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Record W4390521703 · doi:10.1186/s42238-023-00213-9

Comparison of perceptions in Canada and USA regarding cannabis and edibles

2024· article· en· W4390521703 on OpenAlexaffabout
Janet Music, Brian Sterling, Sylvain Charlebois, Christine M. Goedhart

Bibliographic record

VenueJournal of Cannabis Research · 2024
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of British ColumbiaDalhousie University
Fundersnot available
KeywordsLegalizationCannabisRecreationRecreational useExploratory researchPerceptionGeographySocioeconomicsPolitical scienceEnvironmental healthPsychologyMedicineLawSociologySocial science

Abstract

fetched live from OpenAlex

BACKGROUND: Canada took a national approach to recreational cannabis that resulted in official legalization on October 17, 2018. In the United States (US), the approach has been more piecemeal, with individual states passing their own laws regulating adult use. The objective of this study was to compare the two jurisdictions. METHODS: Two exploratory, quantitative surveys were administered in May of 2021 in both Canada and the US. One thousand forty-seven Canadian and 1037 US residents (age 19 and older) were surveyed on approaches to and attendant regulations of consumer cannabis. Tests of significance were performed to analyze differences between two groups. RESULTS: No statistically significant differences exist between the two countries in terms of cannabis legalization acceptance. Usage rates among adults was similar with 45% of Canadians and 42% of Americans confirming they consume cannabis. Respondents maintain that they intend to increase their usage, with edibles attracting a rising level of interest from consumers. CONCLUSIONS: Results suggest that public policy in both Canada and the USA needs to change to reflect rapidly evolving acceptance of cannabis products in North America to realize potential economic returns.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.055
GPT teacher head0.420
Teacher spread0.366 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2024
Admission routes2
Has abstractyes

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