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Record W4313506847 · doi:10.53032/tcl.2020.5.2.13

Quest for the Self in Margaret Atwood’s Surfacing: An Eco feminist Approach

2020· article· en· W4313506847 on OpenAlexaboutno aff
Jitendra Kumar Bharti

Bibliographic record

VenueThe Creative Launcher · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicUtopian, Dystopian, and Speculative Fiction
Canadian institutionsnot available
Fundersnot available
KeywordsEcofeminismPatriarchyCreaturesNatural (archaeology)Power (physics)WifeSociologyGender studiesEnvironmental ethicsHistoryPhilosophyLawPolitical scienceArchaeology

Abstract

fetched live from OpenAlex

The particular paper focuses on the analysis of patriarchal domination and capitalist’s exploitation of women and nature. Through the ecofeminism point of view, I have made a depth study of Margaret Atwood’s Surfacing (1972), and found out that power, patriarchy and domination have oppressed both women and nature. The unnamed narrator, who is protagonist of the novel, symbolizes the natural and environmental destruction by the capitalists. Anna, David’s wife in the novel, represents women’s exploitation in the patriarchal society. The impact of ecofeminism is clearly discern in the novel when the unnamed narrator returns to natural world of the Quebec Island where she was grown up and associate her with nature. She burns all the stuffs that she had and reminded her of past, and decides to lead a life like the creatures of natural world. She rejects the artificial life and quest of her real self in the natural world.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0160.038
Scholarly communication0.0110.005
Open science0.0010.003
Research integrity0.0040.004
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 head0.079
GPT teacher head0.259
Teacher spread0.180 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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