Preceptor in Computational Social Science
Elizabeth is a fourth-year doctoral student pursuing the joint degree between Psychology and Behavioral Science at the University of Chicago and Booth School of Business. She holds a BA, cum laude, from Bowdoin College, and two MA degrees from the University of Chicago (MA in Social Sciences from the MAPSS program and an MA in Psychology). Elizabeth is broadly interested in moral psychology and social cognition. She is a member of the Social Cognitive Neuroscience Laboratory in the department of psychology and the Honesty Morality & Ethics Lab at Booth.
Elizabeth combines tools and measures from developmental psychology, social psychology, behavioral economics, and neuroscience to investigate moral decision making across the human lifespan. In her dissertation work, she is examining the effects of culture and resource scarcity on children’ sharing behavior and the development of cognitive mechanisms associated with generosity. She also explores how different experiences of resource constraint, such as acute hunger and chronic food insecurity, and cultural norms shape children’s conceptions of fairness and their preferences for equality and equity. Likewise, she considers how cultural diversity influences the development of empathetic concern and generosity towards same-race and other-race individuals. In addition to fairness and generosity, she is also interested in moral decision making in the context of honesty. Currently, she is investigating how people judge policies of absolute or flexible honesty and how moral absolutism influences one’s willingness to support hypocritical partners, leaders, and politicians. Relatedly, she is conducting research to better understand how an appreciation for moral nuance develops over time. She employs psychological measures, EEG, and game theory in her research to assess prosocial preferences and related mechanisms contributing to moral cognition.
Statistically, she uses a range of models in her work, including linear, logistic, and linear mixed-effects models, as well as mediation analyses. She predominantly uses R in her research. She also works with RMarkdown and Git in an effort to enhance reproducibility in science. She is excited to help students interested in applying computational techniques to address questions about the social world!