The social sciences are undergoing a data sciences revolution spurred on by new statistical and algorithmic techniques, rapid advances in high-performance computing, and the proliferation of large, complex, and heterogeneous data structures (e.g., spatial, relational, temporal, and textual). These developments present exciting opportunities as well as new challenges for social scientists.
Join us for talks, workshops, and other events that explore the impact of the data sciences revolution on the social sciences across U of T and beyond.
September 26: Computational & Quantitative Social Sciences (CQSS) Methods Training Days DSI@UTSC
New approaches to data:
With new data, novel algorithms, and increases in computing power, there is the potential to accelerate knowledge production in a wide range of areas.
World-renowned CQSS researchers
September 26, 2023
CQSS Methods Training Days consist of focused workshops designed to improve and innovate research practices in the social sciences, humanities, and related fields.
Seed funding for cutting-edge, high-impact research in the area of computational and/or quantitative social science.
A day of CQSS research.
Researchers present a lightning round of talks with opportunities for discussion and networking.
Stay tuned for upcoming events.
Monica Alexander (Department of Statistical Sciences, Faculty of Arts and Science, University of Toronto): “Deficits of migration in the age of Covid-19: A new approach to studying changing migration patterns.”
Angelina Grigoryeva (Department of Sociology, University of Toronto Scarborough, University of Toronto): “New Money in the New Economy: The Shift to Stock-Based Compensation and Wealth Inequality.”
Spike W. S. Lee (Joseph L. Rotman School of Management, University of Toronto): “What Do Fake News and Biased News Look Like? A Text-Analysis and Machine-Learning Approach.”
Monica Ramsey (Department of Anthropology, University of Toronto Mississauga, University of Toronto): “Deep Learning in Archaeology and Paleoethnobotany: Imaging Phytolith Training Data.”
Zahra Shakeri (Institute of Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto): “Social and Behavioural Determinants of Health in Prognostic Machine Learning Models for Patient Outcome Prediction.”
