De la musique aux oreilles du public : le prêt d’instruments de musique dans les bibliothèques de Montréal
Bibliographic record
Abstract
En 2016, les bibliothèques de Montréal ont rejoint le programme de prêt d’instruments de musique de la Financière Sun Life. Alors que les autres bibliothèques canadiennes ont pris des orientations similaires, comme concentrer leur collection dans une seule succursale, la ville de Montréal a choisi d’adapter le programme à ses particularités locales et à ses enjeux spécifiques. Cet article fait un récapitulatif de l’implantation du programme dans le réseau des bibliothèques de Montréal, pour ensuite dresser le portrait de son fonctionnement, décrire le programme de médiation accompagnant la collection, avant de terminer avec un bilan des enjeux rencontrés en cours de route et un bref exemple d’un autre programme similaire à la ville de Sainte-Julie.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.016 | 0.011 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 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".