University of Toronto Social Science Methods Week 2020 - Instructors

Rohan Alexander is a post-doc in the Faculty of Information Sciences at the University of Toronto, Canada. His academic research answers questions in social sciences such as: are our politicians actually representing us, do elections matter, and how can we make political polling better? To do this he builds, cleans, maintains, and shares datasets in a reproducible way, and then uses quantitative methods—such as text analysis, machine learning, and Bayesian hierarchical models—to analyse them. He has been using multi-level modelling with post-stratification (MRP) for around five years and has written multiple academic papers using it. He has delivered workshops on MRP in Australia and the United States. He runs the Petit Poll in Australia, a political survey that which combines non-representative polling data with MRP to cheaply deliver meaningful Australian political polling.

Michael J. Donnelly is an Assistant Professor in Political Science and Public Policy at the University of Toronto. His research is at the intersection of public policy and political behavior, with a particular focus on European politics. He has conducted survey experiments in a variety of countries and contexts, looking at questions of immigration, redistribution, and identity.

Ping-Chun Hsiung has carried out ethnographic fieldwork, interviews, and archival research to advance knowledge and theory in gender studies and qualitative research at local and international levels. Her work challenges the dominant paradigms in qualitative social sciences by unearthing, recognizing, and analyzing research traditions that vary from the western norm. She has decades of experiences publishing and teaching about qualitative interviewing. She has developed an open access online resource called Lives & Legacies: A Guide to Qualitative Interviewing to facilitate the teaching and research of qualitative interview worldwide.

Chris Smith is an Assistant Professor in Sociology at the University of Toronto. Her work on criminal networks includes training materials for practitioners, articles, and her book, Syndicate Women: Gender and Networks in Chicago Organized Crime (University of California Press). She co-authored the invited chapter on Criminal Networks in the forthcoming Oxford Handbook on Social Networks.

Sue Song is a third-year PhD student at the University of Toronto in the Social Psychophysiological Research & Quantitative Methods Lab (SPRQL) and the Lockwood Lab. Sue conducts simulation studies to evaluate the impacts of sample size on Type I error rates.

Catherine Yeh is a 3rd year PhD student in the Department of Sociology. Her research interests are in the areas of the sociology of culture, gender, and economic sociology. She is currently working on a project that analyzes economics and sociology journal text data; this project was what motivated her to learn Python. Through her own experience of learning Python, she understands the challenges of learning coding as a non-coder as well as how Python can be useful to social scientists specifically.