Reading First in Florida: Five Years of Improvement
Bibliographic record
Abstract
Five years of reading comprehension data in Florida Reading First schools were analyzed to address questions regarding student improvement, reduction in the achievement gap, efficacy of site visits to schools making no achievement gains, and effects of student mobility on growth in reading comprehension. Participants were 120,000 students (about 30,000 each in grades K–3) in the 318 schools in the first cohort of Florida Reading First from 2003 to 2008. Outcome measures were the reading comprehension scores on the Stanford Achievement Test (SAT-10) and the Florida Comprehensive Assessment Test (FCAT). The percentage of students on grade level (at or above the 40th percentile) increased, and the percentage of students at high risk (below the 20th percentile) decreased over the five years. Racial/ethnic minority, economically disadvantaged, and English language learner groups improved performance as well, but there was no evidence of narrowing the achievement gap. Reduction in risk for students with learning disabilities was noteworthy. Increased support to low-performing schools was associated with improved performance. Finally, there were significant reductions in growth in reading comprehension associated with leaving a Reading First school.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".