From Tomboy to Drag : Las Notas de un Rey in Toronto
Bibliographic record
Abstract
Each drag king you ask will provide you very different answers as to why they have decided to jump on stage.As well, kings emerge from all kinds of offstage identities-there are femmes and fags, straight girls, trannyboys and butches.I identify as a butch.My butch identity offers me everyday comfortable clothes, my cologne and dildos, and my lady.I have also sought out communities of relative safety to surround my butchness.The move from butch to my moments of drag kinging heightens my expression of masculinity.I take the stage I think primarily because for two thirds of my life, I was convinced that it was a humiliating thing for me to be comfortable in men's clothing.The spectacle of the lights and the cheers and the loud booming music celebrating a woman's body or a trans body transformed into a man's for a few minutes, is powerful, and, turns me on.I want to look like a boy.I want to look like a woman.I want to look like a queer, a person who appears to move between the two.I enjoy watching this happen across someone's eyes, when they glimpse a masculine gesture fall from a feminine limb or vice versa.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.008 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.047 | 0.005 |
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".