Framing leadership: Contributions and impediments to educational change
Bibliographic record
Abstract
In 1995, the International Centre for Educational Change and the Peel District Board of Education in Ontario, Canada initiated the Change Frames project to assist four secondary schools to build and sustain their ‘capacity’ to deal with the changing educational environment in Ontario. The Change Frames strategy required each school to analyse its unique context using each of seven frames – purpose, emotions, politics, structure, culture, learning and leadership. This article reviews the project through the ‘leadership’ lens. In particular, we study the leadership of the principals in the Change Frames schools over a three-year period that involved dramatic government-mandated changes to secondary education in Ontario. The article reports on interviews conducted with the four project school principals, a sample of staff members in 1997 and 1998, and focus group interviews conducted with staff members in each school in 1999. The analysis revealed that the project had been both helpful and problematic in all schools, that there were particular barriers to using some of the ideas, but that a great deal of learning about change had taken place through experience and reflection. Perhaps more significantly, the analysis has enabled the authors to suggest some tentative learnings about the relationships of leadership and change during turbulent times.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.054 | 0.103 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.023 | 0.027 |
| Scholarly communication | 0.017 | 0.007 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.004 | 0.007 |
| 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".