The Bayesian perspective is based on conditioning related to reported evidence that is considered to be certain. What is called ‘Radical Probabilism’ replaces such an extreme view by introducing uncertainty on the reported evidence. How can such equivocal evidence be used in further inferences about a main hypothesis? The theoretical ground is introduced with the aim of offering to the readership an explanation for the generalization of the Bayes’ Theorem. This extension—that considers uncertainty related to the reporting of evidence—also has (...) an impact on the assessment of the value of evidence through the Bayes’ factor. A generalization for such a logical measure of the evidence is also presented and justified. (shrink)

The analysis of inferential interactions plays an important role in the description of the line of reasoning for a forensic evaluator in a case involving the cross-transfer of evidence. It is possible the two items of evidence may mean more to an evaluator when considered jointly than they do if considered separately. An approach to the evaluation of evidence, with particular attention to the factors that need to be considered, is described for a case involving the cross-transfer of evidence. A (...) formula is given which may be used to define the possible interactions between the evidence transferred in each direction and hence ease the interpretation of such evidence. Numerical examples are given from a classical fibre evidence scenario. (shrink)