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Record W4394996391 · doi:10.1016/j.jenvman.2024.120945

Influence of Canadian provincial stewardship model attributes on the cost effectiveness of e-waste management

2024· article· en· W4394996391 on OpenAlexafffundabout
Anica Tasnim, Rumpa Chowdhury, Sharmin Jahan Mim, Kelvin Tsun Wai Ng, Hillary Adu-Darko

Bibliographic record

VenueJournal of Environmental Management · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStewardship (theology)Per capitaData collectionWaste collectionBusinessEnvironmental resource managementEnvironmental planningOperations managementGeographyEnvironmental economicsWaste managementEnvironmental scienceEngineeringMunicipal solid wasteEconomicsEnvironmental healthPolitical science

Abstract

fetched live from OpenAlex

This paper presents a comprehensive analysis of e-waste collection and management trends across six Canadian provinces, focusing on e-waste collection rates, provincial stewardship model attributes, program strategies and budget allocations from 2013 to 2020. Temporal and regression analyses were conducted using data from Electronic Product Recycling Association reports. A group characterization based on geographical proximity is proposed, aiming to explore the potential outcomes of fostering collaboration among neighboring provinces. The analysis emphasizes the significant impact of stewardship model attributes on e-waste collection rates, with Quebec emerging as a standout case, showcasing a remarkable 61.5% surge in collection rates. Findings from group analysis reveal a positive correlation between per capita e-waste collection rate and the growth of businesses and collection sites in Western Canada (Group A - British Columbia, Saskatchewan, and Manitoba). This highlights the potential benefits of a coordinated waste management approach, emphasizing the importance of shared resources and collaborative policies. Saskatchewan and Manitoba allocated only 6.6% and 7.0% of their respective budgets to e-waste transfer and storage. British Columbia's observed steady decrease of e-waste collection rate. In Group A, stewards handled 2.18-13.95 tonnes of e-waste during the study period. The cost per tonne of e-waste tended to be lower when more e-waste is managed per steward, suggesting the potential benefits of an integrated e-waste collection and management system.

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)0.002
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score0.702

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.225
Teacher spread0.211 · 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 designSimulation or modeling
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

Citations14
Published2024
Admission routes3
Has abstractyes

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