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Record W4412416103 · doi:10.1017/plc.2025.10020

Complexity in managing plastics

2025· article· en· W4412416103 on OpenAlexaboutno aff
Rosalind Malcolm

Bibliographic record

VenueCambridge Prisms Plastics · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Abstract This letter discusses the complex nature of plastics, why regulating plastics is a ‘wicked problem’, and the implications of a life cycle approach. The draft Global Plastics Treaty attempts to address two key problems: the cap on production and the problem of chemical additives in plastics. As a ‘wicked’ problem with many conflicting interests, dealing with plastics requires a holistic life cycle approach completely different from the Montreal Protocol. Strict and enforced limits on polymer production would reduce plastics pollution and also encourage a reduction in the range of additives, as limiting production would make mechanical or chemical recycling more viable. Used plastics need to be turned into a commodity rather than a waste, and reducing and standardising the number of different chemical formulations would help by reducing the number of chemicals to be regulated. To achieve these objectives, this letter argues for a regulatory approach based on a forensic analysis that applies extended environmental systems analysis to all the life cycle stages of the plastics value chain.

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)0.008
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0060.015
Scholarly communication0.0160.018
Open science0.0030.010
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0200.003

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.

Opus teacher head0.021
GPT teacher head0.237
Teacher spread0.216 · 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 designTheoretical or conceptual
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

Citations1
Published2025
Admission routes1
Has abstractyes

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