Basic and Translational Research to Combat Stereotypes and Unintentional Biases

对抗刻板印象和无意偏见的基础和转化研究

• 批准号: 9752640
• 负责人: William Taylor Laimaka Cox
• 金额: $ 38.18万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9752640
• 关键词: Address; Basic Science; Behavior; Behavioral; Cognition; Cognitive; Cognitive Science; Collaborations; Decision Making; Economics; Effectiveness; Evidence based intervention; Feeling; Funding; Habits; Health; Human; Intervention; Knowledge; Laboratories; Learning; Mental Health; Mentors; Modeling; Plant Roots; Prejudice; Process; Research Personnel; Resistance; Rewards; STEM field; Scientific Advances and Accomplishments; Scientist; Social Justice; Source; Stereotyping; Stigmatization; Strategic Planning; Symptoms; Testing; Thinking; Translating; Translational Research; United States National Institutes of Health; Universities; Wisconsin; Woman; Work; cognitive neuroscience; combat; convict; effective intervention; evidence base; field study; implicit bias; innovation; member; novel; physical conditioning; public health relevance; racial minority; response; scientific organization; social; social norm; success; theories

Basic and Translational Research to Combat Stereotypes and Unintentional Biases Automatically activated stereotypes give rise to unintentional (implicit) biases in people's thoughts, feelings, and behaviors, even when such biases are strongly opposed by social norms, personal convictions, and objective evidence. Stereotypes and unintentional biases have been implicated as an important social justice issue with consequences for the mental and physical health of members of stigmatized groups. Stereotypes and uninten- tional biases also create barriers to scientific progress by contributing to the underrepresentation of racial minori- ties and women in science, technology, engineering, and math (STEM) fields. In response to these social, health, and scientific issues, the NIH and nearly every other scientific organization has called for effective interventions to address unintentional biases (NIH, 2015). Many of the responses to these calls, however, have taken the form of interventions that are not grounded in scientific theory and evidence — absent a deeper understanding of human cognition rooted in basic cognitive science, these interventions often seek to address the symptoms of bias with- out treating their underlying causes. Although well-intentioned, these efforts at best do not work and at worst make bias problems worse (Paluck & Green, 2009). The sole intervention that has been empirically demonstrated to produce lasting, meaningful bias reductions is the prejudice habit-breaking intervention, which my colleagues and I have developed and tested experimentally in recent years. The initial success of the prejudice habit-break- ing intervention arises from its strong empirical evidence base. Its scientific model of cognitive and behavioral change builds upon decades of basic research into the mechanisms of stereotyping and unintentional bias. This work powerfully demonstrates why both basic and translational research are needed to effectively combat bias. Stereotyping and biases are supported by the same learning mechanisms that contribute to learning and cognition about non-social targets. Much of my past and future research draws on basic cognitive neuroscience to develop and test novel hypotheses about how specific learning mechanisms (e.g., Hebbian and reward/aver- sion learning) contribute to the persistence of stereotypes and unintentional biases. With a better understanding of the basic processes that make stereotypes resistant to change, I can then enhance my translational work with the prejudice habit-breaking intervention to better address those sources of resistance. In this way, my basic and translational work is synergistic, advancing knowledge around mechanisms of stereotype persistence and im- proving and testing interventions to reduce stereotyping and unintentional biases. As a MIRA investigator, I would 1) expand our knowledge of how basic learning mechanisms perpetuate stereotypes and unintentional biases, and 2) translate basic work to enhance the effectiveness of the prejudice habit-breaking intervention, and 3) conduct expanded experimental field-testing of the intervention in collabora- tion with my campus's administration, using the University of Wisconsin - Madison as a living laboratory.

基础和翻译研究，以打击刻板印象和无意的偏见 自动激活的刻板印象会引起人们的思想，感觉， 和行为，即使这种偏见是社会规范，个人信念和客观的强烈反对的 证据。刻板印象和意外偏见已被作为重要的社会正义问题。 污名团体成员的心理和身体健康的后果。刻板印象和不打算 政治偏见还为科学进步造成了障碍 科学，技术，工程和数学（STEM）领域的领带和妇女。为了应对这些社会，健康， 和科学问题，NIH和其他所有科学组织都要求采取有效的干预措施 地址无意的偏见（NIH，2015年）。但是，对这些呼叫的许多回应已采取 没有以科学理论和证据为基础的干预措施 - 对人类的深入了解 认知植根于基本认知科学，这些干预措施通常试图解决偏见的象征 善于治疗他们的根本原因。尽管如此，这些努力充其量是不起作用的，最糟糕的是 使偏见问题变得更糟（Paluck＆Green，2009年）。经验证明的唯一干预措施 产生持久，有意义的偏见减少是偏见的习惯干预，我的同事 近年来，我已经开发和测试了。偏见习惯习惯的最初成功 - 干预源于其强大的经验证据基础。其认知和行为的科学模型 几十年来，基本研究对定型观念和无意偏见的机制进行了几十年的基础研究。这 工作有力地证明了为什么需要基本和翻译的研究才能有效地打击偏见。 刻板印象和偏见得到了有助于学习和的相同学习机制的支持 关于非社会目标的认知。我过去和未来的大部分研究都取决于基本的认知神经科学 开发和测试有关特定学习机制（例如Hebbian and Reward/Aver-）的新颖假设 Sion学习）有助于刻板印象和无意偏见的持续性。有了更好的理解 在使刻板印象具有抵抗力变化的基本过程中，我可以通过 偏见的习惯干预措施更好地解决了那些抵抗的来源。这样，我的基本和 翻译工作是协同作用的，介绍了刻板印象持久性和不变机制的知识 证明和测试干预措施，以减少刻板印象和无意的偏见。 作为MIRA研究者，我将1）扩大我们对基本学习机制如何持续的了解 刻板印象和意外偏见，以及2）翻译基本工作以增强偏见的有效性 习惯干预和3）进行协作的干预措施的实验现场测试 使用威斯康星大学 - 麦迪逊大学作为生活实验室，与我的校园政府一起。