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Record W7010813965

La justice sociale dans deux projets visant à augmenter l’accès à la saine alimentation en circuit de proximité avec un dispositif monétaire alternatif

2024· other· fr· W7010813965 on OpenAlexaboutno aff

Bibliographic record

VenueArchipelago (University of Quebec in Montreal) · 2024
Typeother
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsSocial justiceEconomic JusticeWork (physics)Social innovation
DOInot available

Abstract

fetched live from OpenAlex

Les projets des systèmes alimentaires alternatifs visent à répondre aux enjeux sociaux et écologiques des systèmes alimentaires. Dans quelle mesure ces projets contribuent à la justice sociale des communautés? C’est la question de cet essai, qui s’intéresse plus précisément aux projets visant à augmenter l’accès à l’alimentation saine en circuit de proximité avec un dispositif monétaire alternatif. Deux projets sont choisis : la Carte proximité à Montréal et la Caisse alimentaire commune à Montpellier. Les trois dimensions de la justice sociale - distributive, de reconnaissance, et de représentation - sont analysées dans ces deux projets. Les résultats de cette analyse mettent en lumière les efforts faits en matière de justice sociale dans chacun des projets, ainsi que les points à améliorer. Des recommandations sont émises en conclusion à cet égard. Cet essai contribue à une réflexion sur la justice sociale dans les projets des systèmes alimentaires alternatifs. _____________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : justice sociale, systèmes alimentaires alternatifs, circuit de proximité, accès à la saine alimentation, dispositif monétaire alternatif, transition socioécologique, Carte proximité, Caisse alimentaire commune

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)0.014
metaresearch head score (Gemma)0.020
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: none
Teacher disagreement score0.817
Threshold uncertainty score0.365

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0070.005
Scholarly communication0.0090.004
Open science0.0020.009
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0160.001

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 head0.011
GPT teacher head0.249
Teacher spread0.238 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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