1 Educational Leadership and Management: some consequences
Bibliographic record
Abstract
“An ‘officer elite ’ of headteachers is needed to regain control over our violence-wracked schools... a Sandhurst-type establishment would single out an officer class to run Britain’s schools” (Financial Times, reporting calls from Peter Clark, emergency head of the Ridings School, Halifax for better educational leadership, 17 Oct 1998) A central feature of modern public services has been the displacement of professional judgements by management action. This has been one of the least successful aspects of the transformation and, in the case of universities, materially disturbs the capacity for inventive and dissentful inquiry. The losses to efficiency and quality may take some time to come through but it is quite clear that the employment practices of a university, the way it treats its staff, have a quantifiable impact on its reputation and therefore on its effectiveness. Well-nurtured staff respond well in organisations which depend for their vitality on a commitment to public service values. Brutalised and unfairly treated professional staff simply walk away; those who cannot find other sources of comfort.”
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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.019 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".