Ensemble pour lutter contre le tabagisme : l’expérience canadienne
Bibliographic record
Abstract
Le present article fait la synthese de l'etat actuel du droit canadien sur la question du partage des competences en matiere de lutte contre le tabagisme. Apres une analyse exhaustive de l’arret RJR-MacDonald Inc., nous concluons que le Parlement peut legiferer en matiere de publicite du tabac au moyen de sa competence en droit criminel. Ensuite, apres une analyse des arrets Benson and Hedges, Imperial Tobacco et Rothmans, Benson & Hedges Inc., nous concluons que les legislatures peuvent respectivement : legiferer a leur tour en matiere de publicite du tabac a travers leur competence en droits civils, edicter des lois pour recouvrir directement des cigarettiers les frais des soins de sante des victimes du tabac et promulguer des lois plus strictes que le federal a propos de la lutte contre le tabagisme sous reserve d'un conflit.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.019 | 0.014 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.010 | 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".