A critical perspective on the Society of Environmental Toxicology and Chemistry’s adherence to founding principles—opportunities for the future
Bibliographic record
Abstract
The Society of Environmental Toxicology and Chemistry (SETAC) is a global organization whose mission is the advancement of environmental science and management through collaboration, leadership, communication, and education. On SETAC's 45th anniversary, the following question was raised: Are the 1979 founding principles of SETAC, multidisciplinary approaches to solving environmental problems, multisector engagement, and scientific objectivity, still useful, adequate, and effective in fulfilling its mission? In a special session held at the 45th Annual Meeting in Fort Worth, Texas, United States, a critical evaluation of the founding principles was initiated by reviewing SETAC's history and ongoing activities, and recommendations were made for the future. With few exceptions, participants appreciated SETAC's purposeful efforts to approach challenging environmental issues through multisectoral balance, an approach that is unique among scientific societies. We recognized that scientists have biases and views of what they find important, regardless of employing organization, and that objectivity is best served by being aware of these biases and views. SETAC's founding principles have stood the test of time and continue to provide a strong foundation for the Society's mission, and with a few suggested improvements, will continue to be instrumental in guiding environmental science, stewardship, and policy into the future. The significance of SETAC's contribution of robust science grounded in reliable evidence and data was recognized as being especially crucial at this time of triple planetary crisis (climate change, pollution, and biodiversity loss), compounded by rapid technological developments and geopolitical issues.
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 | 0.116 | 0.099 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.031 | 0.073 |
| Scholarly communication | 0.039 | 0.037 |
| Open science | 0.005 | 0.020 |
| Research integrity | 0.045 | 0.081 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".