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Record W4399590476 · doi:10.1080/01419870.2024.2354886

Chinese voluntary associations in the diaspora: ethnicity, gender and the (re)making of ancestral communities

2024· article· en· W4399590476 on OpenAlex
Ningning Chen, Emily Hertzman, Sylvia Ang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEthnic and Racial Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of China
KeywordsDiasporaEthnic groupVoluntary associationGender studiesSociologyPolitical scienceAnthropologyLaw

Abstract

fetched live from OpenAlex

Recent studies of Chinese voluntary associations (CVAs) have attempted to highlight the theoretical significance of CVAs for understandings of community (re)making. However, the power dynamics inherent in community (re)making has rarely been expounded. In recognition of this, we weave together case studies across countries to explore the complex power relations played out in and through the transformation of CVAs. Collectively, CVAs are understood as ever-changing, heterogeneous ancestral communities composed of common ancestral ties be it origin, locality, surname, religion or language. We aim to contribute to existing scholarship on ethnic and diaspora studies through focusing on CVAs in three ways: (1) foreground CVAs as sites of power relations through unpacking ethnic relations and gender hierarchies; (2) illuminate Chinese diaspora transnationalism beyond political-economic perspectives; and (3) examine the contemporaneous transformation of ethnic Chinese communities in shifting times, including amidst China's “rise” as a global power.

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.

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)0.003
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.454
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.128
GPT teacher head0.415
Teacher spread0.287 · 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