A Framework For Discussing LLMs as Tools for Qualitative Analysis

TL;DR

This paper proposes a framework for integrating Large Language Models into qualitative research, emphasizing their role in proposing or refuting models and supporting human review, fostering cross-paradigm collaboration.

Contribution

It introduces a novel framework for using LLMs in qualitative analysis, highlighting their potential to surface counter-examples and facilitate interdisciplinary collaboration.

Findings

LLMs can propose or refute qualitative models effectively.

Using LLMs to surface counter-examples aids human review.

Framework supports cross-paradigm research collaboration.

Abstract

We review discourses about the philosophy of science in qualitative research and evidence from cognitive linguistics in order to ground a framework for discussing the use of Large Language Models (LLMs) to support the qualitative analysis process. This framework involves asking two key questions: "is the LLM proposing or refuting a qualitative model?" and "is the human researcher checking the LLM's decision-making directly?". We then discuss an implication of this framework: that using LLMs to surface counter-examples for human review represents a promising space for the adoption of LLMs into the qualitative research process. This space is promising because it is a site of overlap between researchers working from a variety of philosophical assumptions, enabling productive cross-paradigm collaboration on tools and practices.