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Evidence-Grounded Auditing of Identification Assumptions in Climate-Policy Causal Evaluations
Difference-in-differences (DID) studies are widely used to evaluate climate policy, but assessing the evidence supporting their identification assumptions remains challenging. We introduce ARGUS, a structured language-model pipeline that audits reported evidence against an eleven-dimension assumptio
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