Time to Break the “Lock-In” Impediments to Chemicals Management
Bibliographic record
Abstract
Despite enormous national, regional, and global efforts on chemical management, the widespread use of hazardous chemicals continues in many parts of the world even after decades of there being well-known risks to public and/or ecosystem health. This continued supply and use, despite strong evidence of negative impacts, is not unique to chemicals management. In the field of climate change, the concept of "lock-in" has been used to explain the complex interactions among economic, social, technological, and political dynamics that reinforce global reliance on the extraction and use of fossil fuels. Learning from carbon "lock-in" phenomena, this Perspective explores the challenges of chemicals management from the perspective of lock-in through three case studies: paraquat, perfluorooctanesulfonic acid (PFOS), and asbestos. These case studies illustrate that most current chemicals management frameworks fail to address the concerns arising from this complex interplay by not involving all relevant stakeholder groups that are part of lock-in, from producers to consumers. This results in a relatively narrow consideration (e.g., only demand but not supply) of the effectiveness and consequences of regulations. We submit that to break lock-in and address the global threat of chemical pollution, current approaches to managing hazardous chemicals should be broadened to take a comprehensive approach to understanding and managing factors contributing to lock-in, notably both supply and demand on national and international scales.
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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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.012 | 0.017 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".