Narrowing feedstock exemptions under the Montreal Protocol has multiple environmental benefits
Bibliographic record
Abstract
The Montreal Protocol on Substances that Deplete the Ozone Layer (Montreal Protocol) can be further strengthened to control ozone-depleting substances and hydrofluorocarbons used as feedstocks to provide additional protection of the stratospheric ozone layer and the climate system while also mitigating plastics pollution. The feedstock exemptions were premised on the assumption that feedstocks presented an insignificant threat to the environment; experience has shown that this is incorrect. Through its adjustment procedures, the Montreal Protocol can narrow the scope of feedstock exemptions to reduce inadvertent and unauthorized emissions while continuing to exempt production of feedstocks for time-limited, essential uses. This upstream approach can be an effective and efficient complement to other efforts to reduce plastic pollution. Existing mechanisms in the Montreal Protocol such as the Assessment Panels and national implementation strategies can guide the choice of environmentally superior substitutes for feedstock-derived plastics. This paper provides a framework for policy makers, industries, and civil society to consider how stronger actions under the Montreal Protocol can complement other chemical and environmental treaties.
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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 | 0.021 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".