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Record W2999697181 · doi:10.29173/cons29397

(Labouring Under Strong Mental Derangement) the Wretched Woman

2020· article· en· W2999697181 on OpenAlexaffvenue
Katherine DeCoste

Bibliographic record

VenueConstellations · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicLiterature: history, themes, analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBroadsideEntertainmentReading (process)DraculaHistoryPeriod (music)SociologyMedia studiesCriminologyLawLiteratureArtVisual artsArt historyAestheticsPolitical science

Abstract

fetched live from OpenAlex

Single-sheet, cheap-to-print publications popularized in urban centres in the seventeenth and eighteenth centuries, broadsides were used to disseminate knowledge and entertainment among the common reading classes of England. Murder broadsides were a particularly common genre during the Victorian period in the mid-to-late-nineteenth century, and while the majority of these focused on the downfalls of male criminals, a significant number of publications concerning female murderers survives. Studying how broadsides were produced, read, and shared, especially in London, this paper examines the significance of their representations of female murderers. Ultimately, murder broadsides about women embodied the anxieties of the Victorian age. In the city, social boundaries were pushed, crossed, and blurred relentlessly; broadsides and their representations of women were active expressions of and responses to such anxieties. But while the tendency of broadsides was towards “moral conservativism” which sought to condemn violent crime, promote sexual purity, and sanctify chaste mothers and wives, broadsides also afforded the women they portrayed a certain notoriety and voice, complicating the common reading of the broadside as a prescriptive or even repressive document.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.897
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.050
GPT teacher head0.227
Teacher spread0.177 · 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 teacher head, not a consensus.

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
Published2020
Admission routes2
Has abstractyes

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