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Record W4312804074 · doi:10.4000/geocarrefour.20420

TEASER-Lab : faire l'expérience d’une transition agri-alimentaire par la coopération autour d’actions fédératrices

2022· article· fr· W4312804074 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGéocarrefour · 2022
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsASTER
Fundersnot available
KeywordsHumanitiesPhysicsArt

Abstract

fetched live from OpenAlex

A partir de l’exemple d’un réseau d’initiatives et d’acteurs dont l’objectif est de construire un système agri-alimentaire plus sain et plus durable à l’échelle d’un territoire rural (celui environnant la ville de Mirecourt, dans le département des Vosges, France), on dégage trois dimensions qui concourent fondamentalement à la transition : la dimension territoriale en montrant notamment que territorialiser signifie opérer une reconnexion, tant matérielle que cognitive, entre agriculture et alimentation ; une dimension d’innovation, celle-ci étant considérée avant tout comme des expériences partagées qui permettent et nécessitent des apprentissages d’ordres technique, organisationnel et relationnel générant des débats de valeurs ; et enfin, une dimension socialement et politiquement engagée.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.648
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0060.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.263
Teacher spread0.234 · 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