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Record W1502709728 · doi:10.3390/resources4030434

Stakeholder Perceptions of Unit Based Waste Disposal Schemes in Ontario, Canada

2015· article· en· W1502709728 on OpenAlexaffabout
Calvin Lakhan

Bibliographic record

VenueResources · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsStakeholderEnforcementUnit (ring theory)BusinessHousehold wasteEnvironmental economicsEconomicsEngineeringPolitical scienceWaste management

Abstract

fetched live from OpenAlex

This study examines stakeholder perceptions of pay as you throw schemes (PAYT) in Ontario, Canada. Using a combination of panel and semi-structured survey data from provincial municipalities, focus is placed on analyzing: (a) the effects of PAYT systems on municipal recycling rates and program costs (b) stakeholder perceptions on the perceived effectiveness of PAYT policy (c) how locality affects PAYT program costs and affect municipal recycling rates and (d) the impact of Ontario’s “one Blue Box per household” provision on PAYT schemes. The results of the analysis show that while the implementation of PAYT schemes do increase municipal recycling rates, there are opportunities for further improvement. In Ontario, the effectiveness of PAYT policy is impaired by inconsistent enforcement, administrative burden, and the inadequate capacity of household recycling bins (“blue bins”).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.288

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.042
GPT teacher head0.225
Teacher spread0.182 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations8
Published2015
Admission routes2
Has abstractyes

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