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Record W2800413441 · doi:10.1111/glob.12194

Renegotiating religious transnationalism: fractures in transnational Chinese evangelicalism

2018· article· en· W2800413441 on OpenAlexaboutno aff
Jonathan Tam

Bibliographic record

VenueGlobal Networks · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsnot available
Fundersnot available
KeywordsTransnationalismDiasporaEvangelismEthnic groupImmigrationGender studiesSociologyIdentity (music)IdeologyState (computer science)Political sciencePoliticsLawAnthropologyAesthetics

Abstract

fetched live from OpenAlex

Abstract In this article, I question to what extent future generations of immigrants will engage in practices of religious transnationalism through their ethnic institutions. I examine how leaders of the next generation of English‐speaking Chinese Canadian evangelicals made sense of their participation in the Chinese Coordination Centre of World Evangelism, a movement that rallies behind both a pan‐Chinese identity and the belief that the Chinese have a special role in evangelizing the world. I argue that the call to religious mobilization grounded in Chinese ethnicity stands on tenuous ground and propose that linguistic, geographical, generational and ideological fractures may diminish the participation of future generations of the Chinese diaspora in ethnically‐based transnational religious organizations. I conclude that these developments would push ‘negotiated transnational religious networks’ into a state of ‘renegotiation'.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.021
Scholarly communication0.0050.004
Open science0.0010.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.341
Teacher spread0.329 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations3
Published2018
Admission routes1
Has abstractyes

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