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Knowledge, probability, and credibility
Author(s) -
Schum David A.
Publication year - 1989
Publication title -
journal of behavioral decision making
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 76
eISSN - 1099-0771
pISSN - 0894-3257
DOI - 10.1002/bdm.3960020104
Subject(s) - credibility , inference , bayes' theorem , value (mathematics) , scholarship , relation (database) , epistemology , psychology , source credibility , computer science , bayesian probability , artificial intelligence , political science , law , machine learning , data mining , philosophy
This paper concerns study of the credibility of human sources of evidence and its relation to the inferential value of testimony they provide. From a certain view of 'knowledge' in epistemology comes the suggestion that credibility assessment can be construed as a cascaded inference in which attributes of human source credibility are identified. Scholarship from evidence law in jurisprudence suggests an evidential basis for credibility assessment in terms of these attributes. Applying Bayes' rule to this cascaded inference offers a way of expressing and combining credibility‐related beliefs in the process of assessing the inferential value of evidence.