Optimizing Chemicals Management in the United States and Canada through the Essential-Use Approach
Bibliographic record
Abstract
Chemicals have improved the functionality and convenience of industrial and consumer products, but sometimes at the expense of human or ecological health. Existing regulatory systems have proven to be inadequate for assessing and managing the tens of thousands of chemicals in commerce. A different approach is urgently needed to minimize ongoing production, use, and exposures to hazardous chemicals. The premise of the essential-use approach is that chemicals of concern should be used only in cases in which their function in specific products is necessary for health, safety, or the functioning of society and when feasible alternatives are unavailable. To optimize the essential-use approach for broader implementation in the United States and Canada, we recommend that governments and businesses (1) identify chemicals of concern for essentiality assessments based on a broad range of hazard traits, going beyond toxicity; (2) expedite decision-making by avoiding unnecessary assessments and strategically asking up to three questions to determine whether the use of the chemical in the product is essential; (3) apply the essential-use approach as early as possible in the process of developing and assessing chemicals; and (4) engage diverse experts in identifying chemical uses and functions, assessing alternatives, and making essentiality determinations and share such information broadly. If optimized and expanded into regulatory systems in the United States and Canada, other policymaking bodies, and businesses, the essential-use approach can improve chemicals management and shift the market toward safer chemistries that benefit human and ecological health.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".