Ethics guidelines for environmental epidemiologists: 2023 revision
Bibliographic record
Abstract
Recognition of the importance to environmental epidemiology of ethical and philosophical deliberation led, in 1996, to the establishment of Ethics Guidelines for the profession. In 1999, these guidelines were adopted by the International Society for Environmental Epidemiology. The guidelines were revised in 2012 and again in 2023 to ensure continued relevance to the major issues facing the field. Comprising normative standards of professional conduct, the guidelines are structured into four subsections: (1) obligations to individuals and communities who participate in research; (2) obligations to society; (3) obligations regarding funders/sponsors and employers; and (4) obligations to colleagues. Through the 2023 revision of the Ethics Guidelines, the International Society for Environmental Epidemiology seeks to ensure the highest possible standards of transparency and accountability for the ethical conduct of environmental epidemiologists engaged in research and public health 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 | 0.171 | 0.311 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.022 | 0.026 |
| Insufficient payload (model declined to judge) | 0.010 | 0.020 |
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".