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Record W2976211199 · doi:10.7202/1062447ar

La vie sans la mort. Qu’est-ce qu’un élevage au zoo?

2019· article· fr· W2976211199 on OpenAlexvenueno aff
Jean Estébanez

Bibliographic record

VenueFrontières · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Qu’est-ce que la mort au zoo? Cet article propose de documenter empiriquement un cas spécifique dans lequel la mort apparait comme une abstraction, renvoyant à l’extinction des espèces, sa dimension concrète étant euphémisée et invisibilisée. On propose l’hypothèse qu’il existe un discours et une pratique à vocation unificatrice sur la mort au zoo, qui relève d’une forme de biopolitique, dans le cadre de pratiques d’élevage. Ainsi, la fonction première du zoo serait de déconnecter la naissance de la mort, afin de mettre en valeur son rôle social de conservation des espèces, mais également de se décharger des enjeux moraux concernant la mort (qu’est-ce qu’une bonne mort? comment la justifier?). Pour autant, la mort concrète ressurgit constamment pour les travailleurs, les animaux et parfois pour les visiteurs. Elle est prise en charge par des régimes de justifications variables selon les contextes et les hiérarchies de nos attachements. C’est dans le détail de cette confrontation que la complexité du vivant apparait et que le noeud gordien qui unit la mort et la vie est nécessairement retissé.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.021
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.013
GPT teacher head0.304
Teacher spread0.290 · 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 designQualitative
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

Citations3
Published2019
Admission routes1
Has abstractyes

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