Dynamique industrielle et stratégie des PME dans l'industrie des viandes
Bibliographic record
Abstract
Uindustrie de la viande, pour faire face à la crise économique, poursuit sa concentration. Les entreprises développent des stratégies de volume et de différenciation afin de renforcer leur compétitivité dans un marché stagnant et très concurrencé. La logique industrielle et financière des groupes privilégie la croissance externe et l’internationalisation ; les PME, généralement plus ancrées dans un système local de production, recherchent des micromarchés. La filière des produits carnés est dorénavant dominée par son aval et la pression de la grande distribution s’exerce de manière croissante : spécialisation des transformateurs, impératifs de la qualité hygiène-sécurité des produits livrés, innovation permanente. Les PME doivent anticiper sur cette dynamique industrielle dont les contraintes sont de plus en plus pressantes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".