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Record W1531312615

MARGARET ATWOOD’S DIVIDED SELF

2011· article· en· W1531312615 on OpenAlexaboutno aff
Kate Moss

Bibliographic record

VenueScholarWorks -A service of University of Vermont Libraries (University of Vermont) · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicLiterature: history, themes, analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHistoryArt
DOInot available

Abstract

fetched live from OpenAlex

"Margaret Atwood‘s Divided Self" explores four novels by celebrated Canadian author, Margaret Atwood: Lady Oracle, Surfacing, Alias Grace, and The Robber Bride. Although others have discussed the reoccurring themes of disunity and duality in Atwood‘s work, these explorations have not addressed some of her newest novels and have taken a very limited approach to reading and understanding Atwood‘s theme of the divided self. This study opens up a literary "conversation" about Atwood‘s theme of the divided self by examining the protagonists of these select novels by using different branches of theory and thought to fully explore this issue. To conquer their double or multiple identities Atwood‘s protagonists in these novels must take two actions: 1) Accept their double/multiple identities as a part of themselves and 2) transcend this position and the resulting ―hauntings‖ by their mothers (or their decision to choose a replacement female "mother" figure) by becoming mothers themselves. The introduction chapter "The Author as 'Slippery Double'" explores Atwood‘s position as a "slippery (divided) subject" between her writing/social and interior selves. Chapter one, "Canadian Women: Nature, Place, and the Divided Other in Atwood‘s Works" explores the role of nature, place, and femininity in Atwood‘s divided protagonists. Chapter two, "The Uncanny Double: Haunting Entities and the Divided Self in Atwood‘s Fiction" contains the main argument and explores the role of the uncanny in Atwood‘s works. Although I explore these four novels most thoroughly explored, this theme runs throughout Atwood‘s entire body of work. Although I mostly use close readings of the primary texts, I also ground my argument in the work of theorists in several fields of thought including Sigmund Freud, Louis Althusser, George H. Mead, and Jacques Lacan.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.558
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.004
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.023
GPT teacher head0.149
Teacher spread0.126 · 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.

Study designQualitative
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
Published2011
Admission routes1
Has abstractyes

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