Modelling the effects of crime type and evidence on judgments about guilt
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2018-11-01
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© 2018, The Author(s), under exclusive licence to Springer Nature Limited. Concerns over wrongful convictions have spurred an increased focus on understanding criminal justice decision-making. This study describes an experimental approach that complements conventional mock-juror experiments and case studies by providing a rapid, high-throughput screen for identifying preconceptions and biases that can influence how jurors and lawyers evaluate evidence in criminal cases. The approach combines an experimental decision task derived from marketing research with statistical modelling to explore how subjects evaluate the strength of the case against a defendant. The results show that, in the absence of explicit information about potential error rates or objective reliability, subjects tend to overweight widely used types of forensic evidence, but give much less weight than expected to a defendant’s criminal history. Notably, for mock jurors, the type of crime also biases their confidence in guilt independent of the evidence. This bias is positively correlated with the seriousness of the crime. For practising prosecutors and other lawyers, the crime-type bias is much smaller, yet still correlates with the seriousness of the crime.
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Beskind, D, J Pearson, J Law, J Skene, N Vidmar and D Ball (2018). Modelling the effects of crime type and evidence on judgments about guilt. Nature Human Behaviour, 2(11). pp. 856–866. 10.1038/s41562-018-0451-z Retrieved from https://hdl.handle.net/10161/17687.
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Donald H. Beskind
Donald H. Beskind directs and teaches in Duke Law School's Trial Practice program and teaches Torts and Evidence. He has been a trial lawyer representing plaintiffs in civil cases and defendants in criminal cases throughout his career.
After beginning his career in practice in Denver, he was a John S. Bradway Fellow at Duke Law from 1975 to 1977, at the conclusion of which he received his LLM. He then joined the governing faculty, first as an assistant professor and then as associate professor and director of the Clinical Program.
In 1981, Beskind returned to private practice, co-founding Beskind & Rudolf (later Beskind, Rudolf & Maher) where he practiced until 1993. In 1993, he joined what became Twiggs, Beskind, Strickland & Rabenau, and practiced with that firm until 2010. While in private practice, as a Senior Lecturer in Law at Duke, he directed and taught in Duke’s Trial Practice program and periodically taught Evidence. Since returning to Duke full-time as Professor of the Practice in 2010, he has continued to handle civil and post-conviction criminal cases and mediate complex disputes.
Beskind is a fellow of the International Society of Barristers, its Administrative Secretary and the Executive Editor of its Quarterly journal. He is also a fellow of the American College of Trial Lawyers. He has served on the Board of Governors of both national and North Carolina trial lawyer organizations and has chaired the committees on continuing legal education for both. He was a founding board member of North Carolina Prisoner Legal Services and served as its president. He has served on the Board of the Center for Death Penalty Litigation and been its president. Beskind lectures on evidentiary and trial skills topics across the United States and has run trial training programs at major U.S. law firms and has trained solicitors and barristers in the United Kingdom.
Beskind received his AB in sociology from The George Washington University, his JD, with honors, from the University of Connecticut, and his LLM from Duke Law School. He is the co-author of two books on North Carolina Evidence, a torts casebook, and numerous materials on trial and pretrial advocacy.
John Pearson
Our lab builds quantitative tools and theories to understand how brains control bodies to learn and survive in a complex world. In particular, we are interested in the process by which organisms like songbirds learn complex motor skills without external reinforcement, the way simple information processing principles can explain the organization of early sensory systems, and how complex behaviors like swimming and grasping are coordinated across the brain. To this end, we also design software tools and algorithm that allow us to model and perturb neural systems in real time.
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