The development and testing of a school improvement model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This multimethod study generated and tested a "best evidence" model of school improvement processes (SIP) capable of improving student achievement. Initially developed through the review of a comprehensive body of previous empirical research, the model was further refined through a 2, 5-year longitudinal study in 10 schools. A quantitative test of this refined model was then conducted using survey evidence from administrators, teachers, parents, and students in 100 elementary schools. The model as a whole explained modest but significant amounts of variation in student achievement across schools. School leadership and SIP implementation processes accounted for the largest proportion of explained variation. Notes 1. Initially sponsored by the Ontario government's Education Improvement Commission (EIC). When EIC closed its doors, the Canadian Education Association assumed responsibility for supervision of the project. 2. These tests are administered by the Educational Quality and Accountability Office (EQAO). 3. These researchers included Patricia Allison, Susan Drake, Dany Laveault, Ronald Wideman, and Glen Zederayko.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.000 | 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 it