MétaCan
Menu
Back to cohort
Record W2013515406 · doi:10.3138/utq.69.4.849

Temporality and Margaret Atwood

2000· article· en· W2013515406 on OpenAlexvenueaboutno aff
Alice Ridout

Bibliographic record

VenueUniversity of Toronto Quarterly · 2000
Typearticle
Languageen
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsnot available
Fundersnot available
KeywordsManifestoTheme (computing)Survival of the fittestPoliticsFormative assessmentWildernessHistoryCanadian literatureTemporalitySociologyLiteratureGenealogyLawEpistemologyArtPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Margaret Atwood’s attempt to define ‘What’s Canadian about Canadian Literature’ in Survival is a helpful starting point for considering the way the stories in Dancing Girls (1977), Bluebeard’s Egg (1983), and Wilderness Tips (1992) relate to the short story genre and Canadian literature as broad, limiting categories. Atwood herself recognizes the personal nature of Survival, defining it as ‘a cross between a personal manifesto’ and ‘a political manifesto’ (Survival, 13). She also acknowledges that ‘several though by no means all of the patterns I’ve found myself dealing with here were first brought to my attention by my own work’ (14). As the title suggests, Atwood’s main thesis is that the recurring theme of Canadian literature is survival. Although Atwood identifies different types of survival (such as Canada’s cultural survival despite the influence of the United States), she believes that the most prevalent type of survival in ‘Canlit’ is simply that of ‘hanging on, staying alive’ (33). Survival was a difficult challenge for early settlers, and Atwood certainly seems correct in identifying it as a formative experience for early writers:

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)0.002
metaresearch head score (Gemma)0.004
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 score0.502
Threshold uncertainty score0.998

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0190.015
Scholarly communication0.0070.006
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.007
GPT teacher head0.178
Teacher spread0.171 · 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

Citations4
Published2000
Admission routes2
Has abstractyes

Explore more

Same venueUniversity of Toronto QuarterlySame topicShort Stories in Global LiteratureFrench-language works237,207