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: 10224866
• 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/10224866
• 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.

与刻板印象和无意偏见作斗争的基础研究和翻译研究 自动激活的刻板印象会在人们的思想、感觉、 和行为，即使这种偏见受到社会规范、个人信念和目标的强烈反对 证据。刻板印象和无意的偏见被认为是一个重要的社会正义问题 对受污名化群体成员的心理和身体健康的影响。刻板印象和不灌输- 传统偏见也造成了科学进步的障碍，因为它导致了种族少数族裔的代表性不足-- 科学、技术、工程和数学(STEM)领域的关系和女性。作为对这些社会、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进行有效的干预 解决无意的偏见(NIH，2015)。然而，对这些电话的许多回应都采取了以下形式 没有科学理论和证据的干预--缺乏对人类更深层次的理解 认知植根于基础认知科学，这些干预措施通常寻求解决偏见的症状- 而不是治疗他们的根本原因。尽管这些努力的用意是好的，但往好了说是行不通的，往坏了说也是徒劳的。 使偏见问题变得更糟(Paluck&Green，2009)。已经被经验证明的唯一干预措施 产生持久的、有意义的偏见减少是打破偏见习惯的干预措施，我的同事们 近年来，我进行了开发和实验测试。偏见习惯的初步成功--打破-- ING干预源于其雄厚的经验证据基础。其认知和行为的科学模型 变革建立在对刻板印象和无意偏见机制的数十年基础研究的基础上。这 这项工作有力地证明了为什么需要基础研究和翻译研究来有效地与偏见作斗争。 刻板印象和偏见得到了相同的学习机制的支持，这些机制有助于学习和 对非社会目标的认知。我过去和未来的许多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，Hebbian和奖励/平均)的新假设 锡安学习)助长了刻板印象和无意偏见的持续存在。更好地理解 在使陈规抵制改变的基本过程中，我可以通过以下方式加强我的翻译工作 打破偏见的习惯干预，以更好地解决这些阻力的来源。通过这种方式，我的基本和 翻译工作是协同的，围绕刻板印象持续和印象的机制推进知识。 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的一名研究人员，我会1)扩大我们对基本学习机制如何永久化的了解 陈规定型观念和无意偏见，以及2)翻译基础工作，以加强偏见的有效性 打破习惯的干预，以及3)扩大实验领域--合作中的干预测试-- 将威斯康星大学麦迪逊分校作为一个活实验室，与我的校园管理部门进行了沟通。