Global Environmental Change and Human Health: An Earth System Science Partnership Response
Bibliographic record
Abstract
ISEE-0685 Background and Objective: The purpose of this paper is to introduce the new Earth System Science Partnership (ESSP) Project on Global Environmental Change and Human Health (GECHH) launched by the four global environmental change research programmes: an international programme on biodiversity science (DIVERSITAS), the International Geosphere-Biosphere Programme (IGBP), the International Human Dimensions Programme on Global Environmental Change (IHDP) and the World Climate Research Programme (WCRP). Methods: The evolving Science Plan explores priorities and settings for the future coordinated international study of the relationships between GEC and human health, taking into account the complexities of concurrently acting environmental changes and the importance of socioeconomic and cultural contexts as modifiers of community vulnerability. Results: The added value of this Project is clear in that it seeks to identify and quantify current health impacts of GEC and to forecast the future health impacts. These scenarios of future health impacts will form a new, dynamic and integrative node in the developing domain of Earth System Science. They will help focus on policy options that ensure a healthier and more sustainable future. The Project will also make connections with other international organizations concerned with health and the environment and argue that there is a natural synergy to be pursued between the GEC and human health community and the ISSE community. Conclusion: Many of the researchers in the environmental epidemiology community are already carrying out research that overlaps with the ESSP GECHH agenda and, therefore, we seek to encourage even greater participation of the ISSE community in the future activities of the ESSP Global Environmental Change and Human Health Project.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".