Bibliographic record
Abstract
The Coalition had set out clearly its strategic objective. By restricting the claims of the public sector on the nation’s resources the intention was to restore incentives, encourage efficiency and to create a climate in which commerce and industry would flourish, laying a secure basis for investment, productivity and increased employment (cited in Fry, 2008: 71). This prospectus is not taken from the Coalition’s Programme for Government in 2010. It is taken from the Queen’s Speech of 15 May 1979, announcing the radical intent of the first Thatcher administration. It reveals an interesting echo of a recurring political problem for British government: an end can be identified and the policy means may be assembled but the outcome is far from assured. In 1979, as the Queen’s Speech made clear, ‘all parts of the United Kingdom’ were to benefit from the new dispensation (ibid.). There was the same expectation after 2010 that by cutting public spending and accelerating ‘the reduction of the structural deficit over the course of a Parliament’, all parts of the United Kingdom would benefit (HM Government, 2010: 15). One crucial difference between 1979 and 2010 was devolution and the Coalition accepted that the Northern Ireland Executive, the Scottish Executive and the Welsh Assembly Government would ‘make their own policy on their devolved issues’ (ibid.: 35). These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.025 | 0.006 |
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".