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dc.contributor.authorAxel, Constant-
dc.date.accessioned2023-04-27T07:29:11Z-
dc.date.available2023-04-27T07:29:11Z-
dc.date.issued2023-
dc.identifier.urihttps://link.springer.com/article/10.1007/s10506-023-09357-8-
dc.identifier.urihttps://dlib.phenikaa-uni.edu.vn/handle/PNK/8357-
dc.descriptionCC BYvi
dc.description.abstractBayesian approaches to legal reasoning propose causal models of the relation between evidence, the credibility of evidence, and ultimate hypotheses, or verdicts. They assume that legal reasoning is the process whereby one infers the posterior probability of a verdict based on observed evidence, or facts. In practice, legal reasoning does not operate quite that way. Legal reasoning is also an attempt at inferring applicable rules derived from legal precedents or statutes based on the facts at hand. To make such an inference, legal reasoning follows syllogistic logic and first order transitivity.vi
dc.language.isoenvi
dc.publisherSpringervi
dc.subjectBayesian modelvi
dc.titleA Bayesian model of legal syllogistic reasoningvi
dc.typeBookvi
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