Leadership practices of middle school principals that promote collective teacher efficacy
Bibliographic record
Abstract
This case study investigates the leadership practices of middle school principals in schools with high Collective Teacher Efficacy (CTE). The research aims to understand how specific leadership actions contribute to the enabling conditions that foster CTE. Using a qualitative approach, the study gathered data through semi-structured interviews with three middle school principals and focus groups with teachers from their schools in a large urban district in Alberta, Canada. The findings reveal four central themes: building and distributing leadership capacity, engaging the school community, driving school improvement, and the significance of principal deportment. Principals prioritized building teacher capacity through strategic alignment with the School Development Plan (SDP) and by fostering collaboration within Professional Learning Communities. They engaged in distributed leadership practices, creating environments where teachers felt empowered and supported. In terms of school improvement, principals used the SDP as a tool to guide instructional enhancements and align district mandates with school priorities. Notably, principal deportment emerged as a critical factor. The deportment of principals—how they carried themselves and embodied their leadership roles—played a pivotal role in building trust and enhancing the overall school climate. Principal deportment was not only crucial for fostering a positive school environment but is also integral to the creation and sustainability of CTE, demonstrating that effective leadership practices can intentionally cultivate this essential construct.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".