The teaches of Peaches: rethinking the sex hierarchy and the limits of gender discourse
Bibliographic record
Abstract
The goal of this Major Research paper is an exploration detailing how Canadian Electro-Pop artist Peaches Nisker transcends normative gender and sex politics through performance and frames the female erotic experience in a way that not only disempowers heterosexuality but also provides a broader more inclusive sexual politics. Through this analysis I focus specifically on three distinct spheres; performance, fandom and use of technology to argue that her critique of sexual conventions provides an expansive and transgressive new definition of female sexuality. Musical performances by female artists, particularly icons such as Madonna and Britney Spears, have demonstrated popular culture's inability to legitimize queer and non-compulsory heterosexual practices. These performances often function as limiting representations of the sexual female. Queerness in popular music culture is often showcased as non-traditional and used as a form of spectacle. The appropriation of homoerotic imagery has traditionally served the purpose of appeasing the mass patriarchal pornographic gaze. I argue that Peaches embodies the essential queer spirit, presenting a politics that builds upon a more fluid sexuality. She reconfigures queer and heterosexual imagery using the language and framework that has been provided by compulsory heterosexuality, to shatter the foundation so often used against women and thereby presenting a new female erotic.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.076 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".