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Record W6925291142 · doi:10.17605/osf.io/48kj6

How do Canadians really feel about Cannabis? Levels of support and consumer perceptions of cannabis regulations in Canada.

2024· other· en· W6925291142 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueOpen Science Framework · 2024
Typeother
Languageen
FieldEnvironmental Science
TopicIchthyology and Marine Biology
Canadian institutionsnot available
Fundersnot available
KeywordsCannabisPossession (linguistics)Recreational useRecreationPerceptionMedical cannabis

Abstract

fetched live from OpenAlex

In October 2018, the Cannabis Act was passed in Canada, legalizing the use, growth, and sale of cannabis from authorized sources for recreational purposes. The Act includes regulations intended to minimize the public health impact of legalization. To date, there is little evidence on the impact of specific cannabis regulations, including their impact on consumer use and perceptions. The study has three objectives: 1) to examine awareness and support for nine specific policies: cannabis legalization, authorized retailers, retail store density, mandatory health warnings on packages, retail store marketing, restrictions on advertising, personal possession limits, and THC limits on cannabis edibles and vaping products; 2) to examine differences in levels of support based on cannabis consumption; and 3) to examine differences in levels of support among cannabis consumers who report sourcing products from 'legal' versus 'illegal' retail stores.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.420
Threshold uncertainty score0.992

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 studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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 head0.011
GPT teacher head0.267
Teacher spread0.256 · 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