Government-mandated warnings on cannabis legally sold for recreational use
Bibliographic record
Abstract
BACKGROUND: Frequent cannabis use can pose risks to health and safety. Multiple governments have legalized the sale of cannabis for recreational use and mandated health and safety warnings for recreational cannabis packages or signs at sales locations. The purposes of this study were to identify common themes across warnings and to compare the actual warnings with those previously recommended by cannabis experts and cannabis users. METHODS: We searched Google and Google Scholar for online lists of governments that allow or will soon allow the sale of cannabis for recreational use. Using the online lists we found, we searched for laws mandating the warnings, using the search terms "mandated warnings for recreational use marijuana" in addition to the name of the jurisdiction under review. We evaluated the content of the warnings and compared them with warnings recommended by cannabis experts and by users of recreational cannabis. RESULTS: Each search led to millions of results. Within the top results of each of the searches there were website links to official legislative websites, databases and documents of the jurisdiction under review. We used these official documents. The search revealed that 11 U.S. states and two countries allow the recreational use of cannabis and that 10 U.S. states and Canada mandate warnings on legally sold recreational cannabis. The mandated warnings can be categorized as focusing on one of nine risks: (1) negative health effects on the user, (2) harm to children or fetuses, (3) risks related to driving or operating machinery, (4) risks of habit formation leading to over-use, (5) risks relating to over-use on a single occasion, especially with regard to edible cannabis, (6) developmental risks for young people, (7) harm caused by secondary smoke, (8) risks of effects lasting several hours, and (9) risks specific to using cannabis topicals. The warnings include no graphic images and no phone number to call for help quitting. CONCLUSIONS: The warnings, as a group, parallel most warnings recommended by cannabis experts and a sample of recreational users of cannabis. The effects of the warnings are unknown, but prior research findings on warnings for cannabis and for other substances suggest potential for positive effects in raising awareness of risks and decreasing the risks. The warnings could be used in public health campaigns. Public health professionals may find it possible through research to help improve the warnings, either in presentation or in content. Cannabis researchers can use the list to identify additional risks suitable for inclusion in mandated warnings.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.002 |
| 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".