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Record W2800985421 · doi:10.4000/economierurale.5384

Soigner autrement ses animaux : la construction par les éleveurs de nouvelles approches thérapeutiques

2018· article· fr· W2800985421 on OpenAlexaff
Florence Hellec, Claire Manoli

Bibliographic record

VenueÉconomie rurale · 2018
Typearticle
Languagefr
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsASTER
Fundersnot available
KeywordsHumanitiesArtPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Les approches alternatives en santé animale sont devenues courantes dans les élevages, bien que leur efficacité soit contestée par nombre de scientifiques et de vétérinaires. Suivant les principes de la sociologie pragmatique, les auteures ont formalisé le processus par lequel les éleveurs s’approprient ces approches, en reconstituant les quatre scènes au cours desquelles ils s’y confrontent : la formation, l’essai en ferme, le travail en groupe d’éleveurs, la consultation individuelle de spécialistes. Les usages que les éleveurs font de ces approches alternatives relèvent alors de la figure de l’amateur : ils articulent différentes approches pour soigner leur troupeau, ce qui implique une coordination entre leurs propres interventions et celles des autres professionnels de santé.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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: Empirical
Teacher disagreement score0.709
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.026
GPT teacher head0.246
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 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

Citations7
Published2018
Admission routes1
Has abstractyes

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