Breaking the Prejudice Habit: An Evidence-Based Campus-Wide Intervention Effort

打破偏见习惯：一项基于证据的、全校范围的干预努力 自动激活的刻板印象会导致有偏见的想法、感觉和行为，甚至在人与人之间也是如此 他们的价值观强烈反对偏见。就像不受欢迎的坏习惯一样，这些无意的偏见可能会非常不同- 控制邪教。我早期的开创性工作奠定了我们当代理解人类如何 有意识地放弃偏见的人有无意或隐含的偏见，这导致他们在不知不觉中变得- 拉拢持续存在的群体间差异。无意歧视的幽灵激发了 研究人员、学者和公共政策官员普遍呼吁制定和实施有效的 减少和消除无意偏见的负面影响的发明。 减少偏见，增加少数民族和妇女在科学、技术、工程师领域的代表性-- ING和数学(STEM)领域一直是NIH和几乎所有其他科学组织的首要任务。在 在2016-2020年战略计划中，NIH将缺乏科学的劳动力多样性确定为取得进展的关键障碍。 刻板印象和无意的偏见是科学劳动力多样化的关键障碍，使其更难 代表不足的群体的成员在多条战线上追求科学事业。无意的偏见可能 同样影响那些已经在科学工作队伍中的人，决定资助谁，指导谁， 要么录用，要么录用。他们还影响着未来的科学家，他们需要决定是否要从事科学事业 是否适合他们，以及他们是否“适合”科学工作者。 对号召采取战略以减少无意偏见的影响的许多回应已经采取 不以证据为基础的干预形式。而且，尽管这些努力的用意是好的，但充其量也不是 工作，而且往往会使偏见问题变得更糟。有效地解决社会问题，比如无意中的偏见， 需要以证据为基础的干预措施，以产生持久并影响现实世界结果的变化。这个 经验证明，唯一能够产生持久、有意义的偏见减少的干预措施是我的 成见--打破习惯的干预。这种干预的初步成功植根于我几十年的研究- 发展偏见习惯模式，该模式提出可以通过一个 意识、关心和努力的结合。在几项随机对照研究中，我和我的同事们 已经证明了这种干预的长期有效性。 作为一名Mira调查员，我将能够1)继续作为这一研究的基础的基本偏差研究 干预，2)扩大干预的现场测试和细化，3)评估一系列的行为外- 受到干预的影响，以及4)创建自动化的、易于导出的干预版本 可以广泛传播。

Breaking the prejudice habit: An evidence-based, campus-wide intervention effort, Automatically activated stereotypes can lead to biased thoughts, feelings, and behaviors, even among people whose values strongly oppose bias. Like unwanted bad habits, these unintentional biases can be extremely diffi- cult to control. My early pioneering work forms the foundation of our contemporary understanding of how people who consciously renounce prejudice have unintentional or implicit biases that leads them to be unwittingly com- plicit in the perpetuation of ongoing intergroup disparities. The specter of unintentional discrimination has inspired widespread calls from researchers, scholars, and public policy officials to develop and implement effective inter- ventions to reduce and eliminate the negative effects of unintentional bias. Reducing bias and increasing representation of racial minorities and women in science, technology, engineer- ing, and math (STEM) fields has been a top priority for NIH and nearly every other scientific organization. In the 2016-2020 Strategic Plan, NIH identifies the lack of scientific workforce diversity as a critical barrier to progress. Stereotypes and unintentional biases are key obstacles to scientific workforce diversity, making it harder for members of under-represented groups to pursue careers in science on multiple fronts. Unintentional biases can similarly influence those who are already in the scientific workforce, making decisions about who to fund, mentor, admit, or hire. They also influence potential scientists-to-be, who need to determine whether a career in science is right for them and whether they “fit” in the scientific workforce. Many of the responses to the clarion call for strategies to reduce the impact of unintentional bias have taken the form of interventions that are not evidence-based. And, though well-intentioned, these efforts at best do not work and very often make bias problems worse. Effectively solving social problems, like that of unintentional bias, requires evidence-based interventions that produce changes that endure and affect real-world outcomes. The sole intervention that has been empirically demonstrated to produce lasting, meaningful bias reductions is my prejudice habit-breaking intervention. This intervention's initial success is rooted in decades of my research de- veloping the prejudice habit model, which proposes that “breaking the prejudice habit” can be achieved through a combination of awareness, concern, and effort. In several randomized-controlled studies, my colleagues and I have demonstrated this intervention's long-term effectiveness. As a MIRA investigator, I would be able to 1) continue the basic bias research that forms the basis of this intervention, 2) expand the field-testing and refinement of the intervention, 3) assess a range of behavioral out- comes affected by the intervention, and 4) create automated, easily-exportable versions of the intervention that can be widely disseminated.