Bibliographic record
Abstract
PURPOSE: The purpose of the paper is to demonstrate how a generic value chain and customer focused system as demonstrated by the Scottish and Irish breast screening programmes can be used to provide a high quality health service. DESIGN/METHODOLOGY/APPROACH: Literature relevant to aligning the entire operating model--the companies' culture, business processes, management systems to serve one value discipline, i.e. customer intimacy, is reviewed and considered in the context of the NHS Scottish Breast Screening Programme in Edinburgh and BreastCheck--the National Breast Screening Programme in Ireland. FINDINGS: This paper demonstrates how an emphasis on customer focus and operational excellence, as used in other service industries, can help to provide a better health service. It uses the Scottish and Irish breast screening programmes as illustrative examples. The paper applies the key requirements in the delivery of a quality service including an understanding of the characteristics of a service industry, the management of discontinuities involved in its delivery and the environment in which it operates. ORIGINALITY/VALUE: System failure is commonly the cause of quality failure in the health system. Breast screening programmes are designed to prevent such a failure. This paper promotes and describes the use of the generic value chain by using the knowledge gained in delivering a mammography-screening programme.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".