Toward a Global Agenda for Research in Environmental Epidemiology
Bibliographic record
Abstract
The global environment is in critical decline. Whether one's concern about environmental epidemiology stems from the perspectives of environmental health, climate change, ecological collapse, or growing inequity, clear problems exist. Natural capital resources are being depleted; disregard for the integrity of ecosystems is entrenched in current business practices. Indeed, despite increasing rhetoric to the contrary, the disregard displayed by those who hold power globally toward long-term sustainability and, thus, the health and well-being of future generations, could be described as wanton. Six years ago, the Millennium Development Goals were announced by the United Nations as a rallying point for action to achieve a sustainable future, particularly by reducing the gap between the "have mores" and "have nots." The attainment of these Goals is now endangered, as is, apparently, the spirit of optimism and idealism that inspired them at the Millennium Summit. We call for a reinvigoration of both concern about-and action on-sustainability. In particular, we appeal to those engaged in the field of environmental epidemiology (and other specialties with whom they engage) to consider how they might help by incorporating sustainability issues (including global ecological integrity and global environmental justice) into their own research programs. This incorporation would make a vital contribution to protect both present and future generations and to reduce resource and health gaps between North and South. Simply put, we propose that sustainability becomes integral to advancing the science of environmental epidemiology and related environmental disciplines.
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 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 | 0.201 | 0.148 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.006 | 0.031 |
| Scholarly communication | 0.026 | 0.042 |
| Open science | 0.006 | 0.020 |
| Research integrity | 0.044 | 0.056 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".