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Record W4281569058 · doi:10.1017/9789048554416

Contesting Chineseness

2022· book· en· W4281569058 on OpenAlexaboutno aff
Sylvia Ang

Bibliographic record

VenueAmsterdam University Press eBooks · 2022
Typebook
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in Asia
Canadian institutionsnot available
Fundersnot available
KeywordsChinaEthnographyEthnic chineseEthnic groupNegotiationCommunismGender studiesPolitical scienceDestinationsGlobalizationGeographySociologyPoliticsAnthropologyLaw

Abstract

fetched live from OpenAlex

Nearly eleven million Chinese migrants live outside of China. While many of these faces of China's globalization headed for the popular Western destinations of the United States, Australia and Canada, others have been lured by the booming Asian economies. Compared with pre-1949 Chinese migrants, most are wealthier, motivated by a variety of concerns beyond economic survival and loyal to the communist regime. The reception of new Chinese migrants, however, has been less than warm in some places. In Singapore, tensions between Singaporean-Chinese and new Chinese arrivals present a puzzle: why are there tensions between ethnic Chinese settlers and new Chinese arrivals despite similarities in phenotype, ancestry and customs? Drawing on rich empirical data from ethnography and digital ethnography, <i>Contesting Chineseness</i> investigates this puzzle and details how ethnic Chinese subjects negotiate their identities in an age of contemporary Chinese migration and China's ascent.

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), Science 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 score0.817
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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.035
GPT teacher head0.252
Teacher spread0.217 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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