External link <https://docs.google.com/document/d/1JF1Wwp50uvjN3XCvZ8g6gRjjLGAQf5vv0OVS5BpakJY/preview> Project Description This research study examines patterns in campus protest movements as well as university responses to protest and protest policing in the United States and Canada from 2012 to 2018. The analytic focus is on student anti-racism movements. The project’s research objectives are to: (1) explain the factors that facilitated student mobilization, particularly on anti-racism and labor issues, and its diffusion across campuses and countries; (2) learn the factors determining university administrations’ and police departments’ responses; and (3) understand the relationship between competing claims from protesters and administrators. We are creating the Student & Campus Protest Events Dataset, an innovative dataset based on student and campus protests reported in student newspapers. Approximately 25% of the protest events in the dataset also include data on university leaders’ reactions to protest and/or protest policing activities. Theoretically, the project brings together the sociological study of social movements, organizations, policing, and political culture by using techniques of machine learning and sociological coding as well as quantitative, interpretive, and relational analysis. The analyses will demonstrate the back-and-forth interactive dynamics -- in which activists organize, protest spreads (or not), and targeted leaders respond (or not) -- that are fundamental to social movement mobilization. The end goals are to explain the key ways that movements try to generate social change and the way that institutions attempt to manage protest. We also expect to develop partnerships with student social movement networks and to translate the findings so they are useful to student activists. Job Description You will work on merging the event dataset with institutional data, other protest event data (e.g. BLM), Twitter data, and other local data from cities and campuses (e.g., census, voting data). You also will check data quality and perform quantitative data analysis. This position is for one year and 20 hours a week. It also has the potential for co-authorship with the PIs. Requirements - Quantitative research experience, including basic knowledge of multivariate statistics - Experience with packages for data collection, data manipulation, and data cleaning, namely R and/or Python - Interest in social movements, political sociology, race, organizations, and/or policing - Bachelor’s Degree in quantitative social science, such as political science, sociology, psychology, economics, or a related field Preferred qualifications - Knowledge of time-series and spatial data, including but not limited to survival analysis, diffusion modeling, and spatial analysis - Experience with geospatial methods (e.g. translation from named locations to geospatial coordinates) - Master’s, PhD, or current graduate student in quantitative social science, such as political science, sociology, psychology, economics, or a related field Application instructions Please send a CV, a cover letter, and the names and email addresses of two references to Alex Hanna (alex.hanna@gmail.com) and Ellen Berrey ( ellen.berrey@utoronto.ca). Individuals from underrepresented racial and gender groups are encouraged to apply. Applications are due May 19, 2022. -- Alex Hanna, PhD alex-hanna.com Director of Research, DAIR Institute <https://www.dair-institute.org/> Co-Chair, Sociologists for Trans Justice (s4tj.com) Book some time with me: https://calendly.com/dr-alex-hanna