Des corps et des hommes trans-formés. La musculation comme « technologie de genre »
Bibliographic record
Abstract
Alors que les études trans utilisent les concepts des études sur les masculinités pour réfléchir aux masculinités trans, les études sur les masculinités ne s’intéressent pas aux enjeux trans. Cette exclusion des personnes trans reflète le problème plus général de leur exclusion dans les recherches sur la santé. Malgré la multiplication des travaux portant sur la masculinité, la santé et le bodybuilding, aucune recherche ne s’est attardée aux rapports que les hommes trans entretiennent vis-à-vis de la musculation dans la construction de leur masculinité. Si, à juste titre, des études sur la masculinité et le bodybuilding montrent que cette pratique sert une masculinité hégémonique, je soutiens que cette interprétation fait l’économie d’une analyse intersectionnelle qui intègrerait l’identité de genre (trans/cisgenre) et j’expose les apports heuristiques des théories trans pour la sociologie du genre, de la santé et du sport pour repenser les liens entre masculinité et muscularité.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".