Bibliographic record
Abstract
Chemicals provide many benefits to humans, but they also present risks. This double nature obliges governments to regulate the chemical risks to secure safety in order to protect public health and environment. Moreover, regulation of chemical risks obliges them to view the global trend toward modernization of chemical management. This is because the market for industrial chemicals is global, and chemical releases can cross borders. Regulation of industrial chemicals is in a period of global maturation. In 2002, the United Nations World Summit on Sustainable Development established the goal that by 2020, chemicals are used and produced in ways that lead to the minimization of significant adverse effects on human health and the environment. To this end, for decades, nations around the world have been updating their regulatory programs. Canada. European Union, Japan, China, Korea, to name a few, are running in this race. Meanwhile, the U.S. Congress has been slow to modernize the Toxic Substances Control Act of 1976 (TSCA), despite a broad consensus that the current design of TSCA is outmoded. Due to this passive attitude of the federal government, U.S. states, prominently California,have enacted new and upgrading programs aimed at assessing and reducing the potential for adverse effects from chemical exposures. In this context, this paper aims at examining the current U.S. chemical safety law and regulation. Notwithstanding the fact that the Korea enacted and has just began implementing the new and advanced regulatory program, this examination is practically, economically and industrially meaningful. It is because the U.S. is the number one producer and trader of chemicals and chemical products in the world. Accordingly, this article first overviews the general chemical regulatory system and governance, and then examines TSCA and Consumer Product Safety Improvement Act in details. It further addresses the new and prominent California Proposition 65 and lastly concludes with some implications.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.084 | 0.039 |
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".