MESD is a new procedural fairness metric that quantifies disparities in explanation quality across intersectional subgroups by combining label-aware aggregation, empirical-Bayes shrinkage, and CVaR weighting.
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MESD: A Risk-Sensitive Metric for Explanation Fairness Across Intersectional Subgroups
MESD is a new procedural fairness metric that quantifies disparities in explanation quality across intersectional subgroups by combining label-aware aggregation, empirical-Bayes shrinkage, and CVaR weighting.