Welcome to CERSI

The mission of the center is to support empirical research on the causes and consequences of social inequalities.

Workshop meets Thursdays, 12:00p-1:20pm

210 Prospect Street, Room 203 

Lunch choices for the upcoming talks will be  listed in the google sheet.  https://docs.google.com/spreadsheets/d/1w-kvFUC5YNu0YYL_MQ4GtlH0PtFdxPskZ3L6aIRL4lM/edit#gid=0 barbara.ruth@yale.edu by 10:00 a.m. the Wednesday before the talk.

For Zoom Meetings, ID will be provided.

https://yale.zoom.us  Passcode: CERSI

To be put on the list to receive email notices of talks, contact barbara.ruth@yale.edu.

The workshop focuses on theoretical and methodological issues in the areas of the life course (education, training, labor markets, aging as well as family demography), social inequality (class structures, stratification, and social mobility) and related topics. The core of the workshop is devoted to the discussion of ongoing research by faculty and graduate students. The workshop will also include lectures and hands-on practical training in select topics in quantitative research methodology.

Our research adopts both an inter-generational perspective, in its concern with how advantage and disadvantage is transmitted between generations, and an intra-generational perspective, focusing on the life course and human development. Much of our work is comparative in nature, across time (comparing the experiences of different birth cohorts, for example) and space (cross-national comparative research), allowing us to explore the impact of different institutional environments on the processes that generate social inequalities.  The members of CERSI – faculty, postdocs and graduate students – are engaged in a variety of research falling within this broad area.

CERSI runs a weekly workshop at which faculty, postdocs, students and visitors present their work. Faculty affiliated with CERSI provide research training in the Department’s graduate program and CERSI organizes occasional weekend methods workshops. We are interested in, and employ, a range of quantitative methods in our work. These include models for causal inference with observational data, demographic techniques, simulation, agent-based modeling, and social network analysis.