Bibliographic record
Abstract
The application of the philosophy for health promotion of the Ottawa Charter, led to the creation of the concept of „healthy settings“ related to people’s lives. They are based on the settings approach, according which health is created as a result of the dynamic interaction between personal, environmental and organizational factors. The aim of this article is to present to Bulgarian readers basic concepts and principles related to health promotion in a particular setting, as well as more widely established settings and new opportunities for health promotion, based on the principle of supportive environments, initiated by the Ottawa Charter philosophy. Methods: a search in Pubmed and Google scholar with keywords: healthy settings, healthy cities, schools, universities, hospitals, prisons for health promotion, published between 1986 - 2021; review of the lists of literature sources of the selected publications. The review includes: beginning, initiators, goals, scope, achievements and some difficulties of the application of the idea of a supportive environments in the discussed healthy settings. Conclusions: The presented healthy settings are initiated and continuously supported by the WHO. Some of the established healthy settings are evolving and some of the health promoting networks have been proven effective for over three decades. Modern and varied activities in people’s lives challenge the concept of “healthy settings”and put on the agenda the need to discuss updating the Ottawa Charter, 1986.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".