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Machine-Assisted Topic Analysis of Large-Scale Health Experience Data: Identifying Sociodemographic Differences and Evaluating Bias in Large Language Models

2026-05-22

Abstract excerpt

<h4>Introduction</h4> Large-scale free-text data with socio-demographic information can capture nuanced accounts of lived experience that are difficult to detect in structured measures. However, manual qualitative analysis is difficult to scale, while automated approaches may obscure subgroup variation or introduce bias. This is especially relevant for large language models (LLMs), whose use in qualitative health...

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Literature Corpus work
bf9b57a3-9cf2-5e20-8f08-14aacabd5fa1
DOI
10.64898/2026.05.20.26353755
Open publication

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