Teachers leading and changing: case studies of teacher leadership in large-scale reform
Bibliographic record
Abstract
This is a qualitative inquiry about teacher leadership. Based on data from interviews with 60 participants, it investigates barriers and supports influencing the role of teacher leader within a large-scale reform initiative in one Canadian school district. This multiple case study and cross-case analysis explores the conditions impacting on five school-based leadership teams working to improve practice within the Assessment for Learning project in Edmonton Catholic Schools. Project emphasis is on building leadership capacity toward the development of professional communities, using assessment literacy as a curricular focus and vehicle for reform. The conceptual framework for this study centers on theories of change, professional development, and previous research on teacher leadership. An individual case study representing a withincase analysis of conditions affecting teacher leadership is presented for each of five schools, to preserve the integrity and unique qualities of each site. Case studies relate the experiences of the schools and their leadership teams, highlighting supports and barriers to teacher leadership as perceived by the participants. The five cases provide the foundation for a cross-case analysis of conditions that may influence teachers taking the responsibility to work as leaders in school improvement. Conditions found to positively affect teacher leadership include district coherence, commitment, and advocacy as well as administrative support; access to external expertise; knowledge of change and quality professional development; feelings of responsibility and high expectations for colleagues' learning; and, a clear role definition as change agents committed to shared goals of reculturing and the development of professional learning communities.
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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 | 0.013 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".