Thursday, March 31, 2011

Research briefs: Social science and law; crime causality; jury research

Monahan, J., & Walker, L. (2011). Twenty-Five Years of Social Science in Law. Law and Human Behavior, 35(1), 72-82.

In this essay, we take the publication of the seventh edition of the casebook Social Science in Law (2010) as an opportunity to reflect on continuities and changes that have occurred in the application of social science research to American law over the past quarter-century. We structure these reflections by comparing and contrasting the original edition of the book with the current one. When the first edition appeared, courts’ reliance on social science was often confused and always contested. Now, courts’ reliance on social science is so common as to be unremarkable. What has changed—sometimes radically—are the substantive legal questions on which social science has been brought to bear.

Murray, J., Thomson, M. E., Cooke, D. J., & Charles, K. E. (2011). Influencing expert judgment: Attributions of crime causality. Legal and Criminological Psychology, 16(1), 126-143.

Courts occasionally permit psychologists to present expert evidence in an attempt to help jurors evaluate eyewitness identification evidence. This paper reviews research assessing the impact of this expert evidence, which we argue should aim to increase jurors' ability to discriminate accurate from inaccurate identifications. With this in mind we identify three different research designs, two indirectly measuring the expert's impact on juror discrimination accuracy and one which directly assesses its effect on this measure. Across a total of 24 experiments, three have used the superior direct methodology, only one of which provides evidence that expert testimony can improve jurors' ability to discriminate between accurate and inaccurate eyewitness identifications.

Wright, D. B., Strubler, K. A., & Vallano, J. R. (2011). Statistical techniques for juror and jury research. Legal and Criminological Psychology, 16(1), 90-125.

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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