Self-reported Impact of the COVID-19 Pandemic on Cannabis Use in Canada and the United States
Bibliographic record
Abstract
The current study examined the self-reported impact of the COVID-19 pandemic on cannabis consumption and behaviors among past 12-month cannabis consumers in Canada and the U.S. across different cannabis laws. Cross-sectional survey data were collected in 2020 from respondents recruited through online commercial panels, aged 16-65, who consumed cannabis in the past 12 months (n = 13,689). Weighted multinomial logistic regression models examined differences between jurisdictions for five outcomes: 1) cannabis consumption; 2) use of product types; 3) use of sources to obtain cannabis; 4) legality of source used; and 5) access to cannabis. Approximately one third of cannabis consumers reported changes to their consumption during the pandemic. Edibles (23% - 31%) and dried flower (21% - 30%) were the two most common products that respondents reported they were "more likely" to use during the pandemic. Most consumers reported "no difference" to changes in sourcing cannabis. Compared to consumers in U.S. recreational states, consumers in U.S. medical (AOR = 1.27, 95% CI: 1.07, 1.50) and illegal states (AOR = 1.22, CI: 1.00,1.48) had higher odds of reporting it was "harder" to access cannabis, and consumers in Canada had lower odds (AOR = 0.73, CI: 0.63,0.84). Future research should examine whether these changes remain after public health restrictions due to the pandemic are removed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".