R.I.P.-H.M.R: A Propos Du Concept De Pole De Developpement et Des Strategies De Developpement Economique Des Regions Quebecoises *
Bibliographic record
Abstract
Au-delà du débat parfois émotif (et peu constructif) qui oppose Montréal aux \nrégions, nous pensons utile de jeter un nouveau regard sur le rapport HMR. Notre \ntraitement du sujet se fera en deux temps. Nous commençons par une mise en contexte \ndu rapport, notamment son lien avec les théories dominantes de l’époque en matière de \ndéveloppement régional. Cet exercice nous sert de prétexte pour revoir la thèse des \npôles de développement. Dans un deuxième temps, nous examinerons les tendances \nde localisation des activités économiques au Canada (de 1971 à 1996) à l’aide d’un \nmodèle centre-périphérie, en jetant un regard particulier sur les cinq régions \npériphériques du Québec. Nous espérons ainsi mieux cerner les effets réels \nd’entraînement de la métropole sur les autres régions du Québec, notamment sur les \nrégions les plus éloignées.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".