Doctoral Dissertation Research: Collective Action and Social Networks in a Peruvian Community

博士生亨利莱尔（华盛顿大学），由埃里克博士监督。Smith和Donna Leonetti博士将对社交网络、集体行动、搭便车和声誉之间的关系进行研究。 在这种情况下，搭便车指的是承担的公共产品生产成本低于其公平份额。 本研究将在秘鲁高原这一突出合作行为重要性的极端环境中进行，旨在揭示合作行为在当地是如何被促进的，以及这种行为是如何被各种环境因素所持续或破坏的。秘鲁安第斯山脉的土著人民在政治和经济上长期处于边缘地位。这一历史加上高海拔的压力因素，如低生态系统生产力，使家庭难以确保持续和充足的食物供应和保持良好的健康。应对食物摄入量变化和疾病或伤害事件的一个重要方法是家庭之间的交换网络。这项研究旨在更好地了解一个人在这些至关重要的社交网络中的地位是如何建立和维持的;社会声誉（通过帮助社区项目获得）在这一过程中发挥作用;以及那些过度捐款的人（即，帮助社区项目，即使其他人没有尽自己的一份力量）研究人员将通过各种研究方法收集定性和定量数据，包括：人口普查、半结构化访谈、通过焦点扫描进行的时间分配观察以及社区任务中的参与者观察。还将收集有关参与社区项目的声誉、社区项目的时间分配以及家庭间食物、劳动力和医疗援助交换的数据。分析将使用多元回归和社会网络分析方法，包括指数随机图模型。这项研究是重要的，因为合作行为是人类适应策略的重要组成部分。它在将社交网络动态的前沿分析与慷慨和声誉数据联系起来方面具有理论创新性。该项目还可用于改善社区事业的运作，如至关重要的灌溉和其他资源管理系统。资助这项研究也支持研究生的教育。

Doctoral student Henry Lyle (University of Washington), supervised by Dr. Eric A. Smith and Dr. Donna Leonetti, will undertake research on the relationship among social networks, collective action, free-riding, and reputation. Free-riding in this context refers to shouldering less than one's fair share of the cost of production of a public good. This study will shed light on how cooperative behaviors of individuals are promoted locally, and how such behaviors may persist or be undermined by a variety of contextual factors.The research will be carried out in highland Peru, an extreme environment that highlights the significance of cooperative behavior. The indigenous people of the Peruvian Andes have a long history of political and economic marginalization. This history combines with high altitude stressors, such as low ecosystem productivity, to make it difficult for families to assure a consistent and adequate supply of food and maintain good health. One important method of coping with variability in food intake and with episodes of illness or injury involves exchange networks among households. This research aims to better understand how one's standing in these critically important social networks is established and maintained; the role that social reputation (achieved from helping with community projects) plays in this process; and whether those who over-contribute (that is, help out with community projects even if others fail to do their part) do so because of later benefits.The researcher will collect both qualitative and quantitative data through a variety of research methodologies, including: demographic censuses, semi-structured interviews, time allocation observations via focal scans, and participant observation in community tasks. Data also will be gathered on reputation for participating in community projects, time allocation to community projects, and inter-household exchanges of food, labor, and medical aid. Analyses will utilize multiple regression and social network analytical methods including exonential random graph models.This research is important because cooperative behavior is an essential part of human adapative strategies. It is theoretically innovative in linking cutting edge analysis of social network dynamics with data on generosity and reputation. The project also has practicial applications to improving the functioning of communal undertakings, such as all-important irrigation and other resource management systems. Funding this research also supports the education of a graduate student.