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Record W4246574831 · doi:10.3138/uhr.42.02.04

Sex, Intimacy, and Desire among Men of Chinese Heritage and Women of Non-Asian Heritage in Toronto, 1910–1950

2014· article· en· W4246574831 on OpenAlexvenueaboutno aff
Elise Chenier

Bibliographic record

VenueUrban History Review · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsChinatownGender studiesWhite (mutation)ChinaSociologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Because few women of Chinese heritage came to Canada, Chinese migrant communities before 1950 are described as “bachelor societies.” Sojourners’ own ambition to return home with more wealth, the imposition of ever-increasing head taxes on migrants from China, the 1923 Chinese Exclusion Act, and deeply entrenched racism toward people of Chinese heritage meant that the vast majority were doomed to live their lives without the emotional, material, or domestic support or companionship provided by wives and children. They were de facto bachelors, if not bachelors in fact. New research, however, shows that since the 1910s young men of Chinese heritage carved out spaces for themselves in Toronto’s urban sexual culture, and young white women a space for themselves in Toronto’s Chinatown. During the first half of the twentieth century, many men of Chinese heritage enjoyed sex, companionship, love, and family life. Perhaps as many as a third were married to or lived common-law with women of white heritage, and many more frequently engaged in sexual and intimate relationships with sex workers they sometimes sought as long-term companions. The evidence presented here challenges the current perception that “Chinese bachelors” lived sexless, loveless lives. These relationships were not without controversy, of course, but many people within the community accepted them, and women of white heritage, including sex workers, were integrated into the community in diverse ways.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.829
Threshold uncertainty score0.801

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.231
Teacher spread0.223 · 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.

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

Citations2
Published2014
Admission routes2
Has abstractyes

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