Towards healthy One Planet cities and communities: planetary health promotion at the local level
Bibliographic record
Abstract
Health promotion has paid a lot of attention to the social determinants of health and to health equity but much less attention to the ecological determinants. Yet the most fundamental determinants of health are the natural systems that make the Earth liveable and are the source of our air, water, food, fuels and materials. Yet they are threatened by the very economic and social development that we have created to meet the social determinants of health. Moreover, the benefits and burdens of that development are inequitably distributed, resulting in both ecological and social injustice. In the past few years the new field of planetary health-'the health of human civilization and the state of the natural systems on which it depends'-has emerged, while WHO has confirmed that 'the source of human health [is] nature'. So arguably the most important task facing health promotion in the 21st century is to turn its attention to planetary health: health promotion workers must become planetary health promoters. Local health promotion in the 21st century needs to incorporate the concept of planetary health promotion and its application in the creation of healthy 'One Planet' communities and must become part of the emerging network of community organizations and individuals working to create sustainable, just and healthy communities.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.016 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".