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Record W2804195559 · doi:10.1111/poms.12894

Did Europe Move in the Right Direction on E‐waste Legislation?

2018· article· en· W2804195559 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueProduction and Operations Management · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsMcGill University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsReuseLegislationProduct (mathematics)Context (archaeology)IncentiveStylized factDirectiveLegislatureEnvironmental economicsBusinessComputer scienceRemanufacturingIndustrial organizationRisk analysis (engineering)EconomicsManufacturing engineeringMicroeconomicsEngineeringLaw

Abstract

fetched live from OpenAlex

This study presents an analytical framework of the product take back legislation in the context of product reuse. We characterize existing and proposed forms of E‐waste legislation and compare their environmental and economic performance. Using stylized models, we analyze an OEM's decision about new and remanufactured product quantity in response to the legislative mechanism. We focus on the 2012 waste electrical and electronic equipment directive in Europe, where the policy makers intended to create additional incentives for the product reuse. Through a comparison to the Original 2002 version of the directive, we find that these incentives translate into improved environmental outcomes only for a limited set of products. We also study a proposed policy that advocates a separate target for the product reuse. Our analysis reveals that from an environmental standpoint, the Recast version is always dominated either by the Original policy or by the one that advocates a separate target for product reuse. We show that the benefits of a separate reuse target scheme can be fully replicated with the aid of fiscal levers. Our main message is that there cannot be a single best environmental policy that is suitable for all products. Therefore, the consideration of product attributes is essential in identification of the most appropriate policy tool. This can be done either by the implementation of different policies on each product category or by implementation of product‐based target levels.

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.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.659
Threshold uncertainty score0.266

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.009
GPT teacher head0.240
Teacher spread0.231 · 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