Une question de comportement. Recommandation des contenus audiovisuels et transformations numériques
Bibliographic record
Abstract
Parmi l’ensemble des dispositifs visant à orienter l’internaute au sein d’une offre audiovisuelle pléthorique, nous distinguons ceux qui s’appuient sur les jugements et ceux fondés sur l’analyse des comportements. L’étude de certains dispositifs proposés en France montre que les recommandations personnalisées, fondées sur l’analyse détaillée des comportements des internautes, parce qu’elles se révèlent d’une efficacité redoutable, occupent une place de plus en plus centrale. Chacune à leur manière, les diverses formes de recommandation posent aux opérateurs de mise à disposition de contenus audiovisuels en ligne de nouveaux défis qui nécessiteront à l’avenir de tester des formes de différenciation concurrentielle. La recommandation personnalisée algorithmique, en particulier, entraîne d’importantes transformations des modèles économiques, des restructurations des marchés et des renouvellements des métiers.
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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 | 0.012 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.019 | 0.007 |
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".