Grain calibration decomposes theoretical constructs into clause-level components, tests each with extractive evidence, and combines results through explicit theory-derived rules to validate LLM coding beyond agreement with human annotators.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Proposes the CoRe-3 (FJS) competency model separating Framing, Judging, and Steering for generative AI use, with preliminary validation via simulations on an open platform showing skill dissociation and validity.
citing papers explorer
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Correct codes for the wrong reasons? validating LLMs as measurement instruments for theoretical constructs
Grain calibration decomposes theoretical constructs into clause-level components, tests each with extractive evidence, and combines results through explicit theory-derived rules to validate LLM coding beyond agreement with human annotators.
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Framing, Judging, Steering: An Assessable Competency Model for Teach-ing Students to Reason With Generative AI
Proposes the CoRe-3 (FJS) competency model separating Framing, Judging, and Steering for generative AI use, with preliminary validation via simulations on an open platform showing skill dissociation and validity.