Investigating so-called women’s football clubs in Hauts-de-France: Between (too?) easy access to the pitch and tricky interview relations
Bibliographic record
Abstract
Malgré un plan de féminisation impulsé en 2011, le football français peine à dépasser un taux de féminisation de 7,4 %. Pour tenter de comprendre cet écart entre décisions institutionnelles et mise en œuvre, l’auteure a mené 111 entretiens semi-directifs au sein des 99 clubs de football « féminin » ou intégrant une section féminine de la Ligue des Hauts-de-France. Toutefois, et même si elle ne présentait guère les attributs identitaires ou encore les relais favorisant une entrée dans ce « petit monde », elle n’a jamais essuyé de refus de terrain. Si dans un premier temps, ce sont ses caractéristiques personnelles qui l’ont permis d’accéder et de se maintenir dans ces clubs, dans un deuxième temps, elle a constaté que cette « sur-ouverture », masquait, en réalité, un processus d’instrumentalisation du travail de recherche par les enquêté·es.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".