School Reopening And COVID-19 In The Community: Evidence From A Natural Experiment In Ontario, Canada
Bibliographic record
Abstract
In December 2020, Ontario, Canada, entered a provincewide shutdown to mitigate COVID-19 transmission. A regionalized approach was taken to reopen schools throughout early 2021 without any other opening of the economy, offering a unique natural experiment to estimate the impact of school reopening on community transmission. Estimated increases of 0.07, 0.08, 0.07, and 0.13 percentage points in community COVID-19 case growth rates occurred 11-15, 16-20, 21-25, and 26-30 days, respectively, after schools reopened. Although small, these changes were particularly evident among children younger than age fourteen, increased over time, and were greater when lag periods were considered, which points to a likely causal effect between in-person classes and a small increase in transmission. These findings suggest that although additional COVID-19 cases are to be expected after the reopening of schools, these risks may be manageable with sufficient, layered mitigation policies.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".