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Record W2461793104 · doi:10.7202/1036208ar

Pour une approche systémique et pragmatique de la transition écologique des systèmes agri-alimentaires

2016· article· fr· W2461793104 on OpenAlexvenueno aff
Claire Lamine, Sibylle Bui, Guillaume Ollivier

Bibliographic record

VenueCahiers de recherche sociologique · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

En partant de la confrontation de trois grands cadres théoriques permettant de traiter des processus de transformation des systèmes agri-alimentaires, les théories des transitions socio-techniques, celles de la sociologie pragmatique, et celles des food regimes, cet article formule une proposition qui emprunte à ces différents cadres pour construire une approche systémique, historicisée et ancrée dans la sociologie pragmatique de ces processus. Approche systémique et historicisée, car il s’agit de saisir comment la modification dans le temps des interdépendances entre certains maillons et acteurs des systèmes agri-alimentaires conduisent à ces processus de transition. Ancrée dans la sociologie pragmatique, car nous proposons également de nous intéresser aux controverses opposant divers acteurs revendiquant une transition écologique, ainsi qu’aux processus de changement de pratiques qu’ils mettent éventuellement en oeuvre. En vue de montrer l’intérêt d’une telle proposition, nous appliquons ensuite cette proposition à trois cas d’étude : d’une part, l’analyse du processus d’institutionnalisation de l’agroécologie au Brésil et en France, et d’autre part, celle de la transition agroécologique à l’échelle d’un système agri-alimentaire territorial.

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)0.016
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.004
Science and technology studies0.0040.018
Scholarly communication0.0120.014
Open science0.0030.005
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0090.001

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 head0.119
GPT teacher head0.370
Teacher spread0.251 · 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 designTheoretical or conceptual
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

Citations55
Published2016
Admission routes1
Has abstractyes

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