Bibliographic record
Abstract
La musique d’aujourd’hui présentée au jeune public est multiple dans ses approches, dans ses sonorités et dans les messages qu’elle cherche à transmettre. Tour à tour didactique, expressive ou émotive, elle varie énormément de par sa forme, son contenu et sa présentation. Certains des compositeurs québécois les plus actifs dans le domaine, dont Denis Gougeon, Yves Daoust, Ana Sokolovic, Isabelle Panneton et Zack Settel, ainsi que John Estacio (Canada), Julian Wachner (États-Unis), Isabelle Aboulker et Coralie Fayolle (France), font la lumière sur ce genre musical particulier, en perpétuelle évolution. Ils évoquent les raisons qui les ont motivés à écrire pour les jeunes, les défis liés au genre, le choix des livrets qui les inspirent, le langage musical adopté, la prolifération du multimédia, la portée des spectacles et l’avenir du genre.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.013 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".