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La mise en marché alternative de l’alimentation à Montréal. De la niche d’innovation à une transition du secteur alimentaire ?

2016· article· fr· W2295894273 on OpenAlexaffvenueabout
Sylvain Lefèvre, René Audet

Bibliographic record

VenueInterventions économiques · 2016
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

La mise en marché alternative de l’alimentation (MMAA) vise à favoriser l’accès de proximité à une saine alimentation via la mise en réseau des producteurs et des consommateurs au sein de circuits courts, tout en poursuivant des objectifs de développement social et communautaire, de convivialité et de sécurité alimentaire dans les quartiers. Cet article, issu d’un processus de recherche action mené avec des initiatives de MMAA, s’interroge sur les stratégies que ces initiatives peuvent privilégier afin de contribuer à une transition du système agroalimentaire vers un état plus soutenable. L’approche des sustainability transitions est mobilisée afin d’appréhender les défis auxquels fait face la MMAA à cet égard. Deux défis sont analysés en détail : celui de la fragmentation de la « niche » de la MMAA, et celui du verrouillage économique du « régime sociotechnique de l’agroalimentaire ». L’article conclu en définissant trois stratégies possibles pour permettre aux initiatives de MMAA de faire face à ces défis.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.283
Threshold uncertainty score0.570

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.006
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.000

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 head0.020
GPT teacher head0.263
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 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

Citations6
Published2016
Admission routes3
Has abstractyes

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