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Record W3202964586 · doi:10.1186/s13011-021-00405-7

An overview of select cannabis use and supply indicators pre- and post-legalization in Canada

2021· article· en· W3202964586 on OpenAlex
Benedikt Fischer, Angelica Lee, Tessa Robinson, Wayne Hall

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSubstance Abuse Treatment Prevention and Policy · 2021
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsImpactMcMaster UniversityUniversity of TorontoSimon Fraser University
FundersInstitute of Psychiatry, Psychology and Neuroscience, King’s College LondonSimon Fraser UniversityKing's College LondonUniversidade de São PauloUniversity of TorontoDepartment of Psychiatry, University of TorontoMcMaster University
KeywordsLegalizationCannabisPublic healthEnvironmental healthPopulationHealth psychologyConsumption (sociology)MedicineDemographyGeographyPsychologyPsychiatrySociology

Abstract

fetched live from OpenAlex

BACKGROUND: Canada implemented the legalization and regulation of non-medical cannabis use, production and sale in 2018 aiming to improve public health and safety. While outcomes from legalization reforms in other jurisdictions mostly rely on US-based data have been assessed to be mixed, Canadian data are only emerging. We compiled select population-level data on key indicators to gauge initial developments from pre- to post-legalization of cannabis in Canada. METHODS: We examined indicators data focusing on the following topics: prevalence of cannabis use, frequency of use, methods/products of consumption, driving after cannabis use, and cannabis sourcing. Indicator data were obtained mostly from national and some provincial population surveys. Prevalence or percentages for the indicators pre- and post-legalization (e.g., 2017- 2020), including confidence intervals were reported, with changes noted, as available in and indicated by the data sources. RESULTS: Data suggested selected increases in cannabis use prevalence, mostly among mid- and older- but possibly also younger (e.g., under legal use age) users. Frequency of use and driving after cannabis use among active users do not appear to have changed. Methods of cannabis use show diversifying trends, with decreases in smoking and increases in alternatives use modes (e.g., edibles, vaping). There is a clearly increasing trend towards accessing cannabis from legal sources among adults, while under-legal-use-age youth do not appear to experience heightened barriers to obtaining cannabis in legalization contexts. CONCLUSIONS: Preliminary indicators on cannabis legalization in Canada show a mixed picture, some similar to US-based developments. While some use increases are observed, these do not necessarily represent indications of increases in cannabis-related harm, also since key (e.g., hospitalization or injury) data are lacking to date. There is a gradual embracing of legal supply sources of cannabis among users, which can be expected to serve public health and safety objectives. At the same time, cannabis use and access among under-age users as a principally vulnerable group do not appear to be hindered or reduced by legalization.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.334
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it