Collaborative Research: Identity, Stereotypes and Black College Student Success

拟议的研究将深入探讨黑人大学生对刻板印象威胁的脆弱性的异质性，以及激励措施如何减轻威胁的影响。当一个社会群体的成员，在特定的情况下，觉得自己有可能确认对他们的群体的负面刻板印象，因此表现不佳，特别是在重要或困难的任务。这项研究将有助于通过确定有助于或减轻威胁的因素和刻板印象威胁脆弱性的后果，并制定一项旨在打击其对黑人大学生的影响的政策，有关刻板印象威胁的知识。它解决了当今人力资本投资研究中最重要的问题之一，这就是为什么黑人学生表现不佳，因此更有可能无法完成大学学位。在这个提议中，主要研究者计划进行一系列的实验室实验研究，探索刻板印象威胁与两种类型的激励（计件工资和奖励）之间的相互作用。该项目将探讨一系列可能导致刻板印象威胁脆弱性差异的关键因素之间的关系，并仔细探讨激励的影响及其与刻板印象威胁的相互作用。该提案具有高度的政策相关性，因为它可以为制定干预措施提供信息，以提高在人口分布不同的机构就读的黑人学生的表现。

The proposed studies will explore, in depth, heterogeneity in the vulnerability of black college students to stereotype threat, and the way in which incentives can mitigate the impact of the threat. Stereotype threat occurs when members of a social group, in a given situation, feel themselves to be at risk of confirming a negative stereotype about their group and therefore perform less well, especially on important or difficult tasks. The study will contribute to knowledge about stereotype threat by identifying factors that contribute to or mitigate the threat and the consequences of stereotype threat vulnerability, and by developing a policy designed to combat its effects on black college students. It addresses one of the most important questions in the study of human capital investment today, which is why black students underperform and as a result are more likely to fail to complete a college degree. In this proposal the principal investigators plan a series of lab experimental studies that will explore the interaction between stereotype threat and two types of incentives: piece rates and prizes. The project will explore the relationship among a set of key factors that are likely to be responsible for the differences in vulnerability to stereotype threat, and carefully explore the impact of incentives and their interaction with stereotype threat. The proposal has high policy relevance because it can inform the development of interventions to enhance the performance of black students enrolled at institutions with varying demographic distributions.