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Article: Decoding Political Trust in China: A Machine Learning Analysis

TitleDecoding Political Trust in China: A Machine Learning Analysis
Authors
KeywordsChina
machine learning
political trust
trust in the central government
trust in the Centre
trust in the local government
Issue Date2022
Citation
China Quarterly, 2022, v. 249, p. 1-20 How to Cite?
AbstractSurvey results inflate political trust in China if the observed trust in the central government is mistaken for the latent trust in the Centre. The target of trust in the country is the Centre, which is ultimately the top leader. The critical issue domain for assessing the Centre's trustworthiness is policy implementation rather than policymaking. The Centre's trustworthiness has two dimensions: commitment to good governance and the capacity to discipline local officials. Observed trust in the central government indicates trust in the Centre's commitment, while observed trust in the local government reflects confidence in the Centre's capacity. A machine learning analysis of a national survey reveals how much conventional reading overestimates political trust. At first glance, 85 per cent of the respondents trust the central government. Upon further inspection, 18 per cent have total trust in the Centre, 34 per cent have partial trust and 33 per cent are sceptical.
Persistent Identifierhttp://hdl.handle.net/10722/344438
ISSN
2023 Impact Factor: 2.5
2023 SCImago Journal Rankings: 0.716

 

DC FieldValueLanguage
dc.contributor.authorLi, Lianjiang-
dc.date.accessioned2024-07-31T03:03:30Z-
dc.date.available2024-07-31T03:03:30Z-
dc.date.issued2022-
dc.identifier.citationChina Quarterly, 2022, v. 249, p. 1-20-
dc.identifier.issn0305-7410-
dc.identifier.urihttp://hdl.handle.net/10722/344438-
dc.description.abstractSurvey results inflate political trust in China if the observed trust in the central government is mistaken for the latent trust in the Centre. The target of trust in the country is the Centre, which is ultimately the top leader. The critical issue domain for assessing the Centre's trustworthiness is policy implementation rather than policymaking. The Centre's trustworthiness has two dimensions: commitment to good governance and the capacity to discipline local officials. Observed trust in the central government indicates trust in the Centre's commitment, while observed trust in the local government reflects confidence in the Centre's capacity. A machine learning analysis of a national survey reveals how much conventional reading overestimates political trust. At first glance, 85 per cent of the respondents trust the central government. Upon further inspection, 18 per cent have total trust in the Centre, 34 per cent have partial trust and 33 per cent are sceptical.-
dc.languageeng-
dc.relation.ispartofChina Quarterly-
dc.subjectChina-
dc.subjectmachine learning-
dc.subjectpolitical trust-
dc.subjecttrust in the central government-
dc.subjecttrust in the Centre-
dc.subjecttrust in the local government-
dc.titleDecoding Political Trust in China: A Machine Learning Analysis-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1017/S0305741021001077-
dc.identifier.scopuseid_2-s2.0-85120915079-
dc.identifier.volume249-
dc.identifier.spage1-
dc.identifier.epage20-
dc.identifier.eissn1468-2648-

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