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Part 1: Doing what exactly?
In the first part of the course, the course discusses both the seminal and most recent methodological literature on (doing quantitative) intersectional research in order to enable you to position this course and your own research in the larger debate. It also provides an overview of the different techniques applied, such as descriptive statistics, regression-based analysis, latent class analysis, and (fuzzy-set) qualitative comparative analysis. This first part covers one to two days, in which you discuss the texts in a seminar style. There will be ample room to discuss your own research (plans) and how it fits in this debate and the different quantitative techniques.
Part 2: Really doing it?
Next, you focus on descriptive and regression-based analyses and how the various ways in which statistical practices can be applied in either testing hypotheses derived from taking an intersectional perspective or exploring how inequalities and hierarchies are intersectional. This includes both practicing with different tools on your own or provided data (the first being preferred) as well as critically reflecting on how to interpret and report results, doing justice to your intersectional perspective. The second part of the course covers two to three days, including introductory lectures and practical sessions in which instructors walk around and are available for advice-giving and discussion. You close the days with brief wrap-ups which might include participant presentations.
Part 3: How to do it with success?
Lastly, we close off the course by zooming out again to discuss the organizational practice of doing intersectional statistics: how to publish intersectionality quantitative research, what to considered when you are applying for grants, and the opportunities and limitations in survey design.
