Feminist Data Studies

This entry explores intersectional data-analysis rooted in social justice in the social sciences and humanities. The datalogical turn foregrounds the proliferation of algorithmic processing and data as an emergent regime of power/knowledge in the digital datafication of everyday life. Big data, digital methods and data studies are buzzwords that privilege modes of knowledge production to elevate quantitative, abstracted and disembodied approaches over qualitative data approaches. However, 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). These processes are not devoid of different forms of cultural prejudices and discriminations, rather they are often used to exacerbate gendered, sexed, racialized, classed power hierarchies. Sub-topics to be discussed in this entry include feminist ethics of care and alternative data studies (Leurs, 2017; Luka & Millette, 2018); examinations of digital infrastructures including e-waste (Hogan, 2015) and assemblages of hardware and software (Bivens, 2017); and critiques of data gathering and data visualizations (Haraway, 1997; Kennedy et al., 2016).