Encadrement juridique des plateformes numériques d'écoute en ligne au Québec en matière de découvrabilité des contenus culturels francophones
Bibliographic record
Abstract
Le projet Encadrement juridique des Plateformes Numérique d’Écoute en Ligne (PNEL) au Québec en matière de découvrabilité des contenus culturels francophones poursuit l’objectif principal de définir les contours juridiques de l’obligation de découvrabilité applicable à cette catégorie spécifique de contenus au Québec, notamment lorsque sa mise en œuvre repose sur des dispositifs techniques tels que l’intelligence artificielle (IA). Ainsi, il s’agit, au travers du présent rapport, d’identifier les obligations spécifiques incombant aux acteurs majoritaires de l'industrie musicale au Québec, que sont les PNEL, afin d’identifier des meilleures pratiques en matière d’utilisation de technologies pour la découvrabilité des contenus culturels francophones.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".