Child Care Services, Socioeconomic Inequalities, and Academic Performance
Bibliographic record
Abstract
OBJECTIVE: To determine if child-care services (CCS) at a population level can reduce social inequalities in academic performance until early adolescence. METHODS: A 12-year population-based prospective cohort study of families with a newborn (n = 1269). Two CCS variables were estimated: "intensity" (low, moderate, and high number of hours) and "center-based CCS type" (early onset, late onset, and never exposed to center-based CCS). RESULTS: Children from low socioeconomic status (SES) families who received high-intensity CCS (any type), compared with those who received low-intensity CCS, had significantly better reading (standardized effect size [ES] = 0.37), writing (ES = 0.37), and mathematics (ES = 0.46) scores. Children from low-SES families who received center-based CCS, compared with those who never attended center care, had significantly better reading (ESearly onset = 0.68; ESlate onset = 0.37), writing (ESearly onset = 0.79), and mathematics (ESearly onset = 0.66; ESlate onset = 0.39) scores. Furthermore, early participation in center-based CCS eliminated the differences between children of low and adequate SES on all 3 examinations (ES = -0.01, 0.13, and -0.02 for reading, writing, and mathematics, respectively). These results were obtained while controlling for a wide range of child and family variables from birth to school entry. CONCLUSIONS: Child care services (any type) can reduce the social inequalities in academic performance up to early adolescence, while early participation in center-based CCS can eliminate this inequality. CCS use, especially early participation in center-based CCS, should be strongly encouraged for children growing up in a low-SES family.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".