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Record W3044961431 · doi:10.1017/aju.2020.39

The Montreal Protocol or the Paris Agreement as a Model for a Plastics Treaty?

2020· article· en· W3044961431 on OpenAlexaboutno aff
Elizabeth A. Kirk

Bibliographic record

VenueAJIL Unbound · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsnot available
Fundersnot available
KeywordsTreatyAppealProtocol (science)Process (computing)Montreal ProtocolSet (abstract data type)Law and economicsKyoto ProtocolComputer scienceBusinessLawPolitical scienceRisk analysis (engineering)Climate changeEconomicsChemistry

Abstract

fetched live from OpenAlex

The notion that a plastics treaty is necessary is gaining traction, but there is less agreement as to its content. Some, including this author, have suggested that a plastics treaty should be modelled on treaties such as the Montreal Protocol, which sets out a broad commitment to end the use of a particular material and then introduce regulations to ban particular forms of that material over time. This approach has an immediate appeal—it sends a signal to states and to industry that they must change their behaviors and products, while giving time to adapt to the new regulation and develop alternative materials or ways of working. The potential drawback of this approach is that some states simply will not accept such rigid standards. In addition, some states may prefer a second approach that is more obviously rooted in the principle of common but differentiated responsibilities, which assigns different obligations to parties according to their respective capacities. Within the climate change regime, the Paris Agreement takes both approaches, asking states to set their own nationally determined contributions (NDCs) to emissions reductions (common but differentiated responsibilities) and then to revise these NDCs over time through an iterative process to deliver progressively more ambitious targets for emissions reduction (moving toward a ban) or mitigation. In reality, neither approach is entirely suited to regulating plastics, so a new approach to treaty-making is required. This new approach should focus on the outcomes desired rather than the practices that need to be regulated.

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.137
Threshold uncertainty score0.273

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0070.018
Scholarly communication0.0150.019
Open science0.0040.005
Research integrity0.0170.014
Insufficient payload (model declined to judge)0.0400.008

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.

Opus teacher head0.027
GPT teacher head0.255
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2020
Admission routes1
Has abstractyes

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