The Consequences of the Austerity Policies for Public Services in the UK
Bibliographic record
Abstract
This article examines the changing landscape of public service provision in the UK during austerity. Austerity is presented through the notions of retrenchment, decentralisation and shifts in governance. The analysis shows that retrenchment and decentralisation eroded the capacity of public institutions to protect the provision of vital public services. This is revealed through the reduced provision of non-statutory services and the reinforcement of inequalities in service provision. Shifts in governance have led to mixed outcomes in the quality of services. This article also addresses how austerity influenced many of the problems observed in service provision during the COVID-19 pandemic. Vital public services in the UK faced the pandemic with a diminished resource base, heightened inequalities and significant fragmentation in service provision.
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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 | 0.010 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 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".