Mapping the international knowledge base of educational leadership, administration and management: a topographical perspective
Bibliographic record
Abstract
This study mapped the international knowledge base of educational leadership, administration and management (EdLAM) from a topographical perspective. Altogether 1651 publications from 18 peer-reviewed English journals published between 2007 and 2016 were reviewed. Combining bibliometric and content analyses, the authors identified 55 countries and regions that produced EdLAM publications. About half the publications came from five Anglo-Saxon countries, a quarter from Europe and a quarter from four emerging regions (Asia, the Middle East, Africa and Latin America). In each cluster of countries, key EdLAM research themes were identified and illustrated with reviewed literature. The overall development trends of EdLAM research include the continuous theorisation and empirical investigation of EdLAM, the increasing critical voices against Neoliberalism and the New Public Management in education, the growing awareness of contextualising EdLAM research locally, and the rising value of comparative studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".