Feminist Data Studies

Abstract

Data, datafication, and data studies have become key buzzwords characterizing contemporary life in the digital and knowledge economies. Critiques and ways to mobilize data for social and economic benefit are variously-and often contradictorily-imagined by scholars in disparate disciplines, as well as by politicians and policy makers, corporations and nonprofit organizations, citizens, and activists. The datalogical turn to study the structuring of data foregrounds the proliferation of algorithmic processing and data as an emergent regime of power and knowledge and value exchanges in the digital datafication of everyday life and culture. Big Data, digital methods, and data studies are more than simply semantic currencies neutrally describing present-day conditions. Indicative of Big Data as a privileged mode of knowledge production, all too often, quantitative, abstracted, and disembodied approaches are privileged over qualitative data approaches. However, we argue, alongside many others, that database technologies and human experiences are always necessarily mutually constituted (Metcalf & Crawford, 2016). Infrastructures, categorizations, and algorithmic processing are commonly black-boxed and therefore invisible with the consequence that data generated is never raw, but always cooked (Bowker, 2006). Data, data analysis, and data visualizations are never neutral, but are power ridden, situated, as they are subject to choices made by humans and machines. Yes, we "are" data, as evidenced by the way that a growing number of the world's populations are increasingly rendered as datafiable (see, for example, Cheney-Lippold, 2017). Data typologies are inescapably based on a moral agenda that prioritizes one worldview over many others. The military-industrial data analysis machinery reestablishes boundaries (and therefore barriers) between "data-haves" and "data have-nots," which are commonly based on categories of difference. Processes of datafication of culture and populations are never devoid of the various forms of cultural prejudices and discriminations. Rather, they are often used to exacerbate intersectional power hierarchies based on gender, sexuality, race, class, ability, religion, migration status, and age.In this entry, we draw from the principles of feminist ethics of care-which include attention to human meaning-making, situatedness, context-specificity, dependencies, and relationalities-to elaborate what feminist data studies could look like (Leurs, 2017;