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Record W2165892206 · doi:10.1177/0270467605282646

A Failing Grade for WEEE Take-Back Programs for Information Technology Equipment

2005· article· en· W2165892206 on OpenAlexaffabout
Nina Nakajima, Willem H. Vanderburg

Bibliographic record

VenueBulletin of Science Technology & Society · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGarbageHazardous wasteElectronic equipmentProduct (mathematics)European unionBusinessEngineeringComputer scienceManufacturing engineeringRisk analysis (engineering)Operations managementWaste management

Abstract

fetched live from OpenAlex

Product take-back (also called extended producer responsibility) has become a trend for dealing with the garbage resulting from categories of problematic products. Waste electrical and electronic equipment (WEEE) is one such category with computer equipment being of particular significance. This article provides a description of the European Union’s program to require the take-back of WEEE as well as the status of similar programs in Canada and the United States. It is concluded that although these programs meet the goal of reducing the quantity of hazardous materials going to landfills, they do not go to the root of the problem by means of preventive approaches that create more circular materials flows. Plastics used in WEEE pose a serious problem, as they are generally not recycled.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.853
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.014
GPT teacher head0.255
Teacher spread0.241 · 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

Citations10
Published2005
Admission routes2
Has abstractyes

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