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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".