Developing effective policy and practice for health promotion in Scotland
Bibliographic record
Abstract
Scotland has recently embarked on a new phase of policy and infrastructure development for improving population health and reducing health inequalities that broadly conforms to the Ottawa Charter and WHO's strategic framework for the prevention and control of non-communicable diseases. The new phase is characterised by an integrated, cross-government approach to improving health with strengthened political and Scottish Executive leadership and investment since devolution. A comprehensive policy framework for improving young people's health and reducing inequalities has been developed across education, health, environment and social justice. It builds on an earlier phase of relative stability and continuity in the health promotion infrastructure with policy focused on CVD and cancer prevention and tackling the behavioural risk factors (smoking, alcohol, diet, physical activity) as well as sexual health and mental health and wellbeing. These national strategies are currently being implemented across Scotland. They combine promotion, prevention, treatment and protection goals and target both population-level and high-risk groups. Crosscutting government objectives and headline targets for addressing poverty, disadvantage and health inequalities now supplement the NHS health improvement targets on smoking, alcohol, physical activity, teenage pregnancy and child immunization. Within the health service, prevention efforts are largely concerned with primary care development (anticipatory care) and health system reform to maximize their impact on reducing health inequalities. Efforts to tackle the social determinants of health and reduce inequalities in health outcomes are beginning to be connected and mainstreamed across local government with Community Planning Partnerships as the main vehicle. National level mechanisms for integrated funding, planning and performance reporting to deliver shared priority outcomes have yet to be developed. The development of health improvement strategies has been founded upon a rich source of population health data to monitor changes and improvements, epidemiological studies and evaluation work. The key issues have been to find ways of intervening to accelerate the rate of improvement and to stem the growing health inequalities. A further challenge is to ensure that the lessons from reviews and evaluations of past programmes and strategies are not lost, but help to guide improvements in the complex delivery system and to inform future policy direction. Within the health service, prevention efforts are largely concerned with primary care development and health system reform. Efforts to reduce inequalities in health outcomes are beginning to be connected and mainstreamed across local government.
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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 | 0.106 | 0.113 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.010 | 0.015 |
| Scholarly communication | 0.020 | 0.012 |
| Open science | 0.006 | 0.025 |
| Research integrity | 0.017 | 0.014 |
| Insufficient payload (model declined to judge) | 0.017 | 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".