Decoding Political Trust in China: A Machine Learning Analysis

被引:18
|
作者
Li, Lianjiang [1 ]
机构
[1] Chinese Univ Hong Kong, Dept Govt & Publ Adm, Hong Kong, Peoples R China
来源
CHINA QUARTERLY | 2022年 / 249卷
关键词
political trust; trust in the Centre; trust in the central government; trust in the local government; machine learning; China; STATE; GOVERNMENT; SUPPORT; RESILIENCE; EDUCATION; POLICY; PARTY;
D O I
10.1017/S0305741021001077
中图分类号
K9 [地理];
学科分类号
0705 ;
摘要
Survey 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.
引用
收藏
页码:1 / 20
页数:20
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