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Record W4223498756 · doi:10.5281/zenodo.6454257

THE FEMINIST NATURE OF THE WORKS OF M. ATWOOD (BASED ON THE NOVEL "THE HANDMAID'S TALE")

2022· paratext· en· W4223498756 on OpenAlexaboutno aff
O. Radchuk

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typeparatext
Languageen
FieldSocial Sciences
TopicDiscourse Analysis and Cultural Communication
Canadian institutionsnot available
Fundersnot available
KeywordsArtLiteratureComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

Scientific research is devoted to the gender aspect in English-language literature, in particular in the works of the Canadian writer Margaret Atwood. The consideration of the gender problem is based on the material of fiction, namely on the basis of the novel “The Handmaid's Tale”. This approach makes it possible to reveal and present gender not only as a parameter that reflects the gender identity of the author, but also as a parameter that is an element of the structure of the work of art. Particular attention is paid to creating an artistic image of the main character of the novel, June, that is dominant. Since the genre of the novel is anti-utopia, the action takes place in a fictional totalitarian state called the Republic of Gilead. In that country, all power and all rights belong to the military, women have no rights to own, work, and love. They have only one function left, namely the reproductive one. M. Atwood embodies the best female qualities, the ability to fight for their lives and be an example to others in the image of June. This is a feminist treatise, the author of which defends the rights of women in modern society.

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)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.008
Scholarly communication0.0050.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.038
GPT teacher head0.297
Teacher spread0.258 · 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
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
Published2022
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)Same topicDiscourse Analysis and Cultural CommunicationFrench-language works237,207