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Record W2054655450 · doi:10.1177/0734242x07079152

Policy options to reduce consumer waste to zero: comparing product stewardship and extended producer responsibility for refrigerator waste

2007· article· en· W2054655450 on OpenAlexaff
Scott Nicol, Shirley Thompson

Bibliographic record

VenueWaste Management & Research The Journal for a Sustainable Circular Economy · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsExtended producer responsibilitySustainabilityBusinessGreenhouse gasReuseEnvironmentally friendlyProduct (mathematics)Stewardship (theology)Consumption (sociology)Environmental stewardshipCleaner productionWaste managementEnvironmental economicsNatural resource economicsElectronic wasteMunicipal solid wasteEnvironmental resource managementEnvironmental scienceEngineeringEconomics

Abstract

fetched live from OpenAlex

Today, over-consumption, pollution and resource depletion threaten sustainability. Waste management policies frequently fail to reduce consumption, prevent pollution, conserve resources and foster sustainable products. However, waste policies are changing to focus on lifecycle impacts of products from the cradle to the grave by extending the responsibilities of stakeholders to post-consumer management. Product stewardship and extended producer responsibility are two policies in use, with radically different results when compared for one consumer product, refrigerators. North America has enacted product stewardship policies that fail to require producers to take physical or financial responsibility for recycling or for environmentally sound disposal, so that releases of ozone depleting substances routinely occur, which contribute to the expanding the ozone hole. Conversely, Europe's Waste Electrical and Electronic Equipment (WEEE) Directive requires extended producer responsibility, whereby producers collect and manage their own post-consumer waste products. WEEE has resulted in high recycling rates of greater than 85%, reduced emissions of ozone-depleting substances and other toxins, greener production methods, such as replacing greenhouse gas refrigerants with environmentally friendly hydrocarbons and more reuse of refrigerators in the EU in comparison with North America.

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)0.040
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.570
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0400.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.003
Science and technology studies0.0040.000
Scholarly communication0.0030.002
Open science0.0020.003
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 head0.048
GPT teacher head0.344
Teacher spread0.296 · 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.

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

Citations57
Published2007
Admission routes1
Has abstractyes

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