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Record W4396801527 · doi:10.1080/09687637.2024.2346655

Cannabis harm reduction: perspectives of women who use and allied social and health-care providers

2024· article· en· W4396801527 on OpenAlexafffundabout
Joseph Janes, Stephanie Baker, Tina Bankovic, J. Abundo, Andrew Smith, Stephen Ellenbogen

Bibliographic record

VenueDrugs Education Prevention and Policy · 2024
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsMemorial University of Newfoundland
FundersCanadian Institutes of Health Research
KeywordsHarm reductionCannabisReduction (mathematics)HarmHealth careMedicinePsychiatryPsychologyNursingSocial psychologyPolitical sciencePublic health

Abstract

fetched live from OpenAlex

Background Despite the legalization of cannabis use in Canada in 2018, there remains little research on cannabis harm reduction, particularly for women. Scholarship and public health guidelines tend to focus on the risks of use, emphasizing abstinence rather than harm reduction. Additionally, harm-reduction research and guidelines often lack the perspectives of women who use cannabis and allied social and health-care professionals.Methods This community-based participatory research mixed method study explores the perspectives of women who use cannabis and service providers on the Canadian Lower Risk Cannabis Use Guidelines (LRCUG) and a synthesis of scholarship from 2015 to 2020. The research synthesis and the LRCUG were presented for review by participants in two focus groups (n = 11) and respondents to an online survey (n = 19).Results Participants described public health guidelines as judgmental in tone, ineffective in conveying useful information, and foregrounding abstinence. Participants also identified shortfalls in the research presented, which did not attend to the social context of cannabis use and cannabinoids’ possible benefits alongside risks.Conclusion Participants’ responses affirm that future LRCUGs should focus on informative rather than prescriptive content with meaningful inclusion of people who use cannabis and service professionals as co-creators of knowledge for safer use.

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.366
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.390
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 designQualitative
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

Citations1
Published2024
Admission routes3
Has abstractyes

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