Effects of Kindergarten Retention Policy on Children’s Cognitive Growth in Reading and Mathematics
Bibliographic record
Abstract
Grade retention has been controversial for many years, and current calls to end social promotion have lent new urgency to this issue. On the one hand, a policy of retaining in grade those students making slow progress might facilitate instruction by making classrooms more homogeneous academically. On the other hand, grade retention might harm high-risk students by limiting their learning opportunities. Analyzing data from the US Early Childhood Longitudinal Study Kindergarten cohort with the technique of multilevel propensity score stratification, we find no evidence that a policy of grade retention in kindergarten improves average achievement in mathematics or reading. Nor do we find evidence that the policy benefits children who would be promoted under the policy. However, the evidence does suggest that children who are retained learn less than they would have had they instead been promoted. The negative effect of grade retention on those retained has little influence on the overall mean achievement of children attending schools with a retention policy because the fraction of children retained in those schools is quite small. Nevertheless, the effect of retention on the retainees is considerably large.
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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 | 0.009 | 0.035 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".