Size Matters to Lesbians, Too: Queer Feminist Interventions into the Scale of Big Data

摘要

How can we recognize those whose lives and data become attached to the far-from-groundbreaking framework of "small data"? Specifically, how can marginalized people who do not have the resources to produce, self-categorize, analyze, or store "big data" claim their place in the big data debates? I examine the place of lesbians and queer women in the big data debates through the Lesbian Herstory Archive's not "big" enough lesbian, gay, bisexual, trans, and queer (LGBTQ) organizing history data set-perhaps the largest data set known to exist on LGBTQ activist history-as one such alternative. In a contribution to critical data studies, I take a queer feminist approach to the scale of big data by reading for the imbricated scales and situated knowledge of data.