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Record W2327869344 · doi:10.1177/0920203x12466206

The growth of a Taiwanese Buddhist association in China: Soft power and institutional learning

2013· article· en· W2327869344 on OpenAlexaff
André Laliberté

Bibliographic record

VenueChina Information · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicReligion and Society Interactions
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsChinaBuddhismGovernment (linguistics)Power (physics)Public administrationPolitical scienceDevelopment economicsSociologyEconomicsLawTheology

Abstract

fetched live from OpenAlex

This article looks at Ciji (Tzu Chi), a Taiwanese Buddhist charity which has been active in China since 1991. Ciji’s presence in China is all the more remarkable in view of outbreaks of crises in relations across the Taiwan Strait as well as the religious nature of the organization. The article first addresses the issue of Taiwan’s soft power in its relations with China and suggests the possibility that Ciji’s activities in Taiwan have shown China the benefits of a liberal policy towards religion in that charitable activities carried out by religious organizations complement the government’s social policies. The second section chronicles Ciji’s presence in China since 1991 and shows that local governments have their own reasons for welcoming Ciji’s volunteers. The third section compares and contrasts state approaches in China and Taiwan with respect to the provision of social services by religious organizations and notes that even if local governments in China are learning about the benefits of a more open policy in their dealings with Ciji, the central government has not adopted the liberal approach of the Taiwanese government in the regulation of religion.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.005
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.001
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 head0.003
GPT teacher head0.234
Teacher spread0.231 · 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

Citations22
Published2013
Admission routes1
Has abstractyes

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