Unpacking the Childcare and Education Policy Response to the COVID-19 Pandemic: Insights from the Canadian Province of Quebec
Bibliographic record
Abstract
Building from Blum and Dobrotić’s conceptual framework, this paper shows that the decisions to reopen childcare centres and schools in the Canadian province of Quebec in 2020 were influenced by four goals: (1) protecting public health, (2) promoting academic success / fostering early education, (3) addressing social inequalities, and (4) helping parents to reconcile employment and care activities. Although the first three objectives were considered in the sequence of reopening, the government quickly chose to prioritize work-family reconciliation above other objectives. Quebec’s tight sequence of reopening childcare centres and schools is not simply a consequence of evolving research showing lower risks associated with COVID-19 for young children, it also reflects the province’s cultural norms toward mothers’ employment and the high legitimacy of the state in subsidizing childcare.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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".