Bibliographic record
Abstract
BACKGROUND: Cannabis use has been linked to impaired driving and fatal accidents. Prior evidence suggests the potential for population-wide effects of the annual cannabis celebration on April 20th ('4/20'), but evidence to date is limited. METHODS: We used data from the Fatal Analysis Reporting System for the years 1975-2016 to estimate the impact of '4/20' on drivers involved in fatal traffic crashes occurring between 16:20 and 23:59 hours in the USA. We compared the effects of 4/20 with those for other major holidays, and evaluated whether the impact of '4/20' had changed in recent years. RESULTS: Between 1992 and 2016, '4/20' was associated with an increase in the number of drivers involved in fatal crashes (IRR 1.12, 95% CI 0.97 to 1.28) relative to control days 1 week before and after, but not when compared with control days 1 and 2 weeks before and after (IRR 1.05, 95% CI 0.92 to 1.28) or all other days of the year (IRR 0.98, 95% CI 0.88 to 1.10). Across all years we found little evidence to distinguish excess drivers involved in fatal crashes on 4/20 from routine daily variations. CONCLUSIONS: There is little evidence to suggest population-wide effects of the annual cannabis holiday on the number of drivers involved in fatal traffic crashes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".