Les spécificités culturelles de la production de musique metal. Le cas de l’industrie de la musique live en France
Bibliographic record
Abstract
Au-delà de la réception et du partage de la culture metal, on peut se demander quelles sont les spécificités culturelles des processus de production de la musique metal par rapport aux autres musiques populaires, si elles existent. Notre travail en cours porte plus précisément sur la question de la musique live. Comment fonctionne l’économie du concert metal en France ? Y a-t-il des particularités dans le fonctionnement de la chaine de production du metal ? Existe-t-il des acteurs spécifiques ? On montrera que, depuis le début des années 2000, on assiste à une croissance de l’offre d’événements associés au metal et d’entreprises impliquées dans la production de cette musique. Toutefois, une visibilité et un succès plus grands semblent incertains car la légitimité du metal est en partie construite sur un plébiscite restreint dans l’espace public.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".