Current state of public sector performance management in seven selected countries
Bibliographic record
Abstract
Purpose This paper seeks to extend the analysis of performance management regimes by Bouckaert and Halligan to other countries in order to contribute to the developing theory of forms and challenges in public sector performance management. Design/methodology/approach The state of performance management and the context in which it has evolved is assessed in seven different countries using dimensions drawn from Bouckaert and Halligan's work along with elements from earlier work by Pollitt and Bouckaert. These are summarized in a table and comparisons made to generate additional insights into the factors that influence the shape and speed of public management evolution. Findings The paper finds that the Bouckaert and Halligan framework for analyzing public sector performance management is useful, albeit with some modifications. Specifically, it finds that administrative culture is a key factor influencing the speed of reform and that the attitude of elites (politicians and civil servants, in most cases) is also a vital piece of the puzzle that was not included in Bouckaert and Halligan, but did appear in the earlier framework of Pollitt and Bouckaert. It also finds evidence that economic and political crises occurring together accelerate the introduction of integrated performance management systems, but that trust in government does not appear to be a significant factor. Finally, the paper observes that, absent political crisis/commitment, governments will prioritise “external” performance measures such as customer service, participation and transparency objectives over “internal” performance measures such as financial, staff management and whole of government reporting. Originality/value The countries studied provide a rare insight into lesser‐known performance management regimes and the use of the Bouckaert and Halligan framework allows for comparisons to earlier (and future) research. The findings will be of interest to scholars in public administration reform and performance management.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".