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Record W3015489883

Circular Economy in Quebec: Economic Opportunities and Impacts (english version)

2018· preprint· en· W3015489883 on OpenAlexaboutno aff
Sara Teigiero, Laurence Solar-Pelletier, Sophie Bernard, Marcelin Joanis, Daniel Normandin

Bibliographic record

VenueRePEc: Research Papers in Economics · 2018
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsnot available
Fundersnot available
KeywordsCircular economyDocumentationResource (disambiguation)EconomyBusinessResource efficiencyResource useEconomic impact analysisEconomicsNatural resource economics
DOInot available

Abstract

fetched live from OpenAlex

There is no doubt as to the negative impact that human activity exerts on the environment, and the international community has adopted a number of measures, such as the Paris Agreement, to minimize the medium-and long-term consequences. In Europe and Asia in particular, the concept of circular economy (CE) has become increasingly significant in view of this challenge. While calling for change to current business models, CE seeks greater efficiency in resource use and waste reduction. This report provides an analysis of relevant documentation and identifies the barriers and levers that could impact the transition toward a circular economy, whose potential benefits are also highlighted here. A number of sectors with significant potential in Quebec are brought to light, along with five case studies of organizations that already provide products and services within a circular economy.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.066
Threshold uncertainty score0.341

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.009
Science and technology studies0.0030.001
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0660.003

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 head0.029
GPT teacher head0.265
Teacher spread0.236 · 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 designTheoretical or conceptual
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

Citations0
Published2018
Admission routes1
Has abstractyes

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