Bibliographic record
Abstract
"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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.015 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".