Contextualised shared leadership: A Canadian case study
Bibliographic record
Abstract
This account summarises the findings from one component of a six-stage study conducted in multiple international sites. Following a series of interviews, a 10-month case study was conducted in a K-12 private school in western Canada. Initial interviews demonstrated how the school manifested shared leadership, clear pedagogical goals, student success, and strong community support. Members of the school agreed to have two university researchers conduct further interviews, observe school-wide, grade level and subject area meetings. Two school-based researchers collaborated to identify key members of the school community, flag salient planning and celebratory events, and participated in ongoing debriefing meetings with the university researchers. All four researchers engaged in data analysis and reporting. The research team identified four themes. First, the teacher work theme included positivity, shared expectations for professionalism, and rigour. Second, communication included unique internal and external communication strategies. Third, there was a learning culture that utilised unconventional information sources. A fourth theme was operational support. Results highlighted the holistic nature of teacher leadership and suggested that teacher leadership is a complex, sophisticated state of being. Results challenge school governance stereotypes and invite educators to work with a sense of vocation and mission.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.052 | 0.014 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".