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Record W2501089188 · doi:10.1017/ccol0521839661.002

Margaret Atwood in her Canadian context

2006· book-chapter· en· W2501089188 on OpenAlexaboutno aff
David Staines

Bibliographic record

VenueCambridge University Press eBooks · 2006
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsPoetryReputationCriticismCanadian literatureLiterary criticismContext (archaeology)Power (physics)LiteratureHistoryPerformance artArtArt historyMedia studiesSociologyPolitical scienceLawArchaeology

Abstract

fetched live from OpenAlex

For more than forty years, Margaret Atwood has been a published author, well known for the intricacies of her poetry, the power of her fiction, and the illumination of her literary criticism. As her reputation has grown steadily in international circles, she has produced more than forty books that have been translated into more than forty languages. But she has rooted most of her writing in her own country of Canada. She is, above all else, Canadian. The early years Born in the city of Ottawa, Canada's capital, on 18 November 1939, Atwood spent her early years in wintry Ottawa and in northern Quebec, where her father, a biologist, pursued his entomological studies. Moving to Toronto in 1946, her parents continued to take young Atwood and her older brother to the northern wilderness in the summers. “I didn't spend a full year in school until I was 11,” Atwood recalls. “Americans usually find this account of my childhood - woodsy, isolated, nomadic - less surprising than do Canadians: after all, it's what the glossy magazine ads say Canada is supposed to be like.” Atwood’s parents are from Nova Scotia, and her extended family lives there: “The orientation of my entire family was scientific rather than literary . . . So while the society around me, in the fifties, was very bent on having girls collect china, become cheerleaders, and get married, my parents were from a different culture. They just believed that it was incumbent on me to become as educated as possible.”2 Her parents were great readers, and though they did not encourage her to become a writer, “they gave me a more important kind of support; that is, they expected me to make use of my intelligence and abilities, and they did not pressure me into getting married.”

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)0.002
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.066
Threshold uncertainty score0.479

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0360.009
Scholarly communication0.0080.003
Open science0.0010.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0210.003

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 head0.014
GPT teacher head0.179
Teacher spread0.164 · 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

Citations17
Published2006
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicCanadian Identity and HistoryFrench-language works237,207