Cannabis Legalization in Canada: The Public Health Approach We Did Not Get
Bibliographic record
Abstract
ABSTRACT Objectives: The reader will understand the successes and shortfalls of the government's stated intention to take “a public health approach” to cannabis legalization. Method: Aspects of a public health approach to cannabis legalization were identified from the drug policy literature and from advice provided to government by health policy organizations. These aspects were compared to the output of federal legislation to identify successes and shortfalls. Results: Public health input had some influence on legislation. However, the legislation compromised a public health approach on critical issues such as industry models, minimum age for use, product promotion practices, product types, consumer protection, and holding industry accountable to regulatory provisions. Conclusions: Cannabis legalization can be improved to better reflect a public health priority. Given that legalization will be a process and not a solitary event, this article will be relevant to Objectifs: Le lecteur comprendra les succès et les faiblesses de l’intention déclarée du gouvernement d’adopter une «approche de santé publique» en matière de légalisation du cannabis. Méthode: Les aspects d’une approche de santé publique en matière de légalisation du cannabis ont été identifiés à partir de la littérature sur les politiques en matière de drogue et des conseils fournis au gouvernement par les organisations responsables des politiques de santé. Ces aspects ont été comparés aux résultats de la législation fédérale pour identifier les succès et les lacunes. Résultats: L’apport de la santé publique a eu une influence sur la législation. Cependant, la législation compromettait une approche de santé publique sur des questions critiques telles que les modèles industriels, l’âge minimum d’utilisation, les pratiques de promotion des produits, les types de produits, la protection des consommateurs et la responsabilisation de l’industrie vis-à-vis des dispositions réglementaires. Conclusions: La légalisation du cannabis peut être améliorée pour mieux refléter une priorité de santé publique. Étant donné que la légalisation sera un processus et non un événement isolé, cet article sera pertinent pour: les fournisseurs de soins de santé et les autorités de santé publique qui souhaitent plaider auprès des divers ordres de gouvernement afin d’atténuer les méfaits, et auditoires internationaux observant l’expérience canadienne.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 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".