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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Notes
- 1.
While ex ante harmonization means that surveys are fielded in different countries with the design intent of an easier harmonization after the data are collected, ex-post means that the surveys were not designed specifically for harmonization (Granda et al. 2010). There is no common definition of ex-post, but from the literature, we can generically say that it is a process (a) in which different survey datasets that were not specifically designed to be compared are pooled and adjusted (i.e. recoded, rescaled, or transformed) to create a new integrated dataset that could be analysed as a typical single-source dataset; and (b) that is based on clear criteria that specifies which datasets are included into the new dataset and clear methods for how variables in the new dataset are created (Slomczynski et al. 2016).
- 2.
Mooney (2016) wrote: “Bilge (2013) argues that a methodology designed to explore the oppression of black women has been commandeered by European feminists (e.g. Lutz et al. 2011), as an intellectual exercise to explore other dimensions of difference, such as disability. Nash (2008) contests this perspective; to associate the method only with black marginalized women is as blinkered as the former privileged white middle-class feminist lens. Crenshaw considers the differences between theoretical positions are less important than the diverse aims and accomplishments of intersectional studies and projects across various disciples.”
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Acknowledgements
Some of this research was presented in sessions of the Fritz Thyssen Foundation conference, “Measuring Women’s Political Empowerment across the Globe: Strategies, Challenges and Future Research,” 2015, in Cologne, Germany; the European Conference on Politics and Gender (ECPG) conference 2015 at Uppsala University, Sweden; and the DomEQUAL Venice Symposium #3, “The Challenges of Intersectionality,” 2018, at Ca’ Foscari University, Venice, Italy. We thank the organizers and participants of those sessions and we also thank Irina Tomescu-Dubrow and Paula Tufis for their comments. This chapter is funded, in part, by a grant from Poland’s National Science Centre for “Political Voice and Economic Inequality across Nations and Time” (2016/23/B/HS6/03916).
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Dubrow, J.K., Ilinca, C. (2019). Quantitative Approaches to Intersectionality: New Methodological Directions and Implications for Policy Analysis. In: Hankivsky, O., Jordan-Zachery, J.S. (eds) The Palgrave Handbook of Intersectionality in Public Policy. The Politics of Intersectionality. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-98473-5_8
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