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Record W2804915311

International Ladies' Garments Workers’ Union

2015· book-chapter· en· W2804915311 on OpenAlexaboutno aff
Ashok Kumar

Bibliographic record

VenueBIROn (Birkbeck, University of London) · 2015
Typebook-chapter
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationPoliticsChinese americansGender studiesEthnic groupPolitical scienceThe artsRacismEveryday lifeClothingIdentity (music)SociologyLawAestheticsArt
DOInot available

Abstract

fetched live from OpenAlex

Book synopsis: This in-depth historical analysis highlights the enormous contributions of Chinese Americans to the professions, politics, and popular culture of America, from the 19th century through the present day.
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\nWhile the number of Chinese Americans has grown very rapidly in the last decade, this group has long thrived in the United States in spite of racism, discrimination, and segregation. This comprehensive volume takes a global view of the Chinese experience in the Americas. While the focus is on Chinese Americans in the United States, author Jonathan H. X. Lee also explores the experiences of Chinese immigrants in Canada, Mexico, and South America. He considers why the Chinese chose to leave their home country, where they settled, and how the distinctive Chinese American identity was formed.
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\nThis volume is organized into four sections: historical overview; political and economic life; cultural and religious life; and literature, the arts, and popular culture. Detailed essays capture the essence of everyday life for this immigrant group as they assimilated, established communities, and interacted with other ethnic groups. Alphabetically arranged entries describe the political, social, and religious institutions begun by Chinese Americans and explores their roles as business owners, activists, and philanthropic benefactors for their communities.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.461
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.041
GPT teacher head0.250
Teacher spread0.209 · 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
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

Citations0
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueBIROn (Birkbeck, University of London)Same topicMigration, Ethnicity, and EconomyFrench-language works237,207