Head Start’s impact is contingent on alternative type of care in comparison group.
Bibliographic record
Abstract
Using data (n = 3,790 with 2,119 in the 3-year-old cohort and 1,671 in the 4-year-old cohort) from 353 Head Start centers in the Head Start Impact Study, the only large-scale randomized experiment in Head Start history, this article examined the impact of Head Start on children's cognitive and parent-reported social-behavioral outcomes through first grade contingent on the child care arrangements used by children who were randomly assigned to the control group (i.e., parental care, relative/non-relative care, another Head Start program, or other center-based care). A principal score matching approach was adopted to identify children assigned to Head Start who were similar to children in the control group with a specific care arrangement. Overall, the results showed that the effects of Head Start varied substantially contingent on the alternative child care arrangements. Compared with children in parental care and relative/non-relative care, Head Start participants generally had better cognitive and parent-reported behavioral development, with some benefits of Head Start persisting through first grade; in contrast, few differences were found between Head Start and other center-based care. The results have implications regarding the children for whom Head Start is most beneficial as well as how well Head Start compares with other center-based programs.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".