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Enregistrement W4361278209 · doi:10.1111/add.16182

Strictly regulated cannabis retail models with state control can provide lessons in how jurisdictions can regulate THC

2023· letter· en· W4361278209 sur OpenAlexaboutno aff
Mafalda Pardal, Elle Wadsworth

Notice bibliographique

RevueAddiction · 2023
Typeletter
Langueen
DomaineMedicine
ThématiqueCannabis and Cannabinoid Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCannabisBusinessHarmGovernment (linguistics)Profit (economics)Harm reductionPublic economicsPublic healthEconomicsLawPolitical scienceMedicinePsychiatry

Résumé

récupéré en direct d'OpenAlex

Government-run or strictly regulated cannabis retail models with heavy state control such as those in Québec (Canada) and Uruguay, respectively, can provide lessons in how jurisdictions with legal cannabis markets can regulate THC. We thank Hall et al. for raising the important topic of regulating delta-9-tetrahydrocannabinol (THC) content in cannabis products [1]. The authors discuss, primarily, the following policy options with a view to reduce cannabis-related harm: (1) banning the sale of high-THC cannabis products, such as edibles, solid concentrates or extracts, (2) capping THC level in legally sold cannabis products and (3) introducing THC-based taxes. There have been reported challenges in introducing some of these types of policies; for instance, in the United States, where most attempts to cap the percentage of THC of cannabis flower have failed [2].* However, other jurisdictions in the region have integrated specific THC-related regulations, particularly, product bans and/or THC caps—which may be simple but viable measures, from a public health standpoint [3]. In what follows, we outline and reflect upon some of the choices made in Uruguay and Québec. It is worth noting that both Uruguay and Québec have not allowed profit-maximizing firms to sell cannabis for non-medical purposes at the retail level. Uruguay has introduced three legal supply channels: home cultivation, non-profit Cannabis Social Clubs (CSCs) and government-regulated pharmacy sales [4].† In Canada, Québec is one of three full government-run retail models, together with Prince Edward Island and Nova Scotia. All other provinces and territories have a full profit-driven retail model or a hybrid model of profit-driven and government-run retail model. Excluding or heavily restricting the participation of profit-maximizing firms could help to limit competition and allow greater control of the products sold and by whom [5]. In terms of THC regulation, both jurisdictions have banned particular high-THC products. In Uruguay, only cannabis flower is legally available—edibles, concentrates, extracts or other cannabis products are not allowed [4]. In Canada, and as Hall et al. rightly highlight, Québec is the only province or territory to restrict product types and prohibit edibles that may be attractive to youth (e.g. chocolate and candy) [6]. In addition, Québec does not sell THC vape oils [7].‡ As illustrated by Uruguay and Québec, jurisdictions can limit the types of cannabis products available to consumers by restricting all non-flower products (e.g. Uruguay) or selected cannabis products (e.g. Québec). Québec and Uruguay have also introduced caps on THC levels for the products supplied through the legal market. Québec introduced a 30% THC limit on all cannabis products [6]. While, in practice, this does not severely limit cannabis flower, as the biological THC ceiling is approximately 35% [8], it limits high-potency products such as solid concentrates, which can be greater than 80% [9]. In Uruguay, a THC cap has been applied to pharmacy sales: registered users are only able to obtain cannabis flower not exceeding 9% THC [10]. This restriction does not apply to CSCs or home cultivation. While CSCs can only distribute cannabis flower among their members, self-reported data from users and representatives of CSCs (c. 2018) suggests that the CSCs might have been distributing cannabis flower with more than 15% THC [11, 12]. Accommodating different THC concentrations among different legal supply options may make these appealing to different segments of consumers, and could potentially minimize the incentives for users to turn to illegal supply channels. It is unclear whether these policy tools have been effective, however. Considering Québec, while previous research has examined provincial differences in areas such as regulations (e.g. [13]), home cultivation (e.g. [14]) or market share (e.g. [15]), there is little research examining THC/product restrictions in Québec compared to other provinces on cannabis-related harms.§ Similarly, in Uruguay, there is no systematic monitoring of THC or potency-related outcomes [16]. An interesting development probably associated with the introduction of the new legal market is the transition from the use of prensado (pressed cannabis), a low-quality and low-THC product, to cannabis flower, which may have unintentionally contributed to an increase in the average potency of cannabis products in the legal and illegal markets [4, 16]. Most research to date in Uruguay has not been able to isolate the effects associated with specific supply models, although a recent study has found an association between the number of home growers and traffic crashes involving injuries [17]—which may be explained, in part, by the fact that the cannabis grown at home may have a higher THC content than the cannabis flower sold at pharmacies, which is capped at 9% THC. It will be important to consolidate the knowledge on the effects of these policy options, especially as other jurisdictions may be moving towards cannabis legalization. Mafalda Pardal and Elle Wadsworth drafted the commentary and approved the final version. We thank Beau Kilmer for his feedback on this commentary. Open access publishing was facilitated by the RAND Corporation. None. N/a.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,009
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,740
Score d'incertitude au seuil0,524

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,009
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0070,007
Communication savante0,0070,005
Science ouverte0,0030,004
Intégrité de la recherche0,0030,005
Charge utile insuffisante (le modèle a refusé de juger)0,0180,001

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 Opus0,024
Tête enseignante GPT0,260
Écart entre enseignants0,236 · 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 source (Gemma direct ou Codex distillé), 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

Citations2
Publié2023
Routes d'admission1
Résumé présentoui

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