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Advancing quantitative intersectionality research methods: Intracategorical and intercategorical approaches to shared
Greta R Bauer1, Ayden I Scheim2
1Epidemiology and Biostatistics, Schulich School of Medicine & Dentistry, Western University, London, Canada; Women's Studies and Feminist Research, Western University, London, Canada.
Social Science & Medicine (1982)
|March 28, 2019
Summary
This study advances quantitative intersectionality methods by distinguishing analytic from descriptive approaches and validating new discrimination measures. It addresses challenges posed by differential constructs in intercategorical analyses, proposing future research directions.
Area of Science:
- Quantitative Social Science
- Methodology
- Intersectionality Studies
Background:
- Recent advancements propose methods for integrating intersectionality into quantitative research.
- Prior work distinguished analytic from descriptive studies in intercategorical intersectionality.
- New measures for major, day-to-day, and anticipated discrimination were introduced and validated.
Purpose of the Study:
- To respond to commentaries on quantitative intercategorical intersectionality methods.
- To discuss the implications of differential constructs for quantitative analysis.
- To outline an agenda for future methods development in quantitative intersectionality.
Main Methods:
- Distinguishing analytic from descriptive studies in intercategorical intersectionality.
- Utilizing causal mediation decomposition for analytic intercategorical intersectionality.
- Developing and validating new measures of discrimination for intercategorical analysis.
Main Results:
- Causal mediation decomposition is identified as a suitable strategy for analytic intercategorical intersectionality.
- Three new measures of discrimination were validated for intercategorical analysis.
- Differential constructs pose limitations on measures and statistical analyses in intercategorical studies.
Conclusions:
- Continued methods development is needed for quantitative intersectionality.
- Understanding differential constructs is crucial for accurate intercategorical analysis.
- The study provides a foundation for advancing quantitative intersectionality research.
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