Current Contexts for Research in Educational Leadership and Management
Bibliographic record
Abstract
Research in education, and in educational leadership and management, has been heavily criticized in the UK for lack of quality and relevance. The criticism has led to a number of initiatives intended to ameliorate the situation, of which this special issue focusing on methods of investigation is a part. The article briefly considers the range of evidence for this critique, both in general and as it relates specifically to the field of education management, and concludes that there is a case to answer and ethical pressure on us to improve. However, some of the purported ‘remedies’ for improvement appear misjudged, and the article argues that the concern about methods is, for the most part, one of these. In summary, a considerable improvement in research could come about simply by us doing more actual research with our existing methods to answer genuine questions, by an increase in appropriate scepticism and by being prepared to put our cherished beliefs and ideas at risk.
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 | 0.236 | 0.228 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.016 | 0.019 |
| Science and technology studies | 0.024 | 0.146 |
| Scholarly communication | 0.076 | 0.061 |
| Open science | 0.008 | 0.025 |
| Research integrity | 0.025 | 0.038 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".