DH through the Intersectional Lens

Crenshaw, in her essay Demarginalizing the Intersection of Race and Sex (1989), introduces for the first time the term Intersectionality. Intersectionality is an analytical framework that describes how the interaction between different social identities (race, gender, class, disability and sexuality) contributes to the reproduction of systems of discrimination, disadvantage and privilege.

This concept constitutes a powerful tool for us. It allows us to critically examine the ways in which we interpret the world around us. It paves the way for an analysis of social injustices based on equity. If we keep pursuing equality rather than equity, we fail to take into account who is victim of this system. A system conceived to put marginalised communities at a constant disadvantage.

Intersectionality serves well to DH, a field rooted in data and computational methods. At first sight, we might assume that these two areas do not have anything in common. What could the digital have to do with the complex net of social dynamics shaping our experience of the world? Well, unfortunately, quite a lot. In an historical moment when we rely on AI to perform our easiest mental processes, I consider fundamental to remind us that these technologies are made by people, for the people. As argued by Alexander Dunst in Digital American Studies: An Introduction and Rationale (2016): “Despite the Latin root of the term, which refers to something given as a basis for reasoning, digital data are precisely not given. Rather, data constitute representations that are gathered at a specific time, with particular instruments and intentions in mind.” If we keep assuming that data reflect objectivity, while ignoring their political implications, we give up a consistent part of their meaning.

Yet, the issue arises when the “complex net of social dynamics shaping our experience of the world” becomes too complex. Being critic can be an exhausting job nowadays. Every marginalised experience requires deep analysis and sensitivity, especially if these subjectivities are meant to become readable data, for both humans and machines.

In Queer Practice as Research: a Fabulously Messy Business (2015), Campbell and Farrier identify the messiness of queerness as a methodology. The goal of Dhers should not be reduced to “tidying up knowledge”. There must be an ongoing conversation between computational and cultural criticism. We need to embrace the complex and often contradictory directions intersectional approach takes us to. To allow the Otherness to be included, not as an exception but as a fundamental part of the discourse.