Early Education and Care Program Quality and Children's Well-being: a Meta-Analysis and Systematic Review of the Early Childhood Environment Rating Scale
Bibliographic record
Abstract
The Early Childhood Environment Rating Scale (-Revised) (ECERS/ECERS-R) is the most widely used assessment of global classroom quality in Early Childhood Education and Care programs. Despite prevalent use of the ECERS/ECERS-R in research and applied settings, its impact on child outcomes have not been systematically reviewed. The objective of this study was to evaluate the association between the ECERS/ECERS-R and children’s well-being. Searches of Medline, PsycINFO, ERIC, websites of large datasets and reference sections of all retrieved articles were conducted up to January 2013. Eligible studies provided a statistical link between the ECERS/ECERS-R and child outcomes. Sixty-three empirical studies met our inclusion criteria. All studies were included in the systematic review and 23 could be meta-analyzed. Associations between ECERS/ECERS-R total and factor scores and children’s cognitive, language, math, and social-emotional outcomes are evident but weak. Greater consistency in study methodology is critical in this area of research.
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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 | 0.019 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.029 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".