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Record W4212810742 · doi:10.1522/revueot.v30n3.1383

S’ alimenter malgré le froid, la distance et le reste : l’émergence de stratégies favorables à la résilience alimentaire en Jamésie (nord du Québec)

2022· article· fr· W4212810742 on OpenAlexaffvenueabout
France Desjardins, Pierre-André Tremblay

Bibliographic record

VenueRevue Organisations & territoires · 2022
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Cet article s’intéresse à la résilience démontrée par les acteurs du système alimentaire de la Jamésie, dans le nord du Québec, en se basant sur les stratégies déployées par les personnes qui se trouvent à l’extrémité de la chaîne de consommation, soit les « mangeurs ». Dans cette région et ce système alimentaire, nous retrouvons des acteurs économiques liés au système alimentaire (producteurs, transformateurs, distributeurs et transporteurs), mais aussi des organisations communautaires et des instances politico-administratives. L’analyse repose sur le fait que les mangeurs possèdent des caractéristiques individuelles et sociales qui organisent, permettent et contraignent leurs stratégies. Ces résultats d’une recherche réalisée en 2020 ont été intégrés à une réflexion systémique relative à l’interdépendance des acteurs afin de proposer des recommandations visant à développer la participation et la coordination des diverses parties prenantes.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score0.287

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.006
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.011
GPT teacher head0.232
Teacher spread0.220 · 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 designQualitative
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
Published2022
Admission routes3
Has abstractyes

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