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Record W3109637521 · doi:10.1515/zaa-2020-2003

Myth and Intersections of Myth and Gender in Canadian Culture: Margaret Atwood’s Revision of the Odyssey in The Penelopiad

2020· article· en· W3109637521 on OpenAlexaboutno aff
Reingard M. Nischik

Bibliographic record

VenueZeitschrift für Anglistik und Amerikanistik · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsMythologyGreek mythologyLiteratureRewritingHistorySociologyClassicsArt

Abstract

fetched live from OpenAlex

Abstract The first part of the article deals with the national myths of Canada. It demonstrates that the long-time supposed lack of myths in Canada may itself be regarded as a myth. After presenting useful meanings of the term myth, the intersections of myth/mythology and gender are considered, both in Canadian culture and in Greek mythology. Linking Homer’s Iliad and Odyssey —the canonized beginnings of Western literature and their foundation on ancient myth—with Canadian culture, Margaret Atwood’s works and their treatment of ancient and social myths are then focussed on, particularly her revisionist rewriting of Homer’s Odyssey in her novel The Penelopiad (2005). This women-centered rewriting of the originally male-dominated story starts from two issues: what led to the hanging of the 12 maids, and what was Penelope really up to? Among the results are an intriguing re-conception of the original main characters, an upgrading of female domestic life, and a debunking not only of Odysseus and his supposedly heroic deeds but also of the authority of ancient myths where precarious not least concerning their conception of gender and gender relations.

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: Empirical
Teacher disagreement score0.886
Threshold uncertainty score0.380

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.021
GPT teacher head0.279
Teacher spread0.258 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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