MétaCan
Menu
Back to cohort
Record W3009934788 · doi:10.7202/1067883ar

Posthuman Conjectures: Animal and Ecological Sciences in Marie Darrieussecq’s Dystopian Fiction

2020· article· en· W3009934788 on OpenAlex
Stéphanie Posthumus

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDalhousie French Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsMcGill University
Fundersnot available
KeywordsDystopiaPosthumanAnthropocentrismNarrativeHybridityEmbodied cognitionSci-FiHuman animalEcocriticismSociologyAestheticsLiteratureEnvironmental ethicsFantasyPhilosophyArtAnthropologyEpistemologyEcology

Abstract

fetched live from OpenAlex

Despite being published over twenty years apart, Marie Darrieussecq’s novels, Truismes (1996) and Notre vie dans les forêts (2017), share many features including their dystopian setting, urgent narrative tone, and themes of hybridity, corporeality and radical revelation. Deconstructing the boundaries between animal and human, nature and culture, human and machine, they invite the reader to move beyond anthropocentrism. In response to this invitation, I propose four posthuman conjectures, tracing the ethos of animal and ecological sciences in the two novels. First, I examine the ways in which the presence of non-human animal worlds requires imagining new subjectivities and writing embodied languages. Second, I move from the animal world to the machine cyborg who remains caught in the effects and affects of the techno-scientific complex in Darrieussecq’s dystopian fiction. Third, I consider the space made in both novels for death and dying as a non-metaphysical phenomenon situating humans in an eco-evolutionary web. Last, I define writing as a form of (post)human technology that the novels use to reject the notion of human superiority and to illustrate language’s capacity to imagine new, less-hierarchical paradigms.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.328
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.065
GPT teacher head0.352
Teacher spread0.287 · 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