Trail-Running and Ultramarathon: A Multidisciplinary Scoping Review
Bibliographic record
Abstract
Les recherches sur les courses à pied d’ultra-endurance se multiplient, et témoignent de la popularité de ce sport. Quelles places occupent les sciences humaines et sociales dans la compréhension de cette pratique ? Cet article contribue à préciser la compréhension d’un véritable phénomène de société à partir d’une revue de littérature pluridisciplinaire dans le domaine des sciences humaines et sociales sur l’ultra-trail. Une analyse qualitative systémique de leur contenu permet d’identifier trois thèmes majeurs : 1) Engagement et profils des coureurs d’ultra-trail ; 2) Motivations et expériences de ses participants ; 3) Territoires et événements du trail running. Ces résultats ont permis de synthétiser les travaux réalisés à ce jour et constituent un point de départ pour développer d’autres approches. Il apparaît qu’au-delà des ancrages disciplinaires, les résultats présentés résonnent entre eux autant qu’ils mettent en évidence un certain nombre de paradoxes, ce qui est représentatif de la discipline elle-même. Au vu de ces observations, certaines pistes peuvent être explorées pour approfondir ces approches et ces études.
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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 | 0.007 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".