Decolonising Drag: When Queer Asian Artists Do Drag
Bibliographic record
Abstract
This chapter starts with a question: how do queer artists of Asian heritage living outside Asia do drag? This question is primarily motivated by the understanding that there are distinct drag traditions in each country and culture, and that there has been a long crossdressing and drag tradition in Asian performance cultures. It is also propelled by the understanding of the entangled relationship between queer and drag cultures, as well as the complex identity issues brought about by the artists’ diasporic positionality. Seen in this light, whether, how and why queer Asian artists do drag, and for what audiences, is not a straightforward question, and the answers are usually contingent, personal and indeed political. I will use the drag performances of three queer Asian artists living in the West as case studies: Hong Kong-born, Melbourne-based artist Scotty So (蘇港鴻), Mainland China-born, London-based artists Whiskey Chow (b.1989), and Toronto-born, London-based artist Sin Wai Kin (單慧乾 formerly Victoria Sin, b.1991). They are all artists working with a range of media and artforms such as performance, film and installation. Most importantly, all three artists have used drag in their artworks to explores issues of identity.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.018 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".