Governance Must Dive into Organizations to Make a Real Difference; Comment on 'Governance, Government, and the Search for New Provider Models'
Bibliographic record
Abstract
In their 2016 article, Saltman and Duran provide a thoughtful examination of the governance challenges involved in different care delivery models adopted in primary care and hospitals in two European countries. This commentary examines the limited potential of structural changes to achieve real reform and considers that, unless governance arrangements actually succeed in penetrating organizations, they are unlikely to improve care. It proposes three sets of levers influenced by governance that have potential to influence what happens at the point of care: harnessing the autonomy and expertise of professionals at a collective level to work towards better safety and quality; creating enabling contexts for cross-fertilization of clinical and organizational expertise, notably through teamwork; and patient and public engagement to achieve greater agreement on improvement priorities and overcome provider/manager tensions. Good governance provides guidance at a distance but also goes deep enough to influence clinical habits.
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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 | 0.011 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.018 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.067 | 0.043 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".