No Half Measures for Beauty Queens: Criteria for Beauty
Bibliographic record
Abstract
À partir d’une enquête ethnographique réalisée à Salsomaggiore (Italie du Nord) en septembre 2001, lors de l’élection de Miss Italia, les auteures comparent la figure de la Miss et les modalités de son élection, dans différents contextes temporels ( XIX e , XX e ) et géographiques (France, États-Unis). Les concours sont de bons exemples pour cerner les mécanismes d’évaluation de la beauté, ainsi que les critères qui la caractérisent, tant du fait des jurys populaires que de jurys d’experts. Ces concours, à l’organisation complexe et délicate, s’avèrent être un mélange savant de critères, allant du mesurable au non-mesurable, du corps à l’âme ; enfin, jonglant entre normes rigoureuses (objectives) et appréciations personnelles (subjectives). Ce contexte devient alors un observatoire privilégié. On y voit se formaliser une norme d’exception, qui évolue selon l’époque et la culture, se révélant significative aussi bien sur le plan local (concours régionaux, nationaux) que global (concours internationaux).
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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".