Facilitators and barriers to the regulation of medical cannabis: a scoping review of the peer-reviewed literature
Bibliographic record
Abstract
BACKGROUND: In recent decades, several political, legislative, judicial, consumer, and commercial processes around the world have advanced legalization efforts for the use of medical cannabis (MC). As the use of MC evolves through legislative reform, with an increase in public acceptance and therapeutic potential, a need exists to further investigate the facilitators and barriers to MC regulation. METHODS: A scoping review was conducted to identify the facilitators and barriers associated with the implementation of MC regulations. MEDLINE, EMBASE, AMED and PsycINFO databases were systematically searched; no restrictions were placed on geographic location/jurisdiction. Eligible articles included those that evaluated the MC regulatory framework of one or more countries. RESULTS: Twenty-two articles were deemed eligible and included in this review. Themes identified include: (1) effects of conflicts, mindset, and ideology of state population, (2) the use of comparisons to analyze MC regulation, and (3) the need for more knowledge, advice, and empirical/clinical evidence to inform future MC policies. CONCLUSION: Policymakers should be aware of facilitators to the MC regulation implementation process, such as the influence of state and federal congruence, increased transparency, and the incorporation of stakeholder concerns, in order to effectively respond to a growing societal acceptance of MC and its use among patients. Given a comprehensive understanding of these influential factors, policymakers may be better equipped to meet the consumer and commercial demands of a rapidly evolving MC regulatory environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".