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The Program in Quantitative Social Science has an active postdoctoral fellow program. This program brings in bright and talented young scholars, who spend a year or two at Dartmouth following completion of their doctorates. While on campus, QSS postdoctoral fellows work on their own research agendas and also collaborate with QSS-affiliated faculty members on joint projects.
David uses empirical and computational methods to explore political institutions in the United States, focusing on elections and representation. He is especially interested in how elections are affected by the location and manipulation of political boundaries. For example, David is involved in research that uses computer-automated districting algorithms to analyze the impact of gerrymandering on the partisan composition of Congress and on the lack of electoral competition in House elections. Furthermore, David's dissertation uses agent-based models and GIS methods to explore various ways in which geographically-defined political boundaries affect representation and policy administration.
Immediately following his QSS fellowship, David served for two years as a lecturer for both QSS and the Department of Government. While at Dartmouth, David was involved in a number of projects exploring ways in which elections distort representation. He conducted research on disenfranchisement, measuring the extent to which African-Americans are removed from the electorate in thousands of legislative districts in the United States due to health and incarceration disparities. He also analyzed claims of fraudulent voting in the 2016 presidential election to determine if voter fraud had a significant effect on Hillary Clinton's popular vote. David iscurrently working on a project that uses millions of voter check-in times during Florida's early voting period in 2012 to analyze how waiting in line to vote affects future electoral participation.
David will begin a tenure track position at the Univeristy of Georgia in the fall of 2019
DJ's research uses experimental and statistical methods to examine how misinformation distorts important aspects of democratic politics, including public opinion, representation, and accountability. He also studies best practices in fact-checking and how to help people make decisions based on the best available evidence. His methodological interests are in survey and experimental design with particular focus on the measurement of knowledge.
DJ has been an Assistant Professor of Political Science in the School of Global and Public Affairs at IE University in Madrid since completing his QSS fellowship.
As a political communication scholar, Erik seeks to understand the political consequences of the public’s interactions with the media environment. His research examines the capacity of media outlets to provide political news, the choices individuals make to consume (or avoid) political information and the effects of exposure to political messages on public opinion. He studies these topics using a variety of data sources including digitized media directories, survey-linked web browsing data and survey experiments.
After one year with QSS, Erik accepted a tenure track position with the Department of Political Science at Texas A&M University
Yuki Shiraito works primarily in the field of political methodology. His research interests center on the development and applications of Bayesian statistical models and large-scale computational algorithms for data analysis. He has applied these quantitative methods to political science research including a survey experiment on public support for conflicting parties in civil war, heterogeneous effects of indiscriminate state violence, and the detection of text diffusion among a large set of legislative bills.
After one year with QSS, Yuki accepted a tenure track position in Political Science at the University of Michigan
Jin's research examines the effects of political (mis)information on public opinion. In an on-going research project, he uses several survey experiments and an observational study to show that people account for the quality of evidence as they revise their opinions about highly polarized political issues. Methodologically, Jin is interested in identifying communication effects based on real-world events such as political rumor diffusions and sudden shifts in news cycles. In a paper conditionally accepted for publication in the Quarterly Journal of Political Science, he highlights methodological challenges in identifying the effects of fake news, and suggests exploiting temporal overlap between rumor circulations and survey interviews can be a useful alternative, using an accidental and sudden spread of “Obama-is-a-Muslim” myths in September 2008 as an illustrative example.
Jin will be completing another postdoc at Penn State University beginning in the fall of 2019
Jun's research investigates the drivers of health disparities in the lives of adolescents, including family, friendship network, and cultural effects. She also applies theories of intersectionality to examine workplace inequality and criminal injustice. In particular, she explores the role of race, emotion expression, and interactional styles in shaping employers’ evaluation in the workplace and jurors’ sentence decision-making in court. Much of Jun's work involves analysis of longitudinal datasets and large-scale surveys. She also collects her own data by designing and conducting original survey experiments.
Jun will begin a tenure track position at Georgia State University in fall 2019