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Record W2294512331 · doi:10.17615/hkeg-ts10

Dangerous Liaisons: Narratives of Sexual Danger in the Anglo-American North, 1770–1820

2019· article· en· W2294512331 on OpenAlexfundno aff
Lynn Wood

Bibliographic record

VenueCarolina Digital Repository (University of North Carolina at Chapel Hill) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsNarrativeHistoryCriminologyPolitical scienceSociologyGender studiesArtLiterature

Abstract

fetched live from OpenAlex

In this dissertation, I seek to understand why Anglo-Americans in the early Republic became preoccupied with stories about sex, especially narratives in which sex was perceived as dangerous. Historians of sexuality have identified the late eighteenth century as an important moment in the transformation of sexual ideologies. Sex became increasingly politicized and connected to ideas about nationhood and citizenship. The regulation of sex was part of a larger transition in which populations were regulated, categorized, and controlled. The Anglo-American North is a dynamic time and place to examine these larger trends - this was the time when white Americans were actively creating a national culture, one that included white people and excluded blacks and aboriginal peoples. I show that, starting in the 1770s, Anglo-Americans increasingly published stories in newspapers, magazines, and novels, in which people were punished for illicit sexual acts. I argue that this increased attention was connected to ideas of Republican virtue. Narratives of sexual danger reflected a belief that immorality would undermine the family, the basic unit of the Republic. Men and women shared in the responsibility of preserving the Republic by controlling their passions.

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)0.003
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.756
Threshold uncertainty score0.486

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0330.017
Scholarly communication0.0050.005
Open science0.0010.005
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.008
GPT teacher head0.189
Teacher spread0.182 · 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 designQualitative
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
Published2019
Admission routes1
Has abstractyes

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Same venueCarolina Digital Repository (University of North Carolina at Chapel Hill)Same topicCanadian Identity and HistoryFrench-language works237,207