A call for mandatory planetary health education in public health and health services research programs
Bibliographic record
Abstract
The effects of global climate and environmental change endanger health, health systems, and public health infrastructure. As future public health and health services professionals, researchers, and clinicians, we will be tasked with protecting and promoting the health of communities in the face of these realities. However, there is limited integration of the environment-health nexus into the curricula of public health and health services research programs. Planetary health, an integrative paradigm linking the complex dynamics between the health of people to the natural systems on which we depend, offers an inroad to equipping emerging health system leaders with the skills and knowledge to protect people and the planet. We call on our institutions to follow other health disciplines, such as medicine, and embed planetary health and environmentally sustainable healthcare practices into core educational offerings.
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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 | 0.136 | 0.149 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.016 |
| Scholarly communication | 0.017 | 0.022 |
| Open science | 0.009 | 0.041 |
| Research integrity | 0.055 | 0.056 |
| Insufficient payload (model declined to judge) | 0.068 | 0.011 |
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".