Practising educational leading ‘in’ and ‘from’ the middle: a site ontological view of best practice
Bibliographic record
Abstract
In this paper, a site ontological approach to practice seeks to understand how educational development can be accomplished through the practices of ‘middle leaders’ - educators who exercise their leading ‘between’ the principal and the teaching staff. Analysis of two vignettes of leading in extraordinary circumstances untangles the web of interrelationships, conditions and practices that comprise middle leading in schools. The discussion focuses on how middle leaders' practices are enabled and constrained by practice architectures, and how their leading is ecologically arranged with other educational practices present. It is argued that notions of ‘best practice’ are an idealised but erroneous myth that often provokes educational development to be practised in homogenised or pre-packaged ways that do not necessarily serve the needs and interests of schools. We conclude by suggesting that best practice might be better conceptualised as site based practices, uniquely realised in response to local issues and concerns.
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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 | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.011 | 0.114 |
| Scholarly communication | 0.018 | 0.022 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.006 | 0.006 |
| 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".