Summer Reading Program with Benefits for At-Risk Children: Results from a Freedom School Program
Bibliographic record
Abstract
Low-income and racial/ethnic minority children are at increased risk of experiencing summer reading loss or declined reading levels due to time away from school. The purpose of this study was to determine whether a 6-week summer reading program would help children maintain or improve reading levels. Four-hundred-fourteen African American and Hispanic children ranging from Kindergarten to 8th grade were assessed before (Time 1) and one-week prior to the end of the program (Time 2) to evaluate changes in Independent and Frustration reading levels. Outcome scores (Independent and Frustration) significantly improved from Time 1 to Time 2, t (415) = 11.62, p < .001 and t (415) = 14.99, p < .001, respectively. Time had a significant effect on both Independent and Frustration score differences (F (1, 415) = 135.09, p < .001 and F (1, 415) = 224.60, p < .001, respectively). A significant time by child level interaction in Independent difference scores was also observed F (1, 410) = 8.21, p < .01, with children in higher levels showing more improvement. There was also a significant time by grade repeat interaction in Frustration difference scores, F (1, 390) = 7.60, p <.01; children with a history of grade repetition showed significant improvement compared to those who had not. Results suggest that this brief summer reading program helped children improve over time, with improvement most notable in children in higher grade levels and those most vulnerable (i.e., grade repetition).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".