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Record W3196568916

Policies to Mitigate Climate Change by Addressing Single-Use Plastic Production and Waste Disposal

2021· article· en· W3196568916 on OpenAlexaff
Tony R. ‎Walker

Bibliographic record

VenueSSRN Electronic Journal · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsDalhousie University
Fundersnot available
KeywordsGreenhouse gasPlastic pollutionWaste managementIncinerationLife-cycle assessmentFossil fuelEnvironmental scienceProduction (economics)Municipal solid wasteCircular economyNatural resource economicsPollutionEngineering
DOInot available

Abstract

fetched live from OpenAlex

Addressing plastic pollution has been viewed as a distraction from Climate Action. But it is not. Plastics derived from fossil-fuels account for 6% of global oil consumption. Therefore, plastics and greenhouse gas (GHG) emissions are intricately connected with every step of the plastic life cycle, from production to transportation to waste disposal, and thus are a major contributor to climate change. Unsustainable plastic production and use of plastic waste for energy recovery by incineration has been widely criticized because of the release of GHG emissions. In Europe, plastic production and incineration of plastic waste contributes to ∼400 million tonnes of CO2/year. Global GHG emissions from plastics will reach 1.34 gigatons per year by 2030 and 2.8 gigatons per year by 2050. Even when plastics degrade in the environment GHGs are emitted. Policy recommendations to reduce GHG emissions from plastic production and waste disposal include: 1. Immediate phase out of virgin fossil-fuel based plastic production for consumer plastics (e.g., single-use plastics which are difficult to recycle and are major contributors to global plastic pollution). 2. International binding agreements and national policies for a total ban on virgin fossil-fuel based plastic production for single-use consumer plastics by 2030. 3. Consumer plastics to be 100% recyclable by 2030 or produced from sustainable low-carbon 100% bio-based plastics. This policy action aligns with international commitments to curb climate change and to achieve zero plastic waste by transitioning to a low-carbon circular economy.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score0.689

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.247
Teacher spread0.222 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations2
Published2021
Admission routes1
Has abstractyes

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