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Record W3082429976 · doi:10.3390/su12197912

Addressing the Social Aspects of a Circular Economy: A Systematic Literature Review

2020· article· en· W3082429976 on OpenAlexafffund
Alejandro Padilla‐Rivera, Sara Russo-Garrido

Bibliographic record

VenueSustainability · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsUniversité du Québec à MontréalPolytechnique Montréal
FundersConsejo Nacional de Ciencia y TecnologíaUniversité du Québec à Montréal
KeywordsCircular economyScarcityReuseSustainable developmentResource scarcitySustainabilityProduct (mathematics)Work (physics)Environmental economicsBusinessResource (disambiguation)EconomicsManagement sciencePolitical scienceEngineeringComputer scienceNatural resource economicsMicroeconomics

Abstract

fetched live from OpenAlex

Circular Economy (CE) is a growing topic among scholars, industries, and governments, and is aimed at decoupling economic growth and development from the consumption of finite resources. CE incorporates different meanings, from reduce, reuse, and recycle activities, to environmental degradation or resource scarcity, and is supported by specific indicators to attain sustainable development. However, so far, there has been no agreement to measure how effective an industry/product is in making the transition from linear to circular approaches, particularly those that affect society. This research work aims to perform a systematic literature review (n = 60) to analyze and discuss how social aspects have been considered and integrated in CE research so far. Moreover, this review provides an overview of the literature on social impact within the CE, which results in three main outputs: a knowledge map of the CE, an analysis of social aspects within CE, and the theories/frameworks used to evaluate social impact of CE. Finally, this study brings to light how CE implementation can affect society and highlights the importance of social dimension in the domains of CE and a policy-making community, which could help move CE towards a sustainable development.

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)0.013
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.025
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.049
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0250.020
Science and technology studies0.0010.002
Scholarly communication0.0040.005
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.031
GPT teacher head0.275
Teacher spread0.243 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations326
Published2020
Admission routes2
Has abstractyes

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