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Data-Adaptive Experimentation to Find Contexts with the Most and Least Discrimination
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Description: Discriminatory human choices are of central interest across the social sciences. We would like to know, for example, how individuals in the U.S. discriminate on the basis of education when choosing which immigrants to prioritize for immigrant visas. But discrimination is not a uniform phenomenon: it occurs within a context. Some individuals in the U.S. might discriminate by education to a greater degree when immigrants come from certain geographic regions. In this project, we extend methods for data-adaptive experiments to search inductively for contexts in which discrimination is especially large.
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