Evaluation of the Leveled Literacy Intervention: Year 1
Bibliographic record
Abstract
Providing early interventions for struggling readers is critical for their future academic success. Studies have suggested that many children who fail to read well in their early school years continue as poor readers and writers in later grades (Juel, 1988). Students who are poor early readers are twice as likely to drop out of school when they reach high school (Kerschner & Connolly, 1991). While the need for early attention to reading and comprehension skills is well documented, traditional approaches have often been either ineffective or detrimental to students (Shepard & Smith, 1989; McGill-Franzen & Allington, 1993). However, there is some evidence that through quality early intervention programs, students ’ beginning reading difficulties can be prevented from becoming long-term reading deficiencies (Goldenberg, 1994; Hiebert & Taylor, 1994; Reynolds, 1991). In January 2006, the Center for Reading Recovery and Literacy Collaborative (CRR) received approval to conduct training for the Leveled Literacy Intervention program (LLI) in a large, urban district in the northeastern United States. Due to the number of participants in the training program, CRR provided the eight session training course on-site in the district over three meeting periods: February 27-March 1; March 14-16; and April 24-25. Due to the approval
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".