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Record W7128435657 · doi:10.7202/1122192ar

Mutants, cyborgs, chimères ou post-animaux. Une approche écotechnocritique

2025· article· fr· W7128435657 on OpenAlexvenueno aff
Mara Magda Maftei

Bibliographic record

VenueÉtudes littéraires · 2025
Typearticle
Languagefr
FieldArts and Humanities
TopicEcocriticism and Environmental Literature
Canadian institutionsnot available
Fundersnot available
KeywordsIdentity (music)The ImaginaryModernityContext (archaeology)Relation (database)

Abstract

fetched live from OpenAlex

Une catégorie de la fiction contemporaine s’intéresse à des formes de vie conçues en fluidité, influencées par les enjeux technoscientifiques et écologiques, et porte un regard différent sur la relation entre les animaux humains et non-humains dans un environnement affecté par le dérèglement climatique. Les personnages de ces œuvres de fiction sont des post-humains (Pierre Ducrozet, L’Invention des corps , 2017 ; Jeanette Winterson , Frankissstein , 2021), des logiciels (Antoine Bello, Ada , 2016), des post-animaux (Emmanuelle Pireyre, Chimère , 2019 ; Mireille Gagné, Frappabord , 2024), des éléments de la nature susceptibles de devenir des sujets de droit (Olivier Remaud, Penser comme un iceberg , 2020). Ces œuvres littéraires créées dans un réseau intertextuel et interdisciplinaire participent à l’émergence d’une réflexion critique, caractérisée par une dimension idéologique, mais aussi poétique (l’écotechnocritique étant l’approche propre à ces formes de vie en mutation). Outre la dimension thématique évidente, cette fiction intellectuelle se distingue par des repérages formels analysés dans le cadre de cet article. Le corpus comparatiste contribue à moduler l’approche écotechnocritique par le dialogue avec différentes sciences.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.922
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
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 head0.010
GPT teacher head0.227
Teacher spread0.218 · 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
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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