Annotator Positionality as Signal: Psychometric Weighting for Anti-Autistic Ableism Detection

arXiv:2605.26397v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in decision-making tasks where they can amplify or suppress perspectives, raising concerns in high-stakes settings affecting autistic communities. While previous research has identified disability-related biases in LLMs, it remains unclear how they conceptualize ableism or detect it in text. We introduce a bias-aware evaluation framework targeting anti-autistic ableist language with a psychometrically-weighted, community-proximate ground truth anchored in annotator positionality. This framework c

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