Partisan Bias and the Bayesian Ideal in the Study of Public Opinion

被引:116
作者
Bullock, John G. [1 ]
机构
[1] Yale Univ, New Haven, CT 06520 USA
关键词
MODEL; UNCERTAINTY;
D O I
10.1017/S0022381609090914
中图分类号
D0 [政治学、政治理论];
学科分类号
0302 ; 030201 ;
摘要
Bayes' Theorem is increasingly used as a benchmark against which to judge the quality of citizens' thinking, but some of its implications are not well understood. A common claim is that Bayesians must agree more as they learn and that the failure of partisans to do the same is evidence of bias in their responses to new information. Formal inspection of Bayesian learning models shows that this is a misunderstanding. Learning need not create agreement among Bayesians. Disagreement among partisans is never clear evidence of bias. And although most partisans are not Bayesians, their reactions to new information are surprisingly consistent with the ideal of Bayesian rationality.
引用
收藏
页码:1109 / 1124
页数:16
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