Early (years) reactions: comparative analysis of early childhood policies and programs during the first wave of the COVID-19 pandemic
Bibliographic record
Abstract
BACKGROUND: During the first wave of COVID-19 there was little evidence to guide appropriate child and family programs and policy supports. METHODS: We compared policies and programs implemented to support early child health and well-being during the first wave of COVID-19 in Australia, Canada, the Netherlands, Singapore, the UK, and the USA. Program and policy themes were focused on prenatal care, well-baby visits and immunization schedules, financial supports, domestic violence and housing, childcare supports, child protective services, and food security. RESULTS: Significant heterogeneity in implementation of OECD-recommended policy responses was found with all of the included countries implementing some of these policies, but no country implementing supports in all of the potential areas. CONCLUSIONS: This analysis gives insight into initial government reactions to support children and families, and opportunities for governments to implement further supportive programs and policies during the current pandemic and future emergencies.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 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".