Incentivizing the Poor Relation: ‘Performance’ and the Pay of Public-Sector ‘Senior Managers’
Bibliographic record
Abstract
This article discusses the principles and practices of pay determination for senior managers in the public sector. A central theme of the article is the analysis of performance-related pay (PRP) in the pattern of pay determination for this group. The discussion of this approach to pay is set in the context of New Public Management (NPM) and the emphasis on installing performance measurement and management as a central element in the ‘reform’ of public-sector services. The exemplary material is drawn from the United Kingdom, as it represents a national case in which NPM techniques have been applied over a quarter of century under successive governments. The article argues that while there are logical connections between PRP and performance measurement and management the practice of pay determination for senior public-sector managers is less coherent than such connections might suggest. The article locates the causes of such incoherence in the complexity of patterns of pay determination for senior public managers and the conceptual and methodological problems inherent in assessing the performance of public-sector services.
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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 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".