Cannabis donation as a harm reduction strategy: a case study
Bibliographic record
Abstract
BACKGROUND: The United States (US) continues to experience unprecedented rates of overdose mortality and there is increased need to identify effective harm reduction practices. Research from Canada describes cannabis donation through harm reduction agencies as an adjunctive strategy to mitigate the negative consequences of more harmful drugs. This case study describes the operational logistics, feasibility, and potential benefits of a cannabis donation program that was operated through a harm reduction program in rural Michigan. CASE PRESENTATION: We applied a community driven research approach to gather information from harm reduction program staff about the implementation and evolution of cannabis donation efforts in Michigan. We also examined 20-months (September 2021 through May 2023) of administrative data from a cannabis company to compare the sale and donation of cannabis products. Ten cannabis-experienced harm reduction clients received cannabis donations, with clinical staff determining client interest and appropriateness, and providing weekly pick-up or delivery. To expand product availability and sustainability, we examined administrative data from a commercialcannabis company that volunteered to provide donations. This administrative data suggests that while flower products constitute most of the adult and medical sales, edible, oil, and topical products predominated donations. Further, cost analysis suggests that donations represent only 1% of total gross sales and account for much less than the expected yearly donation amount. CONCLUSIONS: Research suggests there is potential to reduce alcohol and drug use related harms of more dangerous substances through substitution with cannabis. This case study is the first to document cannabis donation as a harm reduction practice in the US and suggests potential for sustainability dependent on state laws. Findings from this case study provide a starting point for inquiry into cannabis donation as a harm reduction strategy in the US; future research is needed to fully understand the individual-level outcomes, public health impacts, necessary legal regulations, and best practices for cannabis donation programs through harm reduction organizations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".