Breakfast with colleagues: virtual action leadership education in northern Canada
Bibliographic record
Abstract
Purpose We report on a virtual participatory action research project team conducted with educators and educational leaders in a northern Canadian school division. This leadership education project was co-constructed between the superintendent of the school district and our seminar research team at the University of New Brunswick. Design/methodology/approach A virtual learning platform embedded within a constructivist paradigm was selected to deliver the seminars since a distance of 4,000 kilometers separated the research/project team and the leadership education participants. The two-year project consisted of six leadership education seminars with each one taking place on a scheduled Saturday morning. Findings Initial data was collected through the world café activity and analyzed through a constant/comparative method. Findings revealed five thematic social realities that the leadership participants were confronting in their district. The themes are (1) Lack of human resources, (2) Increasing professional dialogue and development, (3) Structures impacting teaching and learning, (4) Community change and (5) Mental wellbeing. Practical implications Research-based virtually delivered leadership collaborative projects can be strategically planned and implemented widely across the world and bring university and public school educators, school leaders, and district superintendents together at low cost to both groups. Virtual leadership education projects impact education positively and foster leadership growth inside the school districts, which is critical for remote Canadian school districts. Originality/value This two-year project combined professional learning, leadership education, and research. The findings are valuable because, in year 2, the research team and the leadership participants worked together to create educational leadership strategies to address their challenges.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.041 | 0.008 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".