Collaborative Research: Building the Group Identity Concept from the Ground Up

在我们日益紧密联系的社会中，个人跨越多个社会世界。理解这些联系所产生的交叉身份是社会科学和政策的一个紧迫挑战。该项目使用跨文化实证研究和理论驱动的数学建模来概念化和测量群体隶属关系，为社会科学家开发一套经验和概念工具，以更好地参与现代社会生活的复杂性。该项目培训了一名博士后学者和一名博士生，教授科学和数学方法及理论。它还创建了互动的，公开的在线工具，（1）解释群体成员关系的理论，（2）说明我们如何根据经验衡量群体隶属关系和群体之间的关系，以及（3）展示了理论和测量的整合如何能够更准确地描绘我们的社会世界如何演变。这项工作建立在断言身份的外在表达被使用的理论之上工具，以促进分类和加快社会互动，包括合作和侵略。虽然这些理论得到了很好的支持，但它们往往对身份进行了有限的、单维的描述。在这个项目中，研究人员发展文化进化理论，以了解多方面的群体隶属关系如何对个人激励做出反应，包括协调身份和合作的成本和收益。具体来说，它建立了一个新的统计方法，确定和衡量真实的群体之间的关系。通过使用收集的人种学数据进行测试，以捕获人们如何在多个交互领域中理解自己和他人的身份，从而迭代地完善模型。尽管很明显，个人持有多个团体的从属关系，我们目前没有分析工具或语言，充分描述了复杂的性质，团体从属关系。该项目建立这些工具，以帮助理解个人如何在一系列社会关系中定位自己。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

Individuals in our increasingly connected society straddle multiple social worlds. Understanding the intersecting identities that result from these connections is a pressing challenge for social science and policy. This project uses both cross-cultural empirical research and theory-driven mathematical modeling to conceptualize and measure group affiliations, developing a suite of empirical and conceptual tools for social scientists to better engage with the complexities of modern social life. The project trains a post-doctoral scholar and PhD student in scientific and mathematical methods and theory. It also creates interactive, publicly available online tools that (1) explain theories of group membership, (2) illustrate how we can empirically measure group affiliations and the relationships between groups, and (3) demonstrate how the integration of theory and measurement can create a more accurate picture of how our social worlds evolve.This work builds on theories that assert that outward expressions of identity are used instrumentally to facilitate assortment and expedite social interactions, including cooperation and aggression. While these theories are well supported, they often present a limited, unidimensional characterization of identity. In this project, investigators develop cultural evolutionary theory to understand how multifaceted group affiliations respond to individual incentives, including the costs and benefits of coordinating identities and cooperation. Specifically, it builds a new statistical approach that identifies and measures the relationships between real groups. Models are iteratively refined via tests using ethnographic data collected to capture how people understand their own and others’ identities across multiple realms of interaction. Despite being evident that individuals hold multiple group affiliations, we do not currently have analytical tools or language that adequately describes the complex nature of group affiliations. This project builds these tools to contribute to understanding how individuals position themselves across a range of social relationships.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.