Bibliographic record
Abstract
Surgical Culture Transformations discover my face/don't hesitate click on me! 1This exclamation and command once appeared on the front page of French performance artist orlan's website, beneath her name.And, indeed, as I navigated my cursor over her face, her face transmogrified into a map of links to various pages on the site featuring images of her artwork; upcoming, current, and past exhibitions; her writing; review essays about her art; and other materials related to her work.orlan's face maps an assortment of eclectic cultural referents; it is a discoverable face that is strangely beautiful, although not according to the standards exemplified in North American fashion magazines.Her hair is wild, half of it greyblack and the other half white: it rises into the sky, an evocation of the Bride of Frankenstein.Hazel eyes gaze out from round, black plastic glasses with thick yellow arms, frames reminiscent of Sigmund Freud's iconic glasses.orlan's dark red lipsticked lips purse together in a notquite smile, a hybrid of vampy film noir actresses like Veronica Lake and the art history icon Mona Lisa.Her temples jut out, augmented with silicone implants originally designed to enhance cheekbones; for this facial feature, we have no immediate cultural referent.When orlan spoke at the Ontario College of Art and Design in the fall of 2008, she had made up her otherworldly temples with luminescent glitter that fascinated my gaze throughout the talk.These temples, made of silicone and highlighted with pearlescent makeup, gleamed.They had been implanted during one of her cosmetic surgery performances from the series "The Reincarnation of Saint orlan" in the 1990s.orlan's facial map is captivating because it is a conglomeration of features familiar to popular culture and Western art history, yet made peculiar through surgical intervention.While her performances are frequently mistaken for a form of beautification, obsession with feminine perfection, or masochism, orlan offers the following commentary on her art:
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.634 | 0.407 |
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".