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Record W4400650952 · doi:10.1080/09699082.2024.2375894

The Gulf Between Heroine and Woman: How <i>The Cry’s</i> Oppositional Double Structure Challenges and Educates Readers

2024· article· en· W4400650952 on OpenAlexaff
Veronica Litt

Bibliographic record

VenueWomen s Writing · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicThemes in Literature Analysis
Canadian institutionsCape Breton University
Fundersnot available
KeywordsHistoryPsychology

Abstract

fetched live from OpenAlex

This article argues that the key to the experimental novel The Cry: A New Dramatic Fable (1754) by Sarah Fielding and Jane Collier lies in the contrasting temporalities of the text’s two genres: the endless debate in the frame narrative and the resolved marriage plot narrated by the heroine Portia. By placing repetition and progression side by side, Fielding and Collier emphasize the gulf between the pain of lived experience and the illusory comfort provided by fictional convention. Amid eighteenth-century literary debates on whether didactic texts should favor realism or idealism, The Cry insists that truly educational novels must represent womanhood pragmatically – as rife with oppression, frustration, and repetition. Through formal features, the co-authors use pace and duration to force their audience to experience the pain of womanhood in real time, then propose a way forward through their heroine’s progressive neologisms. Drawing on Sarah Fielding’s literary criticism, responses to The Cry by eighteenth-century readers, and feminist theory, this essay examines how the novel critiqued the social utility of conventional domestic fiction and exposed the true experience of womanhood.

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)0.004
metaresearch head score (Gemma)0.010
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: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0130.028
Scholarly communication0.0120.008
Open science0.0010.006
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0050.001

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 head0.026
GPT teacher head0.239
Teacher spread0.213 · 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
Published2024
Admission routes1
Has abstractyes

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