The Relative Contributions of Center Demographic, Director, Parental, Social, Environmental, and Policy Factors to Changes in Outdoor Play in Childcare Centers During the COVID-19 Pandemic
Bibliographic record
Abstract
BACKGROUND: The primary objective of this study was to investigate the relative contributions of factors from multiple social-ecological levels in explaining outdoor play changes in childcare centers during the COVID-19 pandemic. METHODS: In Alberta, Canada, licensed childcare center directors (n = 160) completed an online questionnaire. For outcomes, changes in the frequency and duration of outdoor play in childcare centers during COVID-19 compared to before COVID-19 were measured. For exposures, center demographic, director, parental, social, environmental, and policy-level factors were measured. Hierarchical regression analyses were conducted separately for winter (December-March) and nonwinter months (April-November). RESULTS: In most instances, factors at each social-ecological level explained a statistically significant amount of unique variance in changes in outdoor play in childcare centers during COVID-19. Full models accounted for more than 26% of the variance in the outcomes. Changes in parental interest in outdoor play was the most consistent correlate of changes in the frequency and duration of outdoor play in both winter and nonwinter months during COVID-19. In terms of changes in the duration of outdoor play, social support from the provincial government, health authority, and licensing, and changes in the number of play areas in licensed outdoor play spaces were also consistent correlates in both winter and nonwinter months during COVID-19. CONCLUSIONS: Factors from multiple social-ecological levels uniquely contributed to changes in outdoor play in childcare centers during the COVID-19 pandemic. Findings can help inform interventions and public health initiatives related to outdoor play in childcare centers during and after the ongoing pandemic.
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 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".