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Record W2620219822 · doi:10.5539/ells.v7n2p139

Misogyny or Feminism? A Probe into Hawthorne and His The Scarlet Letter

2017· article· en· W2620219822 on OpenAlexvenueno aff
Yueming Wang

Bibliographic record

VenueEnglish Language and Literature Studies · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Studies and Interdisciplinary Research
Canadian institutionsnot available
Fundersnot available
KeywordsPatriarchyCharacter (mathematics)WifeFeminismLiteraturePsychoanalysisSociologyGender studiesPhilosophyArtPsychologyTheology

Abstract

fetched live from OpenAlex

Nathaniel Hawthorne’s The Scarlet Letter has been focused onby critics from different aspects due to his ambiguity used in the novel. Hawthorne himself has been doubted as to whether he is a misogynist or a feminist when describing the female character, Hester Prynne. This article supports the idea that Hawthorne holds the idea offeminism in his work The Scarlet Letter. A writer who mirrors Hester’s life as his own cannot be a misogynist; a writer who honors a woman’s rebelling against patriarchy cannot be a misogynist; a writer who has a beloved wife and mother cannot be a misogynist. Harmonic family relationships, sympathetic character descriptions, and mild demonstrations against patriarchy all prove that Hawthorne is not a misogynist, but a feminist. Hawthorne depicts through four aspects on Hester’s life, Hester’s rebel, Hawthorne’s own family relationship to advocate feminism in his novel.

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)0.006
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 score0.010
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0100.021
Scholarly communication0.0070.005
Open science0.0010.003
Research integrity0.0030.006
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 head0.038
GPT teacher head0.323
Teacher spread0.286 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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