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Narrowly Tailored Actuarial Models for Affirmative Action in Higher Education

机译:高等教育平权行动的狭义精算模型

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Previous research discusses the superiority of actuarial models over clinical models in a number of areas related to accuracy and consistency in decision making. The current project sought to develop an actuarial candidate selection model for affirmative action in higher education that would achieve the goal of diversity by assigning points for a number of diversity-related characteristics in addition to standard academic admission criteria. Two experiments showed that participants who used actuarial models selected applicants with more markers of academic success and greater diversity using factors favored by recent U.S. Supreme Court cases. The second experiment showed that an unweighted actuarial model also helped decision makers select more minority student candidates and that it produced higher ratings of procedural fairness. The article discusses how an actuarial model might pass Constitutional muster in light of recent Supreme Court cases.
机译:先前的研究在许多与决策准确性和一致性相关的领域中讨论了精算模型优于临床模型的优势。当前项目试图为高等教育中的平权行动开发一种精算候选人选择模型,该模型将通过为除标准学术录取标准之外的许多与多样性相关的特征分配分数来实现多样性的目标。两项实验表明,使用精算模型的参与者使用美国最高法院最近的案件所偏爱的因素,选择了具有更高学术成就标志和更大多样性的申请人。第二个实验表明,未加权的精算模型还帮助决策者选择了更多的少数族裔学生候选人,并且该模型产生了更高的程序公正性评级。本文讨论了根据最近最高法院的案件,精算模型如何通过宪法规定。

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