Race, Ethnicity, and Quantitative Methodology
- Mosi A. Ifatunji, University of North Carolina at Chapel Hill
Social statistics were developed - in large part - to measure and study race and racialized population groups. It was during the eugenics debate of the early 20th century that interest in social statistics grew exponentially - i.e., as social scientists and demographers sought to demarcate racial groups and to assess differences between population groups so specified. Although interest in social statistics was initially closely tethered to the study of race and social stratification, today most social scientists study these topics separately. As a result, best practices in social statistics are often blind to race and ethnicity and students of race and ethnicity are often uninterested in statistics.
This course will develop quantitative researchers who give greater, more careful and keen consideration to how race and ethnicity fit in their statistical models. This course will also give race and ethnicity scholars a greater ability to understand, critique, and use quantitative methods. In order to achieve these goals, the course is mostly conceptual, and participants are strongly recommended to have had one of each of the following courses prior to attendance: a basic course in race and ethnicity, a graduate level course in research methods, and a graduate level course in social statistics.
The course will cover four broad topic areas. The first week lays the groundwork for the course by focusing on key concepts and includes a special session on race, ethnicity, and research ethics. The week explores foundational concepts including: race, ethnicity, racialization, ethnogenesis, inequality, stratification, prejudice, discrimination, and ethnoracial orders. Week two focuses on measurement and operationalization. Topics include: measuring race and ethnicity, operationalizing race and ethnicity in multivariate models, measuring group disparities, measuring prejudice, and measuring discrimination. Week three covers research design and data collection strategies. Topics include: questionnaire design, sampling and social survey methods, and experimental and quasi-experimental methods. This week will also include a review of newer emerging methods - i.e., big data and agent-based models. The course will conclude with a detailed focus on statistical analysis and inference. The final week reviews practical strategies for appropriately assessing race and/or ethnic "effects" across a range of statistical methodologies - e.g., statistical interactions, multivariate decomposition, propensity score analysis, and structural equation models. It also introduces datasets, available from ICPSR, that are mindful of many of the issues covered in the course.
For those interested in a more focused study of quantitative methodologies, participants are encouraged to dual enroll in one of the many training courses offered at the ICPSR Summer Program. For more information, including a detailed course description, please email: email@example.com.
Fees: Consult the fee structure.
Location: ICPSR -- Ann Arbor, MI
Date(s): June 22 - July 17
Time: 1:00 PM - 3:00 PM