Du coaching au mentorat dans la pratique des loisirs organisés : comment favoriser le développement positif des jeunes ?
Bibliographic record
Abstract
Les relations interpersonnelles que les jeunes forgent à l’intérieur des loisirs organisés peuvent directement influencer leur développement. L’objectif de cet article est de faire le point sur la littérature récente des effets et des implications du coaching pour promouvoir une nouvelle perspective du développement positif dans le domaine des loisirs organisés. La première partie de l’article présente les bases théoriques et empiriques de l’effet des loisirs organisés sur le développement positif des jeunes. La deuxième partie examine la manière dont les coachs peuvent améliorer le processus du développement positif des adolescents. La troisième partie propose que les mentors sont aussi susceptibles d’avoir un effet sur le développement positif des jeunes et en quoi ils diffèrent des coachs. Enfin, des limites et des recommandations sont fournies pour les futures recherches et pratiques.
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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 | 0.010 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| 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".