Bibliographic record
Abstract
In today’s age of mandated school reforms, it would seem advantageous for principals to share school leadership with teachers. Yet teacher leadership is an area that is still emerging and these skilled professionals may be overlooked and underutilized, to the detriment of school success. This study aims to gain a deeper understanding of the motivating factors behind why environmental teachers choose to take on a leadership role and what conditions hinder or support them in this role. This study, using a sequential explanatory mixed methods design, consists of two phases: a survey completed by Ontario EcoSchools lead teachers, followed by semi-structured interviews. Results show that most teacher leaders are motivated by a personal interest coupled with a desire to instil a deeper understanding of environmental issues and values in their students. Despite their passion, some teacher leaders were unsatisfied or not likely to continue in the role. Results from the Teacher Leadership School Survey indicated they felt their schools were not as supportive of teacher leadership. Even satisfied teachers cited barriers to teacher leadership which included reluctant peers, insufficient active support by the principal and obstructive school structures. Three key areas for consideration emerged: 1) Teacher leaders may lack the skills to navigate resistant school cultures, 2) Principals are key in creating enabling school structures, and 3) Teacher leadership growth requires system-wide change. These insights deepen our understanding of the phenomenon of teacher leaders, so that measures can be implemented to support their professional growth and help foster this essential role in schools.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".