Le système ESAR : un concept nouveau de classification des jouets à l’intention des ludothécaires
Bibliographic record
Abstract
Les responsables d’un service de prêt de jouets et de matériel de jeu (joujouthèque ou ludothèque) doivent pouvoir classer un grand nombre d’objets inusités. Les modes de classification retenus pour ordonner une telle collection sont habituellement définis à partir d’une démarche intuitive dépourvue d’encadrement théorique; leur utilisation devient souvent subjective et peu englobante. L’auteur propose une approche nouvelle qui tient compte d’une manière logique et fonctionnelle de trois dimensions éducatives fondamentales impliquées dans le jeu; elle les transpose en système simple, cohérent et efficace en s’appuyant sur le schème théorique de classification à facettes tel qu’utilisé dans le domaine de l’organisation documentaire.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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 teacher head, 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".