Expanded In-School Instructional Time and the Advancement of Health Equity: A Community Guide Systematic Review
Bibliographic record
Abstract
Expanded in-school instructional time (EISIT) may reduce racial/ethnic educational achievement gaps, leading to improved employment, and decreased social and health risks. When targeted to low-income and racial/ethnic minority populations, EISIT may thus promote health equity. Community Guide systematic review methods were used to search for qualified studies (through February 2015, 11 included studies) and summarize evidence of the effectiveness of EISIT on educational outcomes. Compared with schools with no time change, schools with expanded days improved students' test scores by a median of 0.05 standard deviation units (range, 0.0-0.25). Two studies found that schools with expanded day and year improved students' standardized test scores (0.04 and 0.15 standard deviation units). Remaining studies were inconclusive. Given the small effect sizes and a lack of information about the use of added time, there is insufficient evidence to determine the effectiveness of EISIT on academic achievement and thus health equity.
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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 | 0.102 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".