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Record W4236324680 · doi:10.3138/ecf.24.1.55

True Crime: Contagion, Print Culture, and Herbert Croft's <i>Love and Madness; or, A Story Too True</i>

2011· article· en· W4236324680 on OpenAlexvenueno aff
Kelly McGuire

Bibliographic record

VenueEighteenth-Century Fiction · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicCrime and Detective Fiction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSensibilityNarrativePassionLiteraturePsychoanalysisMythologyCharacter (mathematics)Representation (politics)SubjectivitySociologyPsychologyPhilosophyArtEpistemologyLawSocial psychology

Abstract

fetched live from OpenAlex

Herbert Croft fictionalized an eighteenth-century crime of passion in his epistolary novel, Love and Madness; or, A Story Too True (1780); in his retelling, Croft presents James Hackman, the suicidal murderer of Martha Ray in 1779, as both the victim of various forms of contagion—social, textual, and medical—and as an exemplar of a kind of self-sacrificing sensibility that enables him to overcome the stigma of suicide. Croft's representation of the crime draws heavily upon Goethe's controversial The Sorrows of Young Werther (1774) and implicates this text in Hackman's suicidal subjectivity. Croft frames his anti-Wertherian story as a Christian heroic and nationalist narrative dedicated to dismantling the myth of the “English Malady” of suicidal melancholy. Croft struggles to reposition suicide as a transnational rather than a national phenomenon. The historical figure of James Hackman emerges out of Croft's treatment as an unlikely means of revaluing national character, interests, and sensibility.

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)0.003
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 score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.031
Scholarly communication0.0080.004
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.046
GPT teacher head0.234
Teacher spread0.188 · 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

Citations5
Published2011
Admission routes1
Has abstractyes

Explore more

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