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Écologie politique des paysans alternatifs de l’Empordà (Catalogne) : s’engager entre mer et montagne

2020· article· fr· W3024123093 on OpenAlexaff
Sabrina Doyon

Bibliographic record

VenueDéveloppement durable et territoires · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesPolitical scienceEthnologySociologyArt

Abstract

fetched live from OpenAlex

La région de l’Empordà, dans le nord de la Catalogne espagnole, voit l’émergence, depuis une vingtaine d’années, d’une paysannerie alternative à l’agriculture conventionnelle conjuguant des démarches d’écologisation à un processus de territorialisation du système alimentaire. C’est ce que cet article s’attachera à examiner chez des producteurs vitivinicoles et oléicoles ainsi que, dans une moindre mesure, des maraîchers et des éleveurs. Comment sont-ils parvenus à amalgamer ces deux processus ? Quelles sont les valeurs qui les guident et les pratiques qu’ils mettent en action ? Quelles sont les répercussions sociales et économiques de ces initiatives ? À l’aide de l’approche de la political ecology, nous proposons d’explorer les changements environnementaux récents ayant marqué l’Empordà, et qui s’ancrent dans un contexte socio-économique et politique constituant le socle sur lequel se fondent l’émergence de ces paysans alternatifs ainsi que les pratiques et les discours qu’ils mettent en avant. L’analyse révèle qu’ils proposent un modèle qui leur est propre, conjuguant mer et montagne, mais non sans ambiguïté. En ce sens, ils mettent en lumière les tensions et les paradoxes propres à ce monde « alternatif et écologique ».

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 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)0.001
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.737
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.085
GPT teacher head0.317
Teacher spread0.232 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations1
Published2020
Admission routes1
Has abstractyes

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