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Stratified Political Trust in a Nondemocratic Society: Magnitude, Forms, and Sources of Political Trust in Urban China

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Abstract

There has been a vibrant literature on political trust in China. However, a closer examination of this large literature points to no clear consensus on the measurement and sources of such support. To contribute to this literature, this study is to explore the magnitude, forms, and sources of political trust in urban China. In this study, we explore an alternative approach to the study of political trust, which treats political trust along two straightforward yet distinct dimensions: horizontal and vertical dimensions. Based on this approach, we find that people’s political trust in urban China varies vertically, across different levels of government institutions (e.g., central and local governments), while it changes little horizontally, among different government institutions at the same level. Moreover, we find that the formation of political trust in each level of government institutions — along the vertical dimension — is shaped by a distinct combination of sociopolitical factors. We also explore some important theoretical and political implications from our findings.

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Notes

  1. For definition of political trust, see also the works by Coleman [16] and Levi and Stoker [49].

  2. There is no people’s congress at the township (also jiedao) level.

  3. To further test the strength of the latent structures emerged from EFA, we also employ the technique of confirmatory factor analysis (CFA). A great advantage of CFA is its ability to utilize the full information in the dataset via maximum-likelihood estimation rather than listwise deletion of missing data. The results of CFA also suggest that the two components are strongly coherent.

  4. The sources of our respondents’ political trust are measured by the two factor scores based on our EFA analysis explained in Section IV.

  5. For a welcoming exception, see Jennings [42].

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Appendix: Additional Factor Analysis Based on Data from the World Value Survey

Appendix: Additional Factor Analysis Based on Data from the World Value Survey

As we emphasized in the main text, our survey instruments are by no means exhaustive. Given practical constraints like the length of questionnaire, we focus on key political institutions across different levels, that is, the Party, the government (i.e., administrative bodies), and the people’s congress (i.e., the legislative bodies) across the national, provincial, and county levels. It should be noted inclusion of additional political institutions like procuratorate bodies, police, and propaganda bodies could strengthen our analysis. However, such inclusion would increase the length of questionnaire markedly. It is well possible that inclusion of additional political institutions might affect our results, particularly when we turn the court and police, which have more direct contact with citizens.

We then conducted additional analysis using data from the most the most recent the World Values Survey (WVS Wave 7 2017–2020). WVS along with many other studies failed to recognize both the vertical and horizontal dimensions of political and did not ask any questions related to political institutions at lower levels (e.g., the provincial and county levels) in China. Instead, WVS was able to include more political institutions like the courts, police, and civil service (i.e., the administrative body). The results from our analysis of WVS data are consistent with our main arguments, that is, people in China generally do not distinguish between political institutions at the same level but harbor markedly different attitudes towards different levels. In short, vertical trust matters in China.

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Scree plot of contribution by latent dimensions

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Biplot based on PCA analysis

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Contribution by individual variables

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Huhe, N., Chen, J. Stratified Political Trust in a Nondemocratic Society: Magnitude, Forms, and Sources of Political Trust in Urban China. J OF CHIN POLIT SCI 29, 55–75 (2024). https://doi.org/10.1007/s11366-023-09844-4

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