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Making Marriage Modern

2009· book· en· W2478998580 on OpenAlexaff
Christina Simmons

Bibliographic record

Venuenot available
Typebook
Languageen
FieldArts and Humanities
TopicHistorical Studies on Reproduction, Gender, Health, and Societal Changes
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsGender studiesFemininityHuman sexualitySociologyRomancePleasurePsychology

Abstract

fetched live from OpenAlex

Abstract As a modern female style undermined a Victorian motherhood‐centered ideal, whites and African Americans debated conceptions of women's sexuality and marriage. In the 1910s social hygiene reformers anxious about venereal disease called for scientific sex education but still romanticized motherhood, while sex radicals demanded birth control, free love, or the right to interracial relationships or homosexuality. The book emphasizes more conventional reformers, who by the 1920s hoped to contain the potential for modern women's independence from men and marriage in “companionate marriage.” This incorporated birth control, easier divorce, and intensified sexual intimacy. The most popular version involved free‐spirited flappers who did not seriously challenge male authority or women's ultimate focus on motherhood. Some more equitable minority versions were African American partnership marriage, which included wives' employment, and feminist marriage, in which white and black women imagined a more thoroughgoing equality of work and sex. Sexual advice literature flooded onto the market in the 1930s, offering women conflicting messages about achieving sexual pleasure but also pleasing husbands. Despite the unsettling of an older femininity, deep and persistent structural inequalities between men and women limited efforts to create gender parity in sex and marriage. Yet these cultural battles subverted patriarchal culture and raised women's expectations of marriage in ways that grounded second‐wave feminist claims.

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)0.005
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 score0.027
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0080.017
Scholarly communication0.0060.006
Open science0.0010.008
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0270.006

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 head0.151
GPT teacher head0.290
Teacher spread0.140 · 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

Citations103
Published2009
Admission routes1
Has abstractyes

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