多样性作为优化
Diversity as Majorization
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中文总结 AI 辅助
该研究针对机构在重视多样性与功绩时的群体选择问题，适配 majorization 构建序数多样性预序，提出储备与配额政策，其选择的群体兼具最大多样性与最高功绩，优于其他替代方案。
中文摘要 AI 辅助
机构应如何比较群体多样性，以及在重视多样性与功绩时应选择哪个群体？我们采用基于目标的方法评估整个群体构成，不将任何类型视为内在提升多样性的因素。由于不同多样性指数可能对群体的排序不同，我们转而适配 majorization（优化）以构建一个序数多样性预序。我们证明其最大多样性选择恰好是能最大化广泛类别中所有指数的那些选择。该特性产生了一种储备与配额政策，它会选择最大多样性群体，且在这类群体中选择功绩最高的主体。任何替代方案的多样性更低、功绩更低，或两者皆低。
英文摘要
How should institutions compare group diversity, and which group should they select when they value diversity and merit? We take a target-based approach that evaluates the entire group composition without treating any type as intrinsically diversity-enhancing. Because different diversity indices may rank groups differently, we instead adapt majorization to construct an ordinal diversity preorder. We show that its maximally diverse selections are exactly those maximizing every index in a broad class. This characterization yields a reserve-and-quota policy that selects a maximally diverse group and, among such groups, the highest-merit agents. Any alternative is less diverse, less meritorious, or both.
