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2 blueprints
Tests whether models can identify ableist language, explain why it's problematic, and suggest alternatives. Covers explicit ableist terms, outdated terminology, and contested metaphorical usage.
Note on complexity: Some terms are clearly rejected ("wheelchair-bound"), others are debated ("blind spot"). Tests whether models can navigate this nuance.
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Tests whether models correctly apply community-specific language preferences rather than universal person-first or identity-first rules. Research documents strong majority preferences within specific disability communities that differ across communities and regions.
Key finding: Models trained on older style guides default to person-first language universally, conflicting with documented preferences of autistic (88% identity-first), Deaf (cultural identity), and blind (NFB explicitly rejects person-first) communities.
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