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Record W4290992198

Les relations entre ville et agriculture au prisme de l'innovation territoriale

2018· preprint· fr· W4290992198 on OpenAlexfundno aff
Christophe‐Toussaint Soulard, Coline Perrin, Françoise Jarrige, Lucette Laurens, Brigitte Nougarèdes, Pascale Scheromm, Eduardo Chía, Camille Clément, Laura Michel, Nabil Hasnaoui Amri, Marie-Laure Duffaud-Prévost, Gerardo Ubilla-Bravo

Bibliographic record

VenueProdinra (INRA Bordeaux-Aquitaine) · 2018
Typepreprint
Languagefr
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsnot available
FundersMinistry of Agriculture - Saskatchewan
KeywordsPolitical scienceGeographySociology
DOInot available

Abstract

fetched live from OpenAlex

Le concept d’innovation territoriale est mobilisé dans la littérature pour analyser les rapports entre centre et périphérie, la qualité des milieux et la gouvernance territoriale. Nos recherches reprennent ce concept pour saisir les multiples dimensions des relations entre ville et agriculture et pour comprendre ainsi les transformations de l’agriculture dans le contexte de la société urbaine. Nous analysons pour cela les agencements sociaux, spatiaux et organisationnels qui s’opèrent dans les initiatives agri-urbaines locales. À partir d’une chronique de la place prise par l’agriculture dans l’aménagement urbain et dans les politiques locales, l’exemple de Montpellier permet d’illustrer comment ces agencements agri-urbains sont sources d’innovation territoriale. En effet, l’innovation devient territoriale par accumulation de micro-changements, qui finissent par infléchir des fonctionnements établis dans les usages et les normes qui régulent les relations entre ville et agriculture. Ce processus de passage à une plus grande échelle (scaling up) ouvre un champ de recherche sur les relations entre innovations territoriales et transitions globales.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.026
GPT teacher head0.281
Teacher spread0.255 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueProdinra (INRA Bordeaux-Aquitaine)Same topicAgriculture and Rural Development ResearchFrench-language works237,207