Hybrid journal (It can contain Open Access articles) ISSN (Print) 1470-8396 - ISSN (Online) 1470-840X Published by Oxford University Press[413 journals]
Authors:Robinson P. Pages: 119 - 137 Abstract: AbstractThe theory of comparative propensity, championed by the late Mike Redmayne, has been an influential theory underpinning normative models of the probative value of evidence of previous convictions in criminal trials. It purports to generalize an approximate probative value by means of a Bayesian model in which the likelihood of an innocent person having a criminal record is calculated by reference to general population statistics, and the hard evidence underpinning the prior probability is treated as unknown. The theory has been criticized on the ground that it fails to take account of bias against past offenders in the selection of cases for prosecution. This article analyses the model and these criticisms and concludes that both the model and the criticisms are flawed because they fail to address the evidence on which the prior odds are based. We find that, not only are such mathematical models unsound, but they can only be ‘repaired’ by making assumptions about the typical case which run counter to the legal presumption of innocence. Analysing the flaws in these models, however, does provide some insight into issues affecting the value of prior convictions evidence. PubDate: Thu, 17 Sep 2020 00:00:00 GMT DOI: 10.1093/lpr/mgaa011 Issue No:Vol. 19, No. 2 (2020)
Authors:Meester R; Slooten K. Pages: 139 - 155 Abstract: AbstractOften the expression of a likelihood ratio involves model parameters θ. This fact prompted many researchers to argue that a likelihood ratio should be accompanied by a confidence interval, as one would do when estimating θ itself. We first argue against this, based on our view of the likelihood ratio as a function of our knowledge of the model parameters, rather than being a function of the parameters themselves. There is, however, another interval that can be constructed, and which has been introduced in the literature. This is the interval obtained upon sampling from the so-called ‘posterior likelihood ratio distribution’, after removing, say, the most extreme 5% of a sample from this distribution. Although this construction appears in the literature, its interpretation remained unclear, as explicitly acknowledged in the literature. In this article we provide an interpretation: the posterior likelihood ratio distribution tells us which likelihood ratios we can expect if we were to obtain more information. As such, it can play a role in decision making procedures, for instance about the question whether or not it is worthwhile to try to obtain more data. The posterior likelihood ratio distribution has no relevance for the evidential value of the current data with our current knowledge. We illustrate all this with a number of examples. PubDate: Wed, 16 Sep 2020 00:00:00 GMT DOI: 10.1093/lpr/mgaa010 Issue No:Vol. 19, No. 2 (2020)
Authors:Bergius M; Ernberg E, Dahlman C, et al. Pages: 157 - 164 Abstract: AbstractJudges should not be influenced by legally irrelevant circumstances in their legal decision making and judges generally believe that they manage legally irrelevant circumstances well. The purpose of this experimental study was to investigate whether this self-image is correct. Swedish judges (N = 256) read a vignette depicting a case of libel, where a female student had claimed on her blog that she had been sexually harassed by a named male professor. The professor had sued the student for libel and the student retracted her claim during the hearing. Half of the judges received irrelevant information - that the professor himself had been convicted of libel a year earlier, while the other half did not receive this information. For the outcome variable, the judges were asked to state how much compensation the student should pay the professor. Those judges who received information about the professor himself having been convicted of libel stated that he should be given significantly less compensation than those who did not receive the irrelevant information. The results show that the judges’ decision was affected by legally irrelevant circumstances. Implications for research and practice are discussed PubDate: Wed, 22 Jul 2020 00:00:00 GMT DOI: 10.1093/lpr/mgaa008 Issue No:Vol. 19, No. 2 (2020)
Authors:Ben-Yashar R; Krausz M. Pages: 165 - 180 Abstract: AbstractThis article analyses cases where independence between judges’ skills and states of nature affects decision efficiency in terms of the probability of making a correct collective decision, relative to the case where such independence does not exist. This article explains when it is advantageous to include either former defense lawyers who have expertise in obtaining an acquittal of defendants or former prosecutors who have expertise in obtaining a conviction, in a panel of judges. PubDate: Sun, 27 Sep 2020 00:00:00 GMT DOI: 10.1093/lpr/mgaa009 Issue No:Vol. 19, No. 2 (2020)
Authors:Clermont K. Pages: 181 - 206 Abstract: AbstractMy central interest is decision making in the presence of epistemic uncertainty. A method appropriate for both specialized inquiries and everyday reasoning is based on credal logic, which employs multivalent degrees of belief rather than traditional probability theory. It accounts for epistemic uncertainty as unallocated belief. It holds that, when facing real uncertainty, if a person believes a and believes b, then the person believes a and b together. This brand of multivalent logic underlies and justifies how legal decision makers and the rest of us find facts in a world infused with epistemic uncertainty. Indeed, this article closes by showing the equivalence of multivalent logic and inference to the best explanation. By demonstrating this similarity in reasoning, I aim to shore up our faith in the logic of traditional legal reasoning. PubDate: Thu, 29 Oct 2020 00:00:00 GMT DOI: 10.1093/lpr/mgaa012 Issue No:Vol. 19, No. 2 (2020)
Hybrid journal (It can contain Open Access articles)
