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

在我们这个联系日益紧密的社会中，个人跨越了多个社会世界。理解由这些联系产生的交叉身份是社会科学和政策面临的紧迫挑战。该项目采用跨文化实证研究和理论驱动的数学模型来概念化和测量群体关系，为社会科学家开发一套实证和概念工具，以更好地参与现代社会生活的复杂性。本项目培养一名科学与数学方法与理论方面的博士后学者和博士生。它还创建了交互式的、公开可用的在线工具，这些工具(1)解释了群体成员的理论，(2)说明了我们如何通过经验来衡量群体隶属关系和群体之间的关系，(3)展示了理论和测量的整合如何能够更准确地描绘出我们的社会世界是如何演变的。这项工作建立在断言身份的外在表达有助于促进分类和加速社会互动（包括合作和攻击）的理论之上。虽然这些理论得到了很好的支持，但它们往往呈现出一种有限的、单一的身份特征。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，它建立了一种新的统计方法来识别和衡量真实群体之间的关系。通过使用收集到的民族志数据进行测试，反复改进模型，以捕捉人们如何在多个互动领域理解自己和他人的身份。尽管很明显，个人拥有多个群体隶属关系，但我们目前还没有分析工具或语言来充分描述群体隶属关系的复杂性。这个项目建立了这些工具，以帮助理解个人如何在一系列社会关系中定位自己。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.