Strategic management in public administrations: a results-based approach to strategic public management
Bibliographic record
Abstract
As a field of knowledge, strategy has been taught and practised for over half a century. However, there is still a distinct lack of consensus surrounding the effectiveness of strategy in public administrations. This thematic issue of the International Review of Administrative Sciences is devoted to advanced research which claims that in the age of results-based management, public leaders must opt for a process-based approach to strategy. In doing so, the emphasis is put on the complexity of strategic processes that make it possible to support and maintain the institutions that serve the common good and the general interest and that deliver public services using the results of public action. From a process-based point of view, the strategy of public administration then assumes that analysts and public leaders need to be more aware of the specificities of state institutions. In particular, a thorough knowledge of the ways in which public officials interact with the fundamental values, structures, regulatory frameworks and administrative tools of public administrations is necessary.
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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 | 0.070 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.018 | 0.018 |
| Science and technology studies | 0.005 | 0.054 |
| Scholarly communication | 0.040 | 0.025 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".