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Record W1577512309 · doi:10.7202/1062362ar

“A Whole New Take on Indigenous”: Margaret Atwood’s Oryx and Crake as Wild Animal Story

2019· article· en· W1577512309 on OpenAlexaffvenueabout
Lee Frew

Bibliographic record

VenueStudies in Canadian Literature · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicUtopian, Dystopian, and Speculative Fiction
Canadian institutionsYork University
Fundersnot available
KeywordsOryxDystopiaEnvironmental ethicsHistoryPolitical scienceLawPhilosophyEcology

Abstract

fetched live from OpenAlex

Margaret Atwood’s MaddAddam trilogy has met with popular acclaim and generated considerable scholarly interest since the 2003 publication of its first volume, Oryx and Crake. The implicit critique of Western capitalism presented in Atwood’s dystopian vision of a post-democratic, post-national, and post-human future seems to offer a wide appeal, particularly at a time of sustained environmental crisis. Instead of evaluating the merits of Atwood’s critique, however, this paper examines the ways in which the speculative future of Oryx and Crake and the warnings it contains are delimited by a problematic Second World paradigm. More specifically, the novel can be read in terms of the wild animal story, a genre first established in late-nineteenth-century Canada that Atwood herself was instrumental in defining as such in her controversial 1972 study Survival: A Thematic Guide to Canadian Literature. In keeping with the conventions of the wild animal story, boundary crossings in Atwood’s novel engage in indigenizing fantasy. Despite its powerful warning of imminent disaster, Oryx and Crake nevertheless obscures ongoing colonializing acts by privileging a settler subject-position conceived as endangered by the forces of modernity

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.942
Threshold uncertainty score0.980

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 studies0.0000.000
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 head0.022
GPT teacher head0.251
Teacher spread0.229 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2019
Admission routes3
Has abstractyes

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