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Record W4225116257 · doi:10.3917/recma.364.0180

Tirer le meilleur parti de la contribution de l’économie sociale à l’économie circulaire

2022· article· fr· W4225116257 on OpenAlexaff
Julie Rijpens, Julien De Beys

Bibliographic record

VenueRECMA · 2022
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsMinistère de l’Emploi et de la Solidarité Sociale (Québec)
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Ce texte explore la contribution de l’économie sociale à la transition vers une économie circulaire comme moyen d’engager les citoyens, les entreprises et les territoires dans la circularité. En se basant sur une revue de la littérature, il définit à la fois le concept d’économie circulaire et celui d’économie sociale. Il décrit le potentiel de l’économie sociale pour soutenir les activités circulaires et les modèles d’entreprises apparentés, ainsi que pour mieux intégrer la circularité dans nos économies et nos sociétés. Enfin, il examine la façon de mieux capitaliser sur ce potentiel et d’identifier les orientations politiques qui s’appuient sur la complémentarité des économies sociale et circulaire pour soutenir la circularité et stimuler une transition verte et inclusive.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.029
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0050.008
Scholarly communication0.0130.011
Open science0.0010.004
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0290.003

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 head0.008
GPT teacher head0.216
Teacher spread0.208 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2022
Admission routes1
Has abstractyes

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