“Working On and Against” Classic Burlesque Conventions in Zyra Lee Vanity’s <i>Irie Love</i>
Bibliographic record
Abstract
‘Classic burlesque’ refers to a style of contemporary burlesque performance that attempts to recreate some of the conventions of mid-century striptease. In this article, I explore the work classic burlesque does to cite, adapt, and preserve elements of historic striptease through its practitioners’ unique relationship with the archive and repertoire of historic burlesque. Though classic burlesque is fraught with much of the cultural baggage of the history it inherits, it creates an embodied act of preservation less concerned with historical authenticity than with preserving an attitude toward striptease that values ‘tease’ and a personal approach over codified technique. Using Zyra Lee Vanity’s Irie Love act as a case study, I offer that many performers choose to navigate the biases of the form because of the creative potential it affords them to challenge dominant histories of burlesque that perpetuate the erasure of marginalized artists. Vanity does so by reanimating the important contributions of marginalized artists in the history of striptease. While exclusionary standards still inform much of the practice, many of the conventions of classic burlesque are mobile and can be an important site of meaning-making for the artists who practice it.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".