A third verdict option: Exploring the impact of the not proven verdict on mock juror decision making.

Hope, Lorraine; Greene, Edith; Memon, Amina; Gavisk, Melanie; Houston, Kate A.

doi:10.1007/s10979-007-9106-8

Cited by 17 publications

(65 citation statements)

References 33 publications

(38 reference statements)

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“…Confidence does not always equal accuracy, however (Hall et al, 2007) 18 . Hope et al 5 also found that the different verdict systems did not have a significant impact on the juror's perception of guilt surrounding the defendant.…”

Section: Review Of Empirical Studies Surrounding the Not Proven Verdictmentioning

confidence: 97%

“…In addition, Hope et al 5 demonstrated that irrespective of verdict or evidence weight, verdicts made in the three-verdict system allowed the mock jurors to feel more confident that they had reached the correct verdict than their binary verdict system counterparts. Confidence does not always equal accuracy, however (Hall et al, 2007) 18 .…”

Section: Review Of Empirical Studies Surrounding the Not Proven Verdictmentioning

confidence: 99%

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The bastard verdict and its influence on jurors

et al. 2018

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The Scottish legal system is a unique jurisdiction, as jurors are able to give not proven verdicts in addition to the well-known Anglo-American verdicts (guilty and not guilty). The not proven verdict has never been legally defined, meaning that currently legal practitioners can only estimate why a not proven verdict has been given. The main aim of this study was to investigate if jurors violate the regularity principle, which is commonly incorporated in many rational choice models, by testing if the introduction of the not proven verdict has an impact on the outcomes given by jurors. In addition, this study aimed to test if the introduction of the not proven verdict has an impact upon how the not guilty verdict is perceived by jurors. In this study, 128 participants listened to two vignettes centred on homicide trials. Jurors could give one of two verdicts in one of the vignettes and one of three verdicts in the other vignette. The vignettes were counterbalanced in regard to how many verdicts could be given at the end of them. It was found that jurors in a three-verdict system were less likely to give a not guilty verdict in comparison to jurors in a two-verdict system, showing that jurors violate the regularity principle and that the not proven verdict may change how the not guilty verdict is perceived. The findings of this research have implications in relation to juror communication, article 6 of the European Convention of Human Rights and juror rationality.

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Section: Review Of Empirical Studies Surrounding the Not Proven Verdictmentioning

confidence: 97%

Section: Review Of Empirical Studies Surrounding the Not Proven Verdictmentioning

confidence: 99%

The bastard verdict and its influence on jurors

et al. 2018

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“…The dependent variable for the design considered in this section is a jury level variable so that everybody in the same jury has the same value. For example, it might be whether the jury said guilty or not guilty (though see Hope, Greene, Memon, Gavisk, & Houston, 2008, for allowing more options), or the proportion of guilty verdicts, or it might be of some other characteristic of the jury, like whether the jury discussed ‘forbidden topics’ (Greene, Hayman, & Motyl, 2008). Greene et al research on jury deliberation provides a good example of how to analyse data of this type (and a good example of combining qualitative and quantitative data).…”

Section: Modelling Jury Rather Than Juror Behaviourmentioning

confidence: 99%

Statistical techniques for juror and jury research

Wright

Strubler

Vallano

2011

Legal Criminol Psychol

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Juror and jury research is a thriving area of investigation in legal psychology. The basic ANOVA and regression, well‐known by psychologists, are inappropriate for analysing many types of data from this area of research. This paper describes statistical techniques suitable for some of the main questions asked by jury researchers. First, we discuss how to examine manipulations that may affect levels of reasonable doubt and how to measure reasonable doubt using the coefficients estimated from a logistic regression. Second, we compare models designed for analysing the data like those which often arise in research where jurors first make categorical judgments (e.g., negligent or not, guilty or not) and then dependent on their response may make another judgment (e.g., award, punishment). We concentrate on zero‐inflated and hurdle models. Third, we examine how to take into account that jurors are part of a jury using multilevel modelling. We illustrate each of the techniques using software that can be downloaded for free from the Internet (the package R) and provide a web page that gives further details for running these analyses.

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“…Indeed, in the course of a trial, the main task that every judge has to face concerns the evaluation of various pieces of evidence from a variety of different sources, with the aim of integrating such information into a single decision of conviction or acquittal of a defendant. Presumably, a judge arrives at a certain subjective estimation of the likelihood that the defendant is guilty and decides whether such likelihood is greater or lesser than Houston, 2008;Shapiro, 1991;Wright & Hall, 2007). In such terms, an issue of considerable interest is the following: how do judges integrate various pieces of information in order to make their judgement?…”

Section: Introductionmentioning

confidence: 99%

Integration information in the judicial field: adding versus averaging models

Nori

Bensi

Gambetti

et al. 2012

Psychology, Crime & Law

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In the course of a trial, the main task that every judge or juror has to face concerns the evaluation of various pieces of evidence from a variety of different sources, with the aim of integrating such data into a single, final verdict. Algebraic models have tried to explain and predict decisional paths by identifying formal, mathematical combinatory rules. The aim of the present research was to test two main integration information models, namely adding and averaging, when combining items of judicial evidence. In the first study, we investigated how the probability of guilt varied as a function of the value of the pieces of evidence and information presented, in legal and not legal professional samples. In the second study, we analysed combinatory rules with more complex and realistic experimental material. Results indicated that participants summed the values of pieces of evidence in a linear fashion when they had to provide estimates of guilt. We found evidence of an adding rule among both legal and not legal professionals as well as in simple and more complex judicial cases, thus providing even stronger support for the use and the generalization of a summative model. Theoretical and practical implications are discussed.

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A third verdict option: Exploring the impact of the not proven verdict on mock juror decision making.

Cited by 17 publications

References 33 publications

The bastard verdict and its influence on jurors

The bastard verdict and its influence on jurors

Statistical techniques for juror and jury research

Integration information in the judicial field: adding versus averaging models

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