Achat local, produits du terroir, tourisme gourmand et saveurs du Québec : Quelles sont les stratégies gagnantes ?
Bibliographic record
Abstract
Depuis l’entrée en vigueur de la Politique bioalimentaire "Alimenter notre monde", le gouvernement du Québec souhaite ancrer davantage le secteur bioalimentaire sur le territoire en faisant de l’achat local l’une des pierres angulaires de la prospérité économique et sociale. D’ici 2025, il s’est fixé comme cible d’ajouter 10 milliards $ de contenu québécois dans les produits bioalimentaires achetés au Québec. Dans ce contexte, le développement des marques territoriales est une avenue fortement privilégiée ces dernières années. Ces initiatives sont-elles efficaces ? Dans une étude CIRANO (Korai et Lambert, 2023), les auteurs répondent à cette question et proposent plusieurs pistes de réflexion pour mieux structurer le développement et l’encadrement des marques territoriales et faire en sorte qu’elles fassent de plus en plus partie des habitudes de consommation des Québécoises et Québécois.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.000 |
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".