harnessing the power of data analysis to further understanding of complex systems
Joshua Gary Mausolf
Joshua is a Ph.D. candidate in the Department of Sociology and a preceptor in the Masters of Computational Social Science program at the University of Chicago. He utilizes computational, statistical, and experimental methods to study changes in partisan polarization within and across firms and how partisanship affects hiring and promotional behavior in corporations.
I am pursuing my Ph.D. at the University of Chicago, Department of Sociology. I received my MA at the University of Chicago, BA, summa cum laude from New York University, and was a research fellow at Data Science for Social Good . My general interests intersect at the boundaries of sociology, political science, and economics, which I explore using computational and statistical methods. I am broadly interested in social stratification and inequality, labor markets, corporate boards and organizations, political ideology and polarization, political and media discourse, and social movements. I have worked to apply some of these techniques to urban policy problems such as predicting adverse police incidents or predicting high school dropouts, as well as assessing the effect of crime on residential health. Some of my working projects are available here . My formal research and experience are summarized in my CV .
In teaching, I have emphasized helping individuals improve statistical skills, computational analyses, programming, and research design at both the undergraduate and graduate level. A sampling of topics include multivariate regression modeling, factor analysis, multiple imputation, programming in R and Python, web scraping, natural language processing, and machine learning. I offer detailed information on my teaching under my courses page.
Practiced in statistical data analysis, I specialize in building econometric models for both linear and categorical data, including multiple imputation and time-series analyses. Beyond statistical modeling, I am well versed in the design and implementation of large-scale market surveys. Beyond basic statistical skills, I am also adept at data wrangling and cleaning, and have worked as a research assistant on multiple data-driven projects.