Doctoral Dissertation Research: Drivers of Cooperative Behavior in Situations of Conflict

该奖项全部或部分由《2021年美国救援计划法案》（公法117-2）资助。人类通过一系列直接和间接的交流方式了解他们从未见过的人的声誉，这些声誉帮助他们在合作场景中选择新的合作伙伴。本博士论文研究项目调查人们如何沟通声誉信息，声誉如何影响决策，以及哪些类型的沟通抑制或使这些协会中的效用。它的发现揭示了有助于形成社会共识的文化规范，从而允许许多人进行大规模合作。研究结果可以帮助利益相关者为涉及资源保护和气候变化等许多实体的合作困境制定有效的解决方案。此外，该项目为研究生和本科生提供STEM研究机会，并通过公众宣传活动提高科学能力。本项目探讨声誉如何影响冲突情况下的合作决策。声誉是通过各种形式的交流互动传播的，但人们还不太清楚这些声誉是如何通过保持足够的可靠性而持续下去的，以至于人们在未来做出有关合作的决定时依赖它们。利用民族志、调查、小插曲和经济游戏，本研究评估了声誉是如何习得的，对个人声誉的认同程度，以及对声誉的感知如何影响与其他人的互动。通过社会网络分析和贝叶斯统计对数据进行分析，确定参与者之间的协议水平和声誉信息的规模。本项目的数据评估了理论模型的假设，以评估基于声誉的合作的重要性。通过对声誉传播的内容和社会网络分析，多个学科都将受益，因为它提供了对声誉传播的各种功能的洞察，包括排斥、联盟建立、规范执行和建立群体边界。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。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). Humans learn about the reputations of people they have never met through a range of direct and indirect forms of communication, and these reputations help them choose new partners in cooperative scenarios. This doctoral dissertation research project investigates how people communicate reputational information, how reputation impacts decision-making, and what types of communication inhibit or enable utility in these associations. Its findings shed light on the cultural norms that help develop social consensus thereby allowing for large-scale cooperation of many people. The results can help stakeholders develop effective solutions for cooperative dilemmas involving many entities such as resource preservation and climate change. Additionally, this project provides STEM research opportunities for graduate and undergraduate students and improve science competency through public outreach events.This project examines how reputation impacts cooperative decisions in situations of conflict. Reputations are transmitted through various forms of communicative interaction, but it is not well-understood how these reputations endure, by remaining reliable enough that people rely on them when making future decisions about cooperation. Using ethnography, surveys, vignettes, and an economic game, this study assesses how reputations are learned, the degree of agreement about an individual's reputation, and how perceptions of reputation impact interactions with other people. Data is analyzed through social network analysis and Bayesian statistics to identify the level of agreement between participants and the scale of reputational information. Data from this project assesses the assumptions of theoretical models to evaluate the importance of reputation-based cooperation. Multiple disciplines stand to benefit through the content and social network analysis of reputation transmission as it provides insight into the various functions of reputational communication, including for ostracism, alliance building, norm enforcement, and establishing group boundaries.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.