L’Observatoire québécois du loisir en 2014-2015 : consolidation et développement
Bibliographic record
Abstract
Comme chaque annee, l’Observatoire quebecois du loisir profite de son premier bulletin pour faire etat de ses observations generales et presenter ses orientations annuelles. Cette annee, l’OQL, tout en maintenant ses activites habituelles, prendra de l’envergure autant en abordant des themes de facon plus systematique qu’en elargissant son regard au plan international. Les efforts de consolidation de ses outils et de ses produits et services (Bulletin, Portail des benevoles, Bibliotheque electronique en loisir, Journees de l’OQL) portent progressivement leurs fruits, permettant un meilleur service a ses 5000 membres, nombre qui, nous le souhaitons, pourrait atteindre 10 000 a breve echeance. Deja, les clics sur les divers produits et services en ligne de l’OQL connaissent une progression stimulante.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 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".