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Record W4362589993 · doi:10.1080/13698575.2023.2198558

The “risk object” of cannabis edibles: perspectives from young adults in Canada

2023· article· en· W4362589993 on OpenAlexafffundabout
Charlene Elliott, Matt Ventresca, Emily Truman

Bibliographic record

VenueHealth Risk & Society · 2023
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of Calgary
FundersAlberta Children's Hospital Research InstituteCanada Research Chairs
KeywordsCannabisFocus groupRecreationQualitative researchGovernment (linguistics)PsychologyEnvironmental healthGeographyMedicinePolitical scienceBusinessSociologyPsychiatryMarketingSocial science

Abstract

fetched live from OpenAlex

Young adults are the most prominent users of cannabis in Canada, which was legalised for recreational use in 2018. Edibles are a highly popular form of cannabis delivery for this age group, yet little qualitative research explores young adult perspectives on edibles, including how edibles function socially for them, or are viewed in terms of risk. This study fills this research gap, conducting focus groups with 57 young adults (ages-18–24) in Calgary, Alberta, Canada to explore the ‘risk object’ of cannabis edibles. Findings reveal that delivery mechanism of cannabis – that is, cannabis in food form compared to smoked/inhaled – significantly shifts perceptions of risk by young adults. Edibles were viewed as less risky than smoking cannabis, and participants stated they were more willing to consume edibles than in any other form (and especially in social settings). Risks associated with edibles were primarily short-term/related to over-consumption and were largely mitigated by legalisation. However, participants also emphasised risks for others (including children and inexperienced consumers). Overall, the ‘risk object’ of cannabis edibles shifts depending on the audience considered. Participants described individual consumers as shouldering primary responsibility for managing risks related to cannabis edibles, despite manufacturer and government roles in regulating product quality and protecting vulnerable populations.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.634
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.010
GPT teacher head0.295
Teacher spread0.285 · 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

Citations2
Published2023
Admission routes3
Has abstractyes

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