A Bayesian empirical likelihood procedure combined with sample-splitting machine-learning adjustment estimates the effect of borough Black population share on stop and search disproportionality, finding a negative association for expressive crimes.
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A scalable Bayesian double machine learning framework, with application to racial disproportionality assessment
A Bayesian empirical likelihood procedure combined with sample-splitting machine-learning adjustment estimates the effect of borough Black population share on stop and search disproportionality, finding a negative association for expressive crimes.