Bibliographic record
Abstract
Abstract This article considers the archival, political, and ethical questions raised by curating a public exhibit of archival trans erotic material through a case study of the author's 2019 exhibit Trans Porn Imaginaries: A Half-Century of Transvestite Lawmen and Gendertrash from Hell, which presented materials from the Bonham Centre for Sexual Diversity Studies' Sexual Representation Collection and the ArQuives: Canada's LGBTQ2+ Archives at the University of Toronto's iSchool. The exhibit explored intersections between trans erotic representation and BDSM, gay liberation, Playboy's vision of straight male sexual cosmopolitanism, the feminist porn movement, and sex worker politics. In this article, the exhibit's curator discusses the importance of pornography to trans cultural production, the limits of the archive (especially when researching pornography), and the ethics and politics of putting trans sexual representations on display. Ultimately, the author argues that exhibits such as this one can demonstrate the breadth, diversity, and longevity of transness in popular erotic imaginaries and the creativity of earlier generations of trans cultural producers, as well as create the opportunity for some people to see themselves and their desires represented.
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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.011 | 0.029 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".