Bibliographic record
Abstract
Education is a significant portfolio in any provincial or territorial cabinet. The Education Minister makes decisions and works with others to accomplish specific functions that affect individual students and society as a whole. They are widely seen to have a key role in shaping the future, and as such the pressure on them to perform well and succeed is immense. Surprisingly, for such an important position, new appointees often find they are unprepared for all that is expected of them. In this article, the author, a former territorial Education Minister, summarizes his doctoral research into education leadership. Employing interviews with other former education ministers from across the country and the political spectrum, he endeavoured to develop an interpretive understanding of the position through the lens of identity. Four common themes were developed from the stories of the former ministers: changing identity, voicing identity, educating identity, and trusting identity. He concludes by expressing hope that his analysis and research will help us do a better job of preparing people who assume these positions to understand their roles and responsibilities.
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 | 0.032 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.011 | 0.019 |
| Scholarly communication | 0.015 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".