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Weighting admission scores to balance predictiveness‐diversity: The Pareto‐optimization approach

Although many medical schools seek to improve diversity, they grapple with the challenge of how to weight the scores of different admission methods to achieve a balance between obtaining high predictiveness and ensuring diversity in the selected student pool. Yet, in large‐scale employment settings, substantial progress has been made on this front: Pareto‐optimization has been introduced as an elegant statistical tool to assist decision makers in determining the weights assigned to selection methods in advance (before the selection has taken place) so that a selection system is designed to achieve an optimal balance as reflected by the trade‐off that one outcome (e.g., predictiveness) cannot be improved without harm to the other outcome (e.g., diversity).