The Directorate of Social, Behavioral and Economic Sciences offers postdoctoral research fellowships to provide opportunities for recent doctoral graduates to obtain additional training, to gain research experience under the sponsorship of established scientists, and to broaden their scientific horizons beyond their undergraduate and graduate training. Postdoctoral fellowships are further designed to assist new scientists to direct their research efforts across traditional disciplinary lines and to avail themselves of unique research resources, sites, and facilities, including at foreign locations. This postdoctoral fellowship award supports a rising interdisciplinary scholar in order to expand the Fellow's experience beyond traditional disciplinary boundaries and focus on a key psychological problem of broad interest and importance. The Fellow will study how people develop social capital-the collected resources available through relationships with other people. Examples of social capital include loans, jobs, time, and advice. Social capital proffers crucial advantages to individuals, but economically disadvantaged people often also suffer from poor access to social capital, limiting their social mobility. Little is known about psychological processes that lead to these disparities. In this work, the fellow will generate a laboratory model of social capital inequality, and test an intervention to increase equitable social capital. In doing so, this research will draw from social psychology, cognitive neuroscience, and sociology, crossing traditional disciplinary lines to characterize how people learn about one another and develop social capital. By characterizing and ameliorating disparities in social capital, the proposal may offer benefits to individuals and society as a whole. By developing an interdisciplinary approach, this project offers new insights to several fields, promoting scientific progress.
This project develops a subfield at the intersection of several disciplines: instrumental social learning, or the study of how people learn about others through interaction. This subfield can offer new insights to its parent fields of cognitive neuroscience and social psychology, and can link individual psychology to sociological patterns. First, the proposed work will test how people form impressions of one another during interaction and how interactions influence later decisions to help others. By examining how people learn about others through active experience, this project links impression formation to decision-making and to neural models of reward-based learning. Second, the proposed work highlights the fact that people learn by experiencing the valuable social qualities of other people, such as generosity, in addition to learning about material benefits others bring to the self. Third, the present proposal will test whether social psychological interventions shape reward-based learning, which has most often been studied in isolation of social context. Finally, these findings would tie psychological processes of learning and decision-making within individuals to broad sociological patterns of social capital, linking social cognition "down" to neural models of learning and "up" to societal-level outcomes. The proposed research links disparities in social capital to the way in which individuals learn about one another through interaction, examining how people build social ties that can promote reciprocity. Specifically, the current research tests whether people reciprocate more with others who bring them material rewards through interaction, above and beyond those who display positive character traits and intentions (Experiments 1 and 2). In addition, the present proposal tests a social psychological intervention (empathic mindsets) to shape patterns of reward-based learning (Experiment 3). To propagate the impact of this research, the Fellow will disseminate findings to the scientific community through journals and conferences, and to the public through science communication outlets. To facilitate the development of interdisciplinary science, the Fellow will create quantitative tools for researchers in social psychology to use computational models of social learning and decision-making.
