The Social Politics of Queer Drag: A Study of San Diego's Queer Community and Queercore Subculture
Bibliographic record
Abstract
The origins of queerness as a cultural idea are dispersed across cultural and scholarly origins. My goal with this dissertation is to bring into conversation how these two were brought into dialogue and how they continue to inform each other. In researching this topic I consult archival materials and conduct interviews with participants in Toronto’s queercore subculture, which began in the mid-80s and has continued, albeit in a modified form, until the present. I supplement this work with scholarship and auto-ethnography of my drag career as Sadie Pins in San Diego between 2018 and 2019. Though eclectic, the exchange between these two events brings out important etymological histories that enlighten contemporary debates in queer of colour critique concerning the multiple marginalizations queer black subjects experience from both a gay mainstream and a resistant queer culture. This dissertation unpacks queer community’s techniques of handling diversification and prods at the contemporary dialogue between academics and cultural workers in order to tease out new possibilities for future inquiry.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.037 | 0.020 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.007 |
| 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".