, situational differences and divergences from the presuppositions underlying the characters’ profiles. The experiment illustrates how LLMs can be used to flesh out theoretical presuppositions into contextual narratives and to propose avenues of further inquiry. It also shows that role-playing can generate considerable similarity between characters and is sensitive to how prompts are constructed, warning against the confusion of discursive coherence with sociological data. Role-playing is argued to be just one of several possible ways to use LLMs for generating hypotheses, with the heuristic specificity of this procedure compared with other methods of direct LLM-based reasoning or with other techniques remaining an open issue. The qualitative laboratory is thus conceived of as a heuristic instrument for provoking reflection and refining questions, not for testing theories with artificial data.

Submission history

From: Hugues Draelants [view email]
[v1] Tue, 25 Nov 2025 08:31:48 UTC (555 KB)
[v2] Thu, 12 Nov 2026 18:19:34 UTC (420 KB)