| Description |
Bayes’ Theorem is increasingly used as a benchmark against which to judge the quality of citizens, 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.
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ICAR Research Data Repository for Knowledge Management