MétaCan
Menu
Back to cohort
Record W2588423132 · doi:10.1177/0192512116677587

Local–national political trust patterns: Why China is an exception

2017· article· en· W2588423132 on OpenAlexafffund
Cary Wu, Rima Wilkes

Bibliographic record

VenueInternational Political Science Review · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsUniversity of British Columbia
FundersUniversity of California, San DiegoNational Research University Higher School of EconomicsUniversity of British ColumbiaRiksbankens JubileumsfondEast China University of Science and Technology
KeywordsChinaPoliticsBlind trustGovernment (linguistics)Local governmentNorm (philosophy)Central governmentPolitical scienceSurvey data collectionPublic trustPublic administrationPublic relationsLawStatistics

Abstract

fetched live from OpenAlex

Is political trust in China anomalous? In most countries there are systematic differences in the level of trust in national and local government that take one of three patterns. In some countries, individuals trust the national government more than local government (hierarchical trust); in others individuals trust local government more than national government; while in some countries individuals trust both levels of government equally. Of 11 Asian societies, the only country where hierarchical trust predominates is China. Elsewhere the norm is to put more trust in local levels of government. While previous studies have described the pattern of trust in China, no study has considered relative trust as an outcome or comparatively. Taking advantage of the 2006 and 2010 Asian Barometer Survey data we consider whether the hierarchical trust pattern in China is the result of political control, culture, and/or performance. We find that political control explains the hierarchical trust pattern in China.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.070
GPT teacher head0.429
Teacher spread0.359 · 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 designObservational
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

Citations130
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueInternational Political Science ReviewSame topicSocial Capital and NetworksFrench-language works237,207