Hématomes, éraflures, cicatrices
Bibliographic record
Abstract
Les cicatrices, hématomes et autres traces épidermiques sont le lot quotidien des joueuses de rugby. Ces marques corporelles, potentiellement stigmatisantes, agissent en fait comme des repères utiles à l’implication dans cette pratique sportive où l’engagement physique, si ce n’est le combat, est absolument indispensable. Reçues sur le terrain, ces marques consolident les relations individuelles, intimes, proprioceptives à la pratique au point de constituer un des éléments fondamentaux du groupe sportif et de sa métis. Des entretiens et des observations directes auprès de deux clubs de l’Ouest de la France permettent de préciser les manières d’interpréter, de réinterpréter, de gérer ces traces corporelles qui, en dehors du terrain sportif, prêtent le flan à des interprétations parfois invalidantes. L’ambivalence des propos recueillis et des actions sportives relatées souligne la négociation identitaire continue nécessitée par ces traces qui marquent au sens propre et au sens figuré les relations quotidiennes de chaque joueuse. Les relations rugbystiques sont empreintes de dons de soi, révélés par ces hématomes et autres cicatrices.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.028 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".