Exploring Graduate Programming in Alberta, Canada, Through the Lens of Teacher Leadership
Bibliographic record
Abstract
This chapter explores the availability of leadership and professional development programming in Alberta, Canada, overtly designed to promote teacher leadership. This research focused on identifying the alignment of Alberta universities’ graduate programmes with key dimensions of a range of teacher leadership literature. The theoretical framework included instructional and transformational leadership theories and teacher leadership research. A content analysis of programme information, course outlines, course descriptions, and course materials to identify emergent themes deemed important for educators. Analysis revealed five major findings: (1) over the five-year data capture, available graduate programmes in leadership and varied specialisation themes have doubled; (2) themes reflect contemporary school contexts and teaching challenges; (3) shorter programme duration and the gaining of two specialisations in one master’s programme has become more popular; (4) leadership programmes remain popular and specifically promote teacher leadership values and attributes; and (5) the increase in programmes has implications for academic workload and the sustainability of programmes, given the reduction of government funding to the university sector. The demand for graduate programmes is a reasonable indicator that teacher leadership in terms of teachers’ sense of heightened professionalism and engagement in professional development is alive and well in Alberta.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".