The gender binary, the third space, and public university washrooms
Bibliographic record
Abstract
Sexed bathrooms are key locations for sex and gender violence and oppression. Recent political events have made the problem of gendered bathrooms in public spaces much more visible. This project aims to address this issue in part as an iteration of the ways that gender and sex can be critiqued and practiced. It presents and critiques the problem of the gender binary from two perspectives—the feminist, and the feminist poststructuralist—and argues that Homi Bhabha’s third space approach to constructing identity offers us a unique way of critiquing the gender binary while keeping in mind the discursiveness, and fluidity of gender, but also the fundamentality to which many people ascribe their own gender identity. As a demonstration of the way the third space can address the problem of the gender binary this project contextualizes the third space by applying it to gender neutral washrooms. It will also offer case studies of two Canadian universities—Queen’s and Victoria—who have put gender neutral washrooms in place on their campuses.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.039 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".