Causally Interpreting Intersectionality Theory

Abstract

Social scientists report difficulties in drawing out testable predictions from the literature on intersectionality theory. We alleviate that difficulty by showing that some characteristic claims of the intersectionality literature can be interpreted causally. The formalism of graphical causal modeling allows claims about the causal effects of occupying intersecting identity categories to be clearly represented and submitted to empirical testing. After outlining this causal interpretation of intersectional theory, we address some concerns that have been expressed in the literature claiming that membership in demographic categories can have causal effects.

Carnapian explication and ameliorative analysis: a systematic comparison

“…18 At this point, it might seem that a fruitful explication may well have the potential to serve the purposes of social engineering, but that this potential is rarely or perhaps never truly realized. To alleviate this worry, I now discuss a concrete example of an explication of a socially relevant concept, which leads to precise predictions and thus can serve as an instrument for social intervention and social reform: the explication of the concept of intersectionality offered in Bright et al (2016).…”

“…For example, the analysis of intersectionality in Bright et al (2016) is clearly an instance of explication, but arguably not an instance of ameliorative analysis, despite having the potential to lead to social interventions. 32…”

“…Closing Sect. 1, I discuss an example of a Carnapian explication of the concept of intersectionality (Bright et al 2016). In Sect.…”

Replacing Race: Interactive Constructionism about Racialized Groups

“…However, as more light-skinned groups were elicited into the 'white race' in the early to mid-20 th century, visible biological difference became-once again-central to race thinking (Carter 2007). The importance of visible biological differences in the gender and race has tended to proceed as if 'all the women are white, all the blacks are men'" (Bright, malinsky, & Thompson 2016). Gender certainly plays a role on the group level as well.…”

When journal editors play favorites

“…I am inclined to think bias based on academic affiliation involves epistemic injustice, but I leave arguing this point in detail to future work. 17 This is a simplifying assumption: one could imagine having biases against multiple groups of different strengths, biases whose strength has some random variation, or biases which intersect in various ways (Collins and Chepp 2013;Bright et al 2016). However, the assumption in the main text suffices for my purposes.…”