Narratives of Becoming Leaders in Disciplinary and Institutional Contexts
Bibliographic record
Abstract
<JATS1:p>This collection provides theoretically-informed personal narratives of nine emerging and established leaders in learning and teaching in Australia, Brazil, Canada, Trinidad and Tobago, the UK and the USA. The academics’ narratives consider how individuals navigate the disciplinary and institutional context as emergent and established leaders in learning and teaching.</JATS1:p> <JATS1:p>These learning and teaching leadership narratives highlight the commonalities and differences in the struggles that academic leaders encounter within their unique national contexts, and discipline. The journeys of learning and teaching leadership are often fuzzy owing to lack of well-established structures and pathways. This book seeks to contribute to our understanding of the impact of disciplinary and institutional contexts on the practice of these learning and teaching leaders. It captures the subjective experiences of academics at various stages in their career, navigating their individual pathways of learning and teaching leadership within their national context.</JATS1:p>
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".