Assessing the capacity for public value creation within leadership theories: Raising the argument
Bibliographic record
Abstract
Abstract In recent years, public administration has been targeted by multiple reform efforts. In multiple instances, such initiatives have been ideologically couched in public-choice perspectives and entrenched beliefs that government is the problem. One unavoidable consequence of this continued bout of criticism is the fact that government currently has a noticeably decreased capacity of boosting creation of public value. Within this context, there certainly is an important need for approaches that would counterbalance the loss of public value induced by market fundamentalism. This article suggests that leadership, as a concept of theory and practice, due to its partial immunity to the private-public dichotomy, can provide a pragmatic avenue for nurturing public interest and public value within the devolution of governance, a declining trust in government and a diminished governmental capacity to propagate the creation of public value. While this article critically examines and assesses the capacity of different leadership perspectives in terms of creating and maximizing public value, its primary scope is not the provision of definite answers but rather the instigation of a much necessary discussion.
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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 | 0.050 | 0.149 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.042 |
| Scholarly communication | 0.017 | 0.023 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".