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Brokering Belonging

2010· book· en· W4250808920 on OpenAlexaboutno aff
Lisa Rose Mar

Bibliographic record

VenueOxford University Press eBooks · 2010
Typebook
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationMainstreamPoliticsPower (physics)Political scienceEthnic groupFrontierChinese communityChinese americansGender studiesSociologyPolitical economyChinaLaw

Abstract

fetched live from OpenAlex

This work traces several generations of Chinese "brokers," ethnic leaders who acted as intermediaries between the Chinese and Anglo worlds of Canada. At the time, most Chinese could not vote and many were illegal immigrants, so brokers played informal but necessary roles as representatives to the larger society. Brokers' work reveals the changing boundaries between Chinese and Anglo worlds and how tensions among Chinese shaped them. By reinserting Chinese back into mainstream politics, this book alters common understandings of how legally "alien" groups helped create modern immigrant nations. Over several generations, brokers deeply embedded Chinese immigrants in the larger Canadian, U.S., and Chinese politics of their time. On the nineteenth-century Western frontier, Chinese businessmen competed with each other to represent their community. By the early 1920s, a new generation of brokers based in social movements challenged traditional brokers, shifting the power dynamic within the Chinese community. During the Second World War, social movements helped reconfigure both brokerage and race relations. Based on new Chinese language evidence, this book recounts history from the "middle," a view that is neither bottom up nor top down. Through brokerage, Chinese wielded considerable influence, navigating a period of anti-Asian sentiment and exclusion throughout society. Consequently, Chinese immigrants became significant players in race relations, influencing policies that affected all Canadians and Americans.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.888
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.192
Teacher spread0.181 · 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

Citations45
Published2010
Admission routes1
Has abstractyes

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