Linking Real-Time Categorization Dynamics to Real-world Social Dynamics

将实时分类动态与现实世界的社会动态联系起来

• 批准号: 1423708
• 负责人: Jonathan Freeman
• 金额: $ 52.55万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2018-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1423708&HistoricalAwards=false
• 关键词: Linking; Real; Time; Categorization; Dynamics

A seminal area of social psychological research is in understanding the root causes of stereotyping and discrimination. How might disparities in hiring, pay, and promotions arise? Disparities could stem, in part, from perceived incongruities between an individual and a prototypical expectation for a particular role, even at the level of facial features. When a target's features fit others' expectations or prototypes, their perceived suitability for the role could be enhanced. This might occur when an individual with more feminine features applies for a stereotypically feminine job, e.g., child care provider, or an individual with more prototypically Asian features seeks entry into a field stereotypically associated with Asian-Americans, e.g., a science/technology/engineering/math (STEM) graduate program. Individuals whose subtle facial features deviate from these expectations may have to struggle to demonstrate their suitability for such positions over and above others who are more prototypical. The proposed research will examine whether the cognitive mechanisms underlying the basic ways we see, understand, and categorize other people influence such real-world social behaviors. In other words, how can biases in the process of categorizing others lead to downstream outcomes of interpersonal and societal significance, such as hiring and admission decisions and voting behavior? Previous work by the investigator Jonathan Freeman (New York University) and colleagues has shown that the process of categorizing individuals is dynamic and evolves over hundreds of milliseconds. For instance, cues specifying gender, race, and age are processed early in the perceptual stream, but as more information accumulates, initial tentative perceptions are gradually sharpened until a final categorization that best integrates all cues stabilizes. Mouse-tracking software developed by the investigator can track this process in real-time, determining how multiple conflicting categories (e.g., "white" and "black") may be activated and resolved while an individual categorizes another person. This technique will be used to examine how individuals whose facial features are slightly atypical for their gender or race may trigger competing social categories (e.g., "male" and "female"), and how such cognitive competition may predict downstream social behavior. The proposed research will first examine processes underlying categorization when competing social categories are activated, and then extend this foundational knowledge to several societally-relevant outcomes, including how categorization on the basis of gender and/or racial cues lead to different hiring and admission decisions. Finally, the neural basis of these categorization decisions will be examined, to test how cognitive and neural dynamics jointly predict important behaviors. Together, this research has the potential to make transformative advances in social psychology by establishing links between real-time cognitive and real-world social dynamics, using cutting-edge methodologies to bridge multiple time scales in person perception. The findings will expose the processes underlying appearance-based stereotyping and their links to social behavior, and have numerous implications for reducing the effects of discrimination in the real world.

社会心理学研究的一个重要领域是理解成见和歧视的根源。招聘、薪酬和晋升方面的差异是如何产生的？差异可能部分源于个人与对特定角色的典型期望之间的不协调，甚至在面部特征层面也是如此。当目标的特征符合其他人的期望或原型时，他们对该角色的感知适合性就会增强。当具有更多女性特征的个人申请典型的女性工作（例如儿童保育提供者）时，或者具有更多典型的亚洲特征的个人寻求进入与亚裔美国人典型相关的领域（例如科学/技术/工程/数学（STEM）研究生课程）时，可能会发生这种情况。那些微妙的面部特征偏离这些期望的人可能不得不努力证明自己比其他更典型的人更适合这些职位。拟议的研究将检验我们看待、理解和分类他人的基本方式背后的认知机制是否会影响现实世界的社会行为。换句话说，对他人进行分类的过程中的偏见如何导致具有人际和社会意义的下游结果，例如招聘和录取决定以及投票行为？调查员乔纳森·弗里曼（纽约大学）及其同事之前的工作表明，对个体进行分类的过程是动态的，并且会在数百毫秒内演变。例如，指定性别、种族和年龄的线索在感知流的早期就被处理，但随着更多信息的积累，最初的初步感知逐渐尖锐，直到最能整合所有线索的最终分类稳定下来。调查人员开发的鼠标跟踪软件可以实时跟踪这一过程，确定当一个人对另一个人进行分类时，多个相互冲突的类别（例如“白人”和“黑人”）如何被激活和解决。该技术将用于研究面部特征在性别或种族方面略有不典型的个体如何引发竞争的社会类别（例如“男性”和“女性”），以及这种认知竞争如何预测下游的社会行为。拟议的研究将首先检查当竞争的社会类别被激活时潜在的分类过程，然后将这些基础知识扩展到几个与社会相关的结果，包括基于性别和/或种族线索的分类如何导致不同的雇用和录取决策。最后，将检查这些分类决策的神经基础，以测试认知和神经动力学如何共同预测重要行为。总之，这项研究有可能通过在实时认知和现实社会动态之间建立联系，使用尖端方法来弥合个人感知的多个时间尺度，从而在社会心理学方面取得变革性进展。研究结果将揭示基于外表的刻板印象的背后过程及其与社会行为的联系，并对减少现实世界中的歧视影响具有重要意义。