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.

消除陈规定型观念和无意偏见的基础研究和转化研究 自动激活的刻板印象会在人们的思想、感情、 即使这种偏见受到社会规范，个人信念和客观的强烈反对， 证据陈规定型观念和无意的偏见被认为是一个重要的社会正义问题， 对遭鄙视贬斥群体成员的身心健康造成的后果。陈规定型观念和不坚定的 种族偏见也会造成实里少数民族代表性不足，从而阻碍科学进步。 联系和妇女在科学，技术，工程和数学（STEM）领域。针对这些社会、健康、 和科学问题，NIH和几乎所有其他科学组织都呼吁采取有效的干预措施， 解决无意的偏见（NIH，2015）。然而，对这些呼吁的许多反应采取了以下形式： 不以科学理论和证据为基础的干预措施-缺乏对人类健康的更深入了解 认知植根于基础认知科学，这些干预措施往往试图解决偏见的症状， 治疗他们的根本原因。尽管这些努力的初衷是好的，但往好了说，这些努力并不奏效，往坏了说， 使偏见问题变得更糟（Paluck &绿色，2009）。唯一的干预已经被经验证明 产生持久的，有意义的偏见减少是偏见习惯打破干预，我的同事， 我在最近几年里开发并进行了实验测试。偏见习惯的初步成功-打破- 干预措施源于其强大的经验证据基础。它的认知和行为的科学模型 改变建立在对陈规定型观念和无意偏见的机制进行的数十年基础研究的基础上。这 工作有力地证明了为什么需要基础研究和转化研究来有效地对抗偏见。 陈规定型观念和偏见得到了同样的学习机制的支持，这些机制有助于学习和 对非社会目标的认知。我过去和未来的大部分研究都借鉴了基本的认知神经科学 开发和测试关于特定学习机制（例如，Hebbian和奖励/aver- 锡永）导致陈规定型观念和无意偏见的持续存在。有了更好的了解 的基本过程，使刻板印象抗拒改变，我可以加强我的翻译工作， 打破偏见习惯的干预措施，以更好地解决这些阻力的来源。这样，我的基本和 翻译工作是协同作用的，推进有关刻板印象持续性和即时性机制的知识， 证明和测试干预措施，以减少陈规定型观念和无意的偏见。 作为一名MIRA调查员，我将1）扩大我们对基本学习机制如何延续的知识 刻板印象和无意的偏见，2）翻译基本工作，以提高偏见的有效性 打破习惯的干预，以及3）对协作干预进行扩大的实验现场测试- 我与学校管理层达成了协议，将威斯康星州-麦迪逊大学作为一个活生生的实验室。