Interrupted time series analysis of Canadian legal cannabis sales during the <scp>COVID</scp>‐19 pandemic
Bibliographic record
Abstract
INTRODUCTION: There were repeated reports of increased cannabis sales, use and health impacts in Canada during the COVID-19 pandemic. However, it was unclear whether the increases were due to pandemic effects or industry expansion. METHODS: We performed interrupted time series regressions of monthly per capita legal cannabis sales from March 2019 to February 2021, first with national averages, then with provincial/territorial data after adjusting for store density. We considered two interruption alternatives: January 2020, when product variety increased; and March 2020, when pandemic restrictions began. RESULTS: = 69.6% of within-jurisdiction variation: baseline monthly per capita sales growth averaged $0.21 (95% confidence interval [CI] 0.15, 0.26), sales immediately dropped in January by $1.02 (95% CI -1.67, -0.37), and monthly growth thereafter increased by $0.16 (95% CI 0.06, 0.25). With the March interruption, the regression instead explained 68.7% of variation: baseline sales growth averaged $0.14 (95% CI 0.06, 0.22), there was no immediate drop and growth thereafter increased by $0.22 per month (95% CI 0.08, 0.35). DISCUSSION AND CONCLUSIONS: Increasing cannabis sales during the pandemic was consistent with pre-existing trends and increasing store numbers. The extra increased growth was more aligned with January's new product arrivals than with March's pandemic measures, though the latter cannot be ruled out. We found little evidence of pandemic impacts on Canada's aggregate legal cannabis sales. We therefore caution against attributing increased population-level cannabis use or health impacts primarily to the pandemic.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".