I created a website that is a companion to a recently published paper on intersectionality and political participation. The abstract is as follows:
Dubrow, Joshua Kjerulf. 2008. “How Can We Account for Intersectionality in Quantitative Analysis of Survey Data? Empirical Illustration of Central and Eastern Europe.” ASK: Society, Research, Methods 17: 85-102.
While applying intersectionality is common in the qualitative literature, there are few methodological guides for the quantitative researcher. I examine the challenges of incorporating intersectionality into quantitative survey analysis by comparing and contrasting statistical approaches in the analysis of the influence of intersectional demographics. To illustrate these approaches I use European Social Survey (2006) data and focus on gender, ethnicity, and class and their intersections to explain soft political protest in Central and East European countries. Logistic regression equations with dichotomous explanatory variables, including multiplicative interaction terms and their main effects, allow for testing variants of intersectionality theory and hypotheses testing cumulative disadvantage. Some main guidelines for the cross-national quantitative analysis of intersectionality are: (1) multiplicative interaction terms are the best way to measure intersections and account for their properties as being beyond the sum of their parts; (2) care must be taken with the interpretation of main effects and higher and lower order interaction terms; and (3) each intersection has time and space specific consequences. In advocating for widespread use of quantitative techniques to analyze demographic intersections, large survey data sets, especially cross-national ones, provide opportunities for intersectionality researchers to provide empirical support for their theoretical statements and generalizability of their findings.