Between a rock and a hard place: Comparing arms’ length bodies for public involvement in healthcare across the UK
Bibliographic record
Abstract
Arms' length bodies are often seen as a tool of technocratic governance, designed to insulate decision-making from the politicizing pressures of populist influence. This article examines a subset of arms' length bodies in the UK which challenge this convention: agencies which exist to 'champion' the voice of patients and the public in the four NHS systems (England, Northern Ireland, Scotland and Wales). We compare the functions of these agencies on paper and through qualitative interviews in each system which focused on public involvement in major service change (such as closing hospitals). We found that agencies in all four systems had struggled to demonstrate their legitimacy, squeezed between the demands of the elected Governments they answer to, the NHS organisations they are meant to support and challenge, and the publics whose voices they are meant to amplify. We argue that the evolving solutions found in each system demonstrate a foundational tension between locally-legitimate actors and nationally-capable political savvy.
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 | 0.020 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".