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Record W4399153400 · doi:10.1093/cjres/rsae015

Exploring circular economy transition pathways: a roadmap analysis of 15 Canadian local governments

2024· article· en· W4399153400 on OpenAlexaffabout
Juste Rajaonson, Chedrak Chembessi

Bibliographic record

VenueCambridge Journal of Regions Economy and Society · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsSocioeconomic statusTransition (genetics)Circular economyEconomic geographyRegional scienceSocioeconomic developmentEconomic systemPolitical scienceEconomic growthGeographyEconomicsSociologyEcology

Abstract

fetched live from OpenAlex

Abstract This paper explores how 15 Canadian local governments of various sizes and contexts are transitioning to a circular economy by analysing their roadmap currently in development. It provides qualitative insights into how physical, socioeconomic and institutional factors are influencing the content of roadmaps, along with their similarities and differences. Drawing from the literature on the geography of transitions, we show that while local physical and socioeconomic attributes typically shape the roadmaps by determining likely activities, their actual trajectory varies based on the roadmap instigators and the broader institutional contexts in which they operate. The findings suggest the importance of local governments supporting the roadmap instigators while also recognising that circular economy transition pathways can capitalise on policies and programs not only locally but beyond local boundaries.

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)0.009
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 score0.044
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0070.022
Science and technology studies0.0060.002
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.032
GPT teacher head0.198
Teacher spread0.166 · 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

Citations18
Published2024
Admission routes2
Has abstractyes

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