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2019 | OriginalPaper | Chapter

8. Quantitative Approaches to Intersectionality: New Methodological Directions and Implications for Policy Analysis

Authors : Joshua K. Dubrow, Corina Ilinca

Published in: The Palgrave Handbook of Intersectionality in Public Policy

Publisher: Springer International Publishing

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Abstract

Intersectionality is a way to approach the collection and use of information and explain data patterns. This chapter discusses several major methodological challenges in the application of quantitative methods to intersectionality: (a) measurement of identity with cross-national survey data, (b) accounting for power structures, and (c) the small n problem. It also discusses several solutions: structural equation modelling, survey data harmonization, big data, and mixed methods. The authors argue that factorial analysis within structural equation modelling invites new possibilities to measure intersections. Survey data harmonization, at a large enough scale, turns into big data with a sufficient number of cases to construct and analyse nuanced intersectional groups. The mixed method approach uses both quantitative data to generalize across populations and qualitative approaches to delve deep into social and political processes that can reveal and explain power structures.

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Title: Quantitative Approaches to Intersectionality: New Methodological Directions and Implications for Policy Analysis
Authors: Joshua K. Dubrow
Corina Ilinca
Publisher: Springer International Publishing
Book: The Palgrave Handbook of Intersectionality in Public Policy
Print ISBN: 978-3-319-98472-8

Electronic ISBN: 978-3-319-98473-5

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-319-98473-5_8