The gender binary will not be deprogrammed: Ten years of coding gender on Facebook
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A February 2014 iteration of Facebook’s software upgraded the number of options for gender identification from 2 to 58. Drawing on critical theoretical approaches to technology, queer theory, and insights from science and technology studies, this iteration is situated within a 10-year history of software and user modifications that pivot around gender. I argue that the gender binary has regulated Facebook’s design strategy while the co-existence of binary and non-binary affordances has enabled the company to serve both users and advertising clients simultaneously. Three findings are revealed: (1) an original programming decision to store three values for gender in Facebook’s database became an important fissure for non-binary possibilities, (2) gender became increasingly valuable over time, and (3) in the deep level of the database, non-binary users are reconfigured into a binary system. This analysis also exposes Facebook’s focus on authenticity as an insincere yet highly marketable regulatory regime.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it