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Enregistrement W4366822568 · doi:10.1111/add.16201

Do not let the ideal be the enemy of good enough regulation

2023· letter· en· W4366822568 sur OpenAlexaboutno aff
Wayne Hall, Janni Leung, Beatriz H. Carlini

Notice bibliographique

RevueAddiction · 2023
Typeletter
Langueen
DomaineMedicine
ThématiqueCannabis and Cannabinoid Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCannabisLegalizationPublic healthBusinessPublic economicsLegislationMarketingAdvertisingMedicinePolitical scienceLawEconomicsPsychiatry

Résumé

récupéré en direct d'OpenAlex

Research on the effectiveness and efficiency of different methods of regulating cannabis potency should be a high priority for public health research that will inform the design of cannabis regulations that minimize public health harms. Our article [1] was intended to alert the addictions field to the critical issue of increased cannabis potency as a public health concern, counter the cannabis industry argument that such regulation is unnecessary and canvas some regulatory options. We thank our commentators for their thoughtful responses, which reveal that regulating tetrahydrocannabinol (THC) potency is more complex than it seems at first sight. Freeman & Lorenzetti highlight consumers’ need for simpler advice on labels, much as standard drinks of alcohol [2]. They have led consensus projects to define standard doses of THC that could be used in this way. They also make the useful point that regulators need to consider setting minimum unit prices for cannabis, much as those that have been implemented to reduce heavy alcohol consumption in some countries. Pardal & Wadsworth highlight the fact that the US model of cannabis legalization—a commercialized for-profit market, with minimal regulation of potency and promotion—is not the only model on offer [3]. Uruguay has limited sales to herbal cannabis and capped the THC content of cannabis sold in pharmacies. The Canadian province of Quebec has banned sales of cannabis extracts, limited the sale of edibles and imposed a cap on the THC content of herbal cannabis. The effectiveness of these policies is well worth investigation. The major empirical question is whether the policies will succeed in the longer term, when neighbouring jurisdictions allow the sale of banned products that can be easily transported across borders. Caulkins points out the economic drivers of increasing cannabis potency in the United States; namely, cannabis producers’ need to make maximum use of whole cannabis plants to compete in a market in which cannabis prices are declining [4]. He argues that bans on the sale of high-potency cannabis products would be simpler and easier to implement than attempting to regulate the potency of the many different cannabis products in US legal cannabis markets. He cites evidence that bans need not generate large-scale illicit markets. We agree that banning high-potency products could be the most effective measure to protect public health in countries contemplating cannabis legalization. We doubt its feasibility, however, in mature US markets that already sell high-potency products and in which cannabis retailers will strenuously oppose the policy. Governments regulating these markets may also prefer the revenue from taxing cannabis products on the basis of their THC content. The regulation of cannabis potency is nowhere near as straightforward as regulating alcohol, but we should not allow the cannabis industry to use this as a reason for failing to regulate cannabis potency. In cannabis regulation, as in any area of public health, we should not allow the ideal to be the enemy of the good enough. Research on the effectiveness and efficiency of different methods of regulating cannabis potency should be a high priority for public health research that will inform the design of cannabis regulations which minimize public health harms. Open access publishing facilitated by The University of Queensland, as part of the Wiley - The University of Queensland agreement via the Council of Australian University Librarians. None.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,252
Score d'incertitude au seuil0,601

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,032
Tête enseignante GPT0,300
Écart entre enseignants0,268 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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