Creating Turn Around Schools: The Effects of Project REACH on Students, Teachers, Principals and Support Staff 1 Final Report to the Ontario Principals Council
Bibliographic record
Abstract
resources, allocated at the discretion of the principal, to improve student achievement in schools serving disadvantaged student populations. In August 2004 the Ontario Principals Council provided a research grant to address the following questions: 1. How have principals used Project REACH resources? 2. What are the outcomes of Project REACH for students, teachers, principals/viceprincipals and support staff? 3. What factors, particularly leadership factors, contribute to, or inhibit, success in Project REACH? In this report we will first describe the background to the program and then address each of these research questions in turn, giving the greatest attention to the last, the role of principals in the change. The final section is an interpretation of the results in the light of research on school improvement. Background to the Program In the last decade school change theory has moved in three directions. First, research (e.g., Stringfield & Yakimowski-Srebnick, 2005) has demonstrated that although measurement of student achievement has an important role to play in stimulating improvement at the school and district levels, measurement alone is insufficient to improve teaching and learning. The problem is that schools with persistently low levels of achievement lack the internal capacity to create the conditions that lead to successful change. Improvement requires an infusion of resources, as well as accountability mechanisms: in Fullan’s (2001) terms, it is the combination of pressure and support that leads to change. Second, is the finding that maintaining an effective balance between pressure and support, between bottom-up and top-down improvement efforts, between inward and outward directives, requires knowledgeable principals employing a braod array of technical and interpersonal skills. "Leadership is to this decade what standards were to the 1990s " (Fullan, 2005, p. ix). Third, the aims of school change have broadened. There is a
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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 | 0.009 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".