Governance for health in the Anthropocene
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore the pressing issues facing health and health systems governance in the Anthropocene – a new geological time period that marks the age of colossal and rapid human impacts on Earth’s systems. Design/methodology/approach The viewpoint illustrates the extent of various human induced global ecological changes such as climate change and biodiversity loss and explores the social forces behind the new epoch. It draws together current scientific evidence and expert opinion on the Anthropocene’s health and health system impacts and warns that many these are yet unknown and likely to interact and compound each other. Findings Despite this uncertainty, health systems have four essential roles in the Anthropocene from adapting operations and preparing for future challenges to reducing their own contribution to global ecological changes and an advocacy role for social and economic changes for a healthier and more sustainable future. Practical implications To live up to this challenge, health services will need to expand from a focus on health governance to one on governance for health with a purpose of achieving equitable and sustainable human development. Originality/value As cities and local governments work to create more healthy, just and sustainable communities in the years ahead, health systems need to join with them as partners in that process, both as advocates and supporters and – through their own action within the health sector – as leading proponents and models of good practice.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.029 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".