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Record W2504822650 · doi:10.1017/ccol0521839661.006

Margaret Atwood and environmentalism

2006· book-chapter· en· W2504822650 on OpenAlexaboutno aff
Shannon Hengen

Bibliographic record

VenueCambridge University Press eBooks · 2006
Typebook-chapter
Languageen
FieldArts and Humanities
TopicUtopian, Dystopian, and Speculative Fiction
Canadian institutionsnot available
Fundersnot available
KeywordsSubtextEnvironmentalismEnvironmental ethicsMedia studiesLiteratureHistoryArt historyAestheticsSociologyArtLawPolitical sciencePhilosophyPolitics

Abstract

fetched live from OpenAlex

“What is a human being?” This question, among others, constitutes what Atwood calls the “sub-sub-subtext” of her lecture delivered at Carleton University (Ottawa, Canada) in January of 2004, “Scientific Romancing: The Kesterton Lecture.” Primarily a lecture on science fiction, it also touches on themes that have informed her writing for several decades - despotism versus decency; obsessive control versus the spectrum of human desire; science and art; reason and the imagination - all of which contribute to her sense of the environment. How much imbalance in these pairs of terms can we tolerate? Or, as she says in her lecture, “How far can we go in the alteration department and still have a human being?” The present is a turning point for Atwood. She states in the Kesterton Lecture and in her very short piece entitled “Writing Oryx and Crake ” that, until now, the human animal has not changed. “What we want has not changed for thousands of years, because, as far as we can tell, human nature hasn’t changed either” (“Kesterton Lecture,” n.p.); and, “ homo sapiens remains at heart what he’s been for tens of thousands of years – the same emotions, the same preoccupations.” Her view of the animal itself up to this turning point will emerge in analysis of her work. For now, keep in mind that given current scientific research we are able, for the first time, to alter that animal beyond recognition.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.012
Scholarly communication0.0040.005
Open science0.0000.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.021
GPT teacher head0.163
Teacher spread0.143 · 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 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

Citations22
Published2006
Admission routes1
Has abstractyes

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