Outsourcing Central Government Services
Bibliographic record
Abstract
Introduction The requirements on central government to liberalise services as part of the implementation of the General Agreement on Trade in Services (GATS) provided an opportunity to distance the civil service from the more difficult and public-facing elements of its roles. Privatising delivery of these services enabled the introduction of performance management and cost-cutting measures that could be blamed on the contractor rather than the government. While the civil service and particularly the Home Office, often called the Ministry of the Interior in other countries, have traditionally had responsibility for police, borders, visas, migration and asylum, this has primarily been focused at a policy level. Until the late 1960s, governments had no particular interest in asylum or immigration policy as most of the post-war immigration to the UK had been from Commonwealth countries including the Caribbean and Indian subcontinent to meet employment shortfalls in UK public services (Timmins, 2001). Other migration between the UK and Commonwealth countries saw trends moving the other way as UK citizens migrated to Australia, New Zealand and South Africa. The pressure on government departments to cut costs through the Rayner Scrutiny Reviews from 1980 onwards and then agencification through the creation of Next Steps Agencies in the late 1980s and early 1990s had generated some institutional change in the structure of the civil service (Gray and Jenkins, 1984; Dowding, 1995). While preparing to meet UK commitments for public service liberalisation through the Government Procurement Agreement (GPA) and anticipated GATS agreements, central government implemented this by prioritising nationalised industries and local government (De Graaf and King, 1995; Parker, 2009). When approaching central government services, those that were public facing, employed more staff and were not regarded as strategic were peripheralised first, in anticipation of competition requirements on the civil service. This enabled a reduction in central department employee headcounts and was expected to reduce the day-to-day management burden of these services, allowing a focus on policy issues (Theakston, 1995). These services were primarily focused on clerical tasks including tax returns, social security and pensions that employed higher numbers of low-paid staff and required most face-toface contact. The use of agencification and then privatisation would allow the reformulation of pay bands that could lead to cost reductions in the front-line delivery services (Dowding, 1995).
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.194 | 0.098 |
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".