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

University Of Washington, Seattle WA

Investigators

Abstract

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.