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Record W7112834480

Zenia’s function as the freudian Id in Margaret Atwood’s The Robber Bride

2025· dissertation· en· W7112834480 on OpenAlexaboutno aff

Bibliographic record

VenueDSpace repository (University of Tartu) · 2025
Typedissertation
Languageen
FieldArts and Humanities
TopicUtopian, Dystopian, and Speculative Fiction
Canadian institutionsnot available
Fundersnot available
KeywordsFreudian slipScholarshipPsychoanalytic theoryFunction (biology)Freudian theoryEmpirical research
DOInot available

Abstract

fetched live from OpenAlex

Published in 1993, Canadian author Margaret Atwood’s The Robber Bride and its divisive main antagonist, Zenia, continue to inspire lively critical discussion. Despite Atwood’s reservations about interpretations rooted in gender binaries, the existing research has primarily focused on Zenia’s status as a woman while overlooking frameworks like Sigmund Freud’s psychoanalysis, especially his theory of the id, the ego, and the super-ego. Because of this, the thesis aims to demonstrate how Zenia aligns with the Freudian id and examine what this reveals about her function in the novel. The introduction provides a background on the previous reception of The Robber Bride, a brief summary of the novel, and an overview of Atwood’s views on feminist readings of her works. The literature review outlines the three main approaches to analysing Zenia in the previous scholarship and discusses the central concepts of Freud’s psychoanalytic model of the mind. The first three subsections of the empirical study examine excerpts from the novel to provide proof of Zenia functioning as the Freudian id, followed by a comparison of the findings of the id approach to those of previous interpretations of Zenia in the fourth subsection. The conclusion summarises the findings of the thesis. Keywords: Margaret Atwood, The Robber Bride, Canadian literature, Sigmund Freud, psychoanalysis

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.829
Threshold uncertainty score0.404

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0250.039
Scholarly communication0.0090.003
Open science0.0010.003
Research integrity0.0020.004
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 head0.010
GPT teacher head0.182
Teacher spread0.172 · 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 designTheoretical or conceptual
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

Citations0
Published2025
Admission routes1
Has abstractyes

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