Les agences de valorisation de vidéos et la structuration d’une économie des UGC
Bibliographic record
Abstract
L’importance qu’ont acquise les contenus « non professionnels » (user generated contents) a favorisé le développement d’activités spécifiques, de l’ordre de l’intermédiation et de la diffusion numériques. Mises en œuvre par des acteurs économiques, ces activités s’intègrent, non sans frictions, aux secteurs historiques des industries culturelles/communicationnelles. Le présent article soutient l’hypothèse de la constitution d’une filière propre aux productions relevant d’une catégorie construite en référence aux propositions de Richard Caves et regroupant les contenus à bas coûts et réalisés en dehors des circuits habituels de production audiovisuelle industrielle. Il s’agit d’apprécier, d’une part, le phénomène de réintermédiation caractéristique du développement contemporain de l’économie du Web et, d’autre part, l’intensification de la marchandisation de toute forme d’expression.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 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".