L’institutionnalisation des fat studies : l’impensé des « corps gros » comme modes de subjectivation politique et scientifique
Bibliographic record
Abstract
Cet article discute de l’institutionnalisation croissante du champ de recherche desfat studies. Entremêlant savoirs militants et connaissances universitaires, ce courant interdisciplinaire et intersectionnel veut dénoncer la discrimination basée sur le poids dans les sociétés occidentales en mettant en avant le vécu des personnesfat. Puisque ces théories et ces pratiques sont peu connues des communautés féministes francophones, en raison d’un déficit de traduction, l’auteure a choisi de présenter certains enjeux liés à la construction sociale des discours sur la « corpulence » et la reconnaissance des « corps gros » comme sujets épistémiques.
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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 | 0.203 | 0.190 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.011 | 0.098 |
| Scholarly communication | 0.026 | 0.023 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 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".