Reclaiming representASIAN: how (South)East Asian drag queens on RuPaul’s Drag Race reconfigure queer Asian diasporic subjectivities
Bibliographic record
Abstract
Queer Asian diasporas often contend with a dual perception shaped by Western portrayals of being either “not attractive enough” or objects of racial fetishization. In 2024, the RuPaul’s Drag Race (RPDR) franchise saw a surge in Asian drag performers. Despite their growing visibility, there remains a gap in scholarship exploring how their distinct contributions to queer Asian representation (re)configure queer Asian subject formations in Western societies. Using various theoretical frameworks, we conceptualize Queer Asian Drag Pedagogy (QADP) to contest the racialized and gendered logics that underpin White reductionist narratives of queer Asian representation. Specifically, we analyze the performances of Marina Summers, Nymphia Wind, and Plastique Tiara on RPDR. Our conceptual QADP framework is built upon three tenets: decentralizing Whiteness, embodied kinship through cultural expression, and storying resistance, to dislocate the normative Eurocentric gaze that perpetuates racialized desirability and cultural essentialism that subjugates queer Asian diasporic identities.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.019 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".