Bibliographic record
Abstract
While there is debate around the impact of leadership education and development on practice, the general assumption underpinning the debate is that leadership can be taught in some form. This is reected in the number of university leadership centres across the world (e.g. Lancaster, Exeter and INSEAD in Europe; Auckland in New Zealand; and Washington, Northwestern and Pennsylvania in the US). There are also non-university organizations such as the Center for Creative Leadership (US), which has a global reach, and the Asian Leadership Institute (Thailand and Canada) that oer a variety of leadership programmes. Many business schools across the world are re-packaging MBA programmes around global, strategic or executive leadership – as opposed to management. And this is not just the purview of business schools. Kellerman (2013: 136) says that at Harvard University, where she works, ‘virtually every single one of its professional schools boasts the words “leader” or “leadership” in its mission statement’. The Massachusetts Institute of Technology’s Sloan Fellows programme in innovation and global leadership promises a ‘deep reservoir of resources’, ‘expanded skills and capabilities’ and a ‘change-the-world toolkit’,1 which is typical of many top-ranked programmes.
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 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 | 0.000 | 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) | 0.208 | 0.025 |
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; both teacher heads agree on what is shown here.
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".