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Record W1491515612 · doi:10.1017/cbo9780511635496

The Seduction Narrative in Britain, 1747–1800

2009· book· en· W1491515612 on OpenAlexaff
Katherine Binhammer

Bibliographic record

VenueCambridge University Press eBooks · 2009
Typebook
Languageen
FieldArts and Humanities
TopicLiterature: history, themes, analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNarrativeLiteratureNew HistoricismBalladMemoirHistoricismContext (archaeology)FeminismAppealArtHistoryGender studiesSociologyPoetry

Abstract

fetched live from OpenAlex

Eighteenth-century literature displays a fascination with the seduction of a virtuous young heroine, most famously illustrated by Samuel Richardson's Clarissa and repeated in 1790s radical women's novels, in the many memoirs by fictional or real penitent prostitutes, and in street print. Across fiction, ballads, essays and miscellanies, stories were told of women's mistaken belief in their lovers' vows. In this book Katherine Binhammer surveys seduction narratives from the late eighteenth century within the context of the new ideal of marriage-for-love and shows how these tales tell varying stories of women's emotional and sexual lives. Drawing on new historicism, feminism, and narrative theory, Binhammer argues that the seduction narrative allowed writers to explore different fates for the heroine than the domesticity that became the dominant form in later literature. This study will appeal to scholars of eighteenth-century literature, social and cultural history, and women's and gender studies.

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 score0.044
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0090.017
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.015
GPT teacher head0.180
Teacher spread0.165 · 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

Citations42
Published2009
Admission routes1
Has abstractyes

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