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A cross‐Canada analysis of the efficiency of residential recycling services

2008· article· en· W2126225082 on OpenAlexaffabout
James C. McDavid, Annette E. Mueller

Bibliographic record

VenueCanadian Public Administration · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsBusinessEnvironmental science

Abstract

fetched live from OpenAlex

Abstract: The primary purpose of this article is to investigate the factors that predict the efficiency of residential recycling collection services in Canadian local governments. The findings are based on a survey of 128 residential recycling producers from all regions of Canada. One of the most significant findings is the lack of a relationship between private‐sector companies collecting recyclables and the overall efficiency of collection operations. The dominance of the private‐sector collection of recyclables (over seventy‐seven per cent of all producers were contracted companies) does not translate into greater efficiencies. The most important variables in the model are amenable to local control. They include tonnes collected per vehicle per year, requiring full bins, inclusion of composting operations in the overall recycling program, the number of different kinds of materials recycled, participation rate, and reliance on side‐loading collection vehicles. Among the direct predictors of unit costs, the key underlying factor is the productivity of residential recycling operations. Because recyclables are marketed, handling them takes time, reduces the weights that collection vehicles can carry, and generally reduces productivity. Even diligent efforts to improve productivity will not bring recycling costs down to the levels for residential solid‐waste collection. Sommaire: L'objectif principal du présent article est d'examiner les facteurs qui prévoient l'efficacité des services de collecte de produits recyclables résidentiels dans les municipalités canadiennes. Les résultats reposent sur un sondage réalisé auprès de 128 producteurs de collecte de produits recyclables résidentiels opérant dans toutes les régions du Canada. L'un des résultats les plus notoires est le manque de relations entre les sociétés du secteur privé qui récupèrent les produits recyclables et l'efficacité d'ensemble des opérations de collecte. La prédominance de la collecte de produits recyclables par le secteur privé (plus de soixante‐dix‐sept pour cent de tous les producteurs étaient des sociétés contractuelles) ne se traduit pas par une plus grande efficacité. Les variables les plus importantes du modèle peuvent faire l'objet d'un contrôle local. Elles comprennent les tonnes récupérées par véhicule par an, l'exigence de poubelles pleines, l'inclusion d'opérations de compostage au programme général de recyclage, le nombre de différentes sortes de matériaux recyclés, le taux de participation, et le recours à des camions de collecte à chargement latéral. Parmi les variables explicatives directes des coûts unitaires, le principal facteur sous‐jacent est la productivité des opérations de recyclage résidentiel. Comme les produits recyclables sont commercialisés, leur manutention prend du temps, réduit le poids que les camions de collecte peuvent transporter, et réduit d'une manière générale la productivité. Même des efforts diligents pour améliorer la productivité ne feront pas baisser les coûts du recyclage aux niveaux de ceux de la collecte des déchets solides résidentiels.

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)0.001
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 score0.019
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.014
GPT teacher head0.232
Teacher spread0.218 · 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

Citations11
Published2008
Admission routes2
Has abstractyes

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