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Record W4415981372 · doi:10.63419/sabita.v2i1.37

Diasporic Female Subjectivity and Dissent in Margaret Atwood’s Neo-Victorian Novel Alias Grace

2025· article· W4415981372 on OpenAlexaboutno aff
Sneha Kar Chaudhuri

Bibliographic record

VenueSabita - A Journal of Humanities · 2025
Typearticle
Language
FieldArts and Humanities
TopicShort Stories in Global Literature
Canadian institutionsnot available
Fundersnot available
KeywordsSubjectivityContext (archaeology)ColonialismHybridityForegroundingMainstreamVictorian eraDiasporaVictorian literaturePostcolonialism (international relations)

Abstract

fetched live from OpenAlex

This article will critically discuss the issues of diaspora, migration and subversive female individuality in Margaret Atwood’s neo-Victorian novel Alias Grace (1996). The first part will briefly consider the emerging trends of retro-Victorian, post-Victorian and neo-Victorian fictional responses by contemporary authors to revive and reinvent the Victorian world order. It will then consider how Atwood as a Canadian British writer opposes the grand metanarrative of Victorian imperialism through her subtle critique of British colonization and patriarchy in this novel which deals specifically with nineteenth century Canada. As a neo-Victorian novel, it offers a subversive critique of white Victorian mainstream neo-Victorian fictional texts that revive the British Victorian past with an unambiguous sense of nostalgia, antiquarianism and celebration. Atwood in this novel exposes the precarious and problematic lives of diasporic British women in the Victorian imperial context and exposes the dark underbelly of British racism, sexism and imperialism and renders the Victorian world order as self-contradictory, unjust and essentially problematic. Overall, this article will critically engage with marginalized female criminals and their ambivalent diasporic subjectivity in the historical context of nineteenth century Britain and Canada.

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)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.227
Threshold uncertainty score0.452

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0200.033
Scholarly communication0.0070.002
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.254
Teacher spread0.236 · 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
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

Citations0
Published2025
Admission routes1
Has abstractyes

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