Developing Public Service Leaders : elite orchestration, change agency, leaderism, and neoliberalization
Bibliographic record
Abstract
Developing Public Service Leaders examines why and how governments and professional associations have mounted major interventions over recent decades to develop senior staff from public service organizations as leaders. A critical explanation is developed of the foundational contribution made by national leadership development interventions in the 2000s to the emergence, proliferation, and normalization of leadership development provision. Drawing on their qualitative research in England, the authors examine the origins, implementation, and direct outcomes of national leadership development interventions for school education, healthcare, and higher education. The diffuse contemporary legacy of these interventions is also explored within the growing international movement to develop public service leaders, comparing interventions in the USA, Canada, Australia, New Zealand, and England. This deeply contextualized critical analysis shows how powerful elite groupings orchestrate leadership development interventions, widely acculturating senior staff as leaders but not necessarily also as change agents for public service reforms. The interventions also offer a source of credentials fostering leadership as an incipient profession that serves the ongoing neoliberalization of public services. Developing Public Service Leaders is a comprehensive and essential read for any researcher, policymaker, or student striving for an in-depth understanding of leadership development as policy, practice, and emergent institution.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".