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We use the Dirichlet distribution in a new application as a tractable model for the variability between personal prior probability vectors over a large population of persons. Given a common realized likelihood function, the resulting population distribution of coherent personal posterior probability vectors is analyzed and found to have mixed moments expressible as a one-dimensional integral. Implications for the study of the evolution of scientific knowledge are discussed.
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