Promoting the use of diverse sources of evidence: evaluating progress in the provision of services for people with dementia and their carers
Bibliographic record
Abstract
English This article reports on an innovatory partnership between regulatory bodies and researchers to assess progress in improving NHS, local authority and other services for older people in 10 different parts of England. It discusses how consultation exercises held as part of local inspections that fed into a national review of the National Service Framework for Older People may enlarge the evidence base for planning and service improvement purposes. The results provide an example of the need for greater debate about different sources of evidence in health and social care. There is comparatively little recent UK research-based evidence on what people with dementia and their carers think about the services they receive and policy makers may need to draw on wide-ranging sources of evidence if they are to make necessary service improvements and to develop policy initiatives.
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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 | 0.688 | 0.760 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.023 | 0.015 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.019 | 0.017 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".