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: 9983120
• 负责人: William Taylor Laimaka Cox
• 金额: $ 38.13万
• 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/9983120
• 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.

对抗刻板印象和无意偏见的基础和转化研究 自动激活的刻板印象会导致人们的思想、情感、 和行为，即使这些偏见遭到社会规范、个人信念和客观客观的强烈反对 证据。刻板印象和无意识的偏见已被视为一个重要的社会正义问题， 对受侮辱群体成员的身心健康造成的后果。刻板印象和无意识的 偏见还导致少数族裔代表性不足，从而对科学进步造成障碍。 科学、技术、工程和数学 (STEM) 领域的关系和女性。为了应对这些社会、健康、 和科学问题，美国国立卫生研究院和几乎所有其他科学组织都呼吁采取有效干预措施 解决无意的偏见（NIH，2015）。然而，对这些呼吁的许多回应都采取了以下形式： 缺乏科学理论和证据的干预措施——缺乏对人类更深入的了解 认知植根于基础认知科学，这些干预措施通常旨在解决偏见的症状 治疗其根本原因。尽管本意是好的，但这些努力充其量不会奏效，最坏的情况也是如此 使偏见问题变得更糟（Paluck＆Green，2009）。经经验证明的唯一干预措施 要产生持久、有意义的偏见减少，就要采取打破偏见习惯的干预措施，我的同事们 我近年来进行了实验开发和测试。打破偏见习惯的初步成功—— 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 变革建立在数十年对成见和无意偏见机制的基础研究之上。这 这项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对抗偏见。 陈规定型观念和偏见受到有助于学习和学习的相同学习机制的支持。 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础认知神经科学 开发和测试关于特定学习机制（例如赫布和奖励/平均）如何 认知学习）会导致刻板印象和无意识偏见的持续存在。有了更好的理解 了解了使刻板印象难以改变的基本过程，然后我可以通过以下方式增强我的翻译工作 打破偏见习惯的干预措施可以更好地解决这些阻力来源。这样，我的基本和 转化工作是协同作用的，可以推进关于刻板印象持续和即时机制的知识。 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 MIRA 调查员，我会 1）扩展我们对基本学习机制如何持续存在的知识 刻板印象和无意识的偏见，2）转化基础工作以增强偏见的有效性 打破习惯的干预措施，以及3）对协作干预措施进行扩大的实验现场测试 与我的校园管理部门合作，将威斯康星大学麦迪逊分校作为一个活生生的实验室。