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The Normative and Material Foundations of Judicial Confidence in Bolivia

Published online by Cambridge University Press:  28 August 2019

José Kaire*
Affiliation:
José Kaire is a doctoral candidate at the University of Minnesota.
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Abstract

What allows unpopular judiciaries to gain the trust of the public? Some suggest that judicial confidence depends on procedural integrity. Others emphasize the importance of ideological congruence between the court and the public. This article examines the explanatory power of these two leading hypotheses while also paying closer attention to the moderating effects of political and economic inclusion. It finds that confidence in the judiciary is driven by normative considerations when inclusion is high, but by ideological proximity when inclusion is low. The findings highlight that institutional support does not emerge from a single causal path. Instead, inequalities in the economic and political structure make people trust institutions for different—and sometimes contrasting—reasons.

Information

Type
Research Article
Copyright
© University of Miami 2019 
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Table 1. Perceived Judicial Independence by Department and Partisan Affiliation

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Figure 1. Probability of Supporting Judicial Independence by Degree of Marginalization

Notes: Estimates from a logistic fixed effects regression controlling for years of education, political knowledge, partisanship, and ideological distance from the TSJ. Survey question: “Do you think that the judiciary should be or should not be independent from the executive in order to be more effective?” Marginalization is measured through factor scores of the political satisfaction and economic well-being variables explained in the text.Source: The AmericasBarometer by the Latin American Public Opinion Project (LAPOP), www.LapopSurveys.org
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Table 2. Normative and Instrumental Predictors of Confidence in the TSJ

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Figure 2. Predicted Judicial Confidence by Procedural and Ideological Satisfaction

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Figure 3. Marginal Effect of Explanatory Variables at Varying Degrees of Marginalization

Notes: Low and high refer to the 10th and 90th percentiles of the respective variables. Point estimates are plotted along their 85% (light gray), 80%, 70%, 60%, and 50% (dark gray) confidence intervals to adjust for potential false negatives when coefficients approach zero. The interactions (differences between levels of marginalization) are all significant at the 95% level.
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