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Record W4224881455 · doi:10.7565/ssp.v5.6760

Study Protocol: Cannabis in the Closet? Older Persons' Perceptions of Stigma and their Influence on Use and Access to Medicinal Cannabis

2022· article· en· W4224881455 on OpenAlexaff
Sherry Dahlke, Kathleen F. Hunter, Madeline Toubiana, Maya R. Kalogirou, Melissa Scheuerman, Jeffrey I. Butler

Bibliographic record

VenueSocial Science Protocols · 2022
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsYork UniversityMacEwan UniversityUniversity of Alberta
Fundersnot available
KeywordsCannabisStigma (botany)PerceptionQualitative researchEffects of cannabisMedicinePsychiatryHelpfulnessPsychologySocial psychology

Abstract

fetched live from OpenAlex

Background: Cannabis has been used for medicinal purposes for millennia. Stigma associated with cannabis use may influence older persons access to cannabis, information seeking about cannabis, and/or use of cannabis. Scant research has sought to examine the impact of older persons’ perceptions of stigma on the ways they learn about and use medicinal cannabis, with important implications for their health.
 Methods/Design: In this qualitative descriptive study, we will seek older persons’ information needs and challenges accessing cannabis from older persons and professionals who work in the cannabis industry. Using open ended questions, we will survey and interview older persons who use cannabis or are considering using it about their perceptions of stigma, information seeking, choice of cannabis product, and preferred vendor. Professionals who work with cannabis will be interviewed for their experiences with older persons seeking information about and access to cannabis.
 Discussion: Findings will identify what information related to medicinal cannabis use older Canadians most urgently need, shed light on any stigma they fear and/or experience when searching for such information, and inform the development of information products and knowledge mobilization strategies tailored to older Canadians’ knowledge needs.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.206
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.058
GPT teacher head0.434
Teacher spread0.376 · 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.

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

Citations3
Published2022
Admission routes1
Has abstractyes

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