Conflits autour de l’indication géographique Hatcho miso : de l’exclusion vers le choix d’une alternative ?
Bibliographic record
Abstract
Le cas de la certification de l’indication géographique (IG) Hatcho miso constituerait un des cas les plus conflictuels des politiques japonaises de « marques régionales » promues depuis les années 2000 : les deux fabricants historiques de la ville d’Okazaki se sont en effet retrouvés exclus du groupe des producteurs inscrits dans ce label validé en 2017 par l’État. Les conflits autour de cette certification ont pour toile de fond l’opposition profonde entre deux modes de gouvernance « sectorielle » et « territoriale », qui rend difficile la recherche d’un compromis entre deux parties. Pour sortir de cette impasse, il est proposé de construire un autre marché légitime fondé sur des normes à base civique, délibérative et territorialisée.
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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 | 0.019 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.023 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".