Legibility Dilemmas and State Collection of Gender Data

Hyatt Regency Denver at Colorado Convention Center 

Thousands of state government forms have at least one gender box, a pairing of questions about sex, gender, sex assigned at birth, and gender identity with a variety of answer options. By deciding "who to count, what to count and how to count," gender box design makes political choices about whose experience to value and whose to ignore (Guyan 2022: 1), and whom to make legible to the state (Bowker and Star 1999). They play a critical role in the social process of "determining gender" because, at least in the eyes of the state, they legitimize and define (a subset of) individuals' identity claims (Westbrook and Schilt 2014: 33).

This article describes and analyzes the current state of the gender box-the question-and-answer pair that collects information about a person's sex, gender, assigned sex at birth, and gender identity, among other things-based on a novel dataset of more than 12,000 government forms in use in 2021 and 2022 and computationally scraped from state government websites. Parsing these question/answer pairs, this article demonstrates how and in what ways forms make gender legible for some people and not others, creating social dilemmas for members of marginalized groups and policy dilemmas for those who design gender boxes in the first place. It describes an approach to gender data collection that is wildly heterogeneous but with an entrenched gender binary, and demonstrates that inclusivity is, among other things, a function of date and a state's broader social commitments to LGBTQ+ equality. In the end, this article shows how a federalized yet interdependent structure of government in the U.S. may allow for context-specific legibility for transgender, nonbinary, intersex, and gender-nonconforming individuals while also saddling them with the perpetual risks of inconsistent disclosures to the state. These findings open new doors for researchers and advocates committed to more sensitive, privacy-protective, and effective gender data collectio