Cutback Management in the United Kingdom: Challenges of Fiscal Consolidation for the Administrative System*
Bibliographic record
Abstract
This article reviews the administrative implications of the fiscal gap that has opened up in all OECD countries as a result of the financial crisis. It outlines the pressures for fiscal consolidation, which will lead to deep and prolonged real cuts in public spending. The article examines the political debate in the United Kingdom and stresses the exceptional difficulties facing all administrative systems over what might be a decade of spending restraint. Accordingly, it anticipates an emphasis on cutback management as last seen in the United Kingdom in the 1980s, and reflects on the successful Canadian experience. Three hypotheses are advanced: failure to control spending; success based on the New Public Management; and the need to adapt government capabilities to manage cutbacks. Implementing large real cuts in the face of political and administrative pressures for budget maximization will require extraordinary political determination. Intelligent and constructive definition and implementation of spending priorities will require a reconfiguration of administrative systems, which may amount to a new paradigm.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".