Editorials Health in all policies—from what to how
Bibliographic record
Abstract
Already the Ottawa conference for health promotion in 1986pointed out the importance of environment for our health.1 ‘Make the healthy choice the easy one ’ was the famous slogan. But actually much earlier, in the 1800s, Rudolf Virchow emphasized the role of social conditions for public health. Hygienic improvements in environments and social conditions were seen as important measures for controlling the infectious disease epidemics of those times. With the emergence of chronic, non-communicable diseases as major public health problems, early response was clinical treatments. With the identification of their behavioural risk factors, public health work started to pay attention to prevention and to health education of people. But the Ottawa Charter argued that health education alone is insufficient. The role of the social and physical environments was again emphasized for disease prevention and health promotion. The North Karelia Project in Finland and
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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 | 0.007 | 0.039 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.014 | 0.022 |
| Insufficient payload (model declined to judge) | 0.038 | 0.018 |
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".