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Modelling the effects of crime type and evidence on judgments about guilt

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 preco...

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Autores principales: Pearson, John M., Law, Jonathan R., Skene, Jesse A. G., Beskind, Donald H., Vidmar, Neil, Ball, David A., Malekpour, Artemis, Carter, R. McKell, Skene, J. H. Pate
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6436087/
https://www.ncbi.nlm.nih.gov/pubmed/30931399
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author Pearson, John M.
Law, Jonathan R.
Skene, Jesse A. G.
Beskind, Donald H.
Vidmar, Neil
Ball, David A.
Malekpour, Artemis
Carter, R. McKell
Skene, J. H. Pate
author_facet Pearson, John M.
Law, Jonathan R.
Skene, Jesse A. G.
Beskind, Donald H.
Vidmar, Neil
Ball, David A.
Malekpour, Artemis
Carter, R. McKell
Skene, J. H. Pate
author_sort Pearson, John M.
collection PubMed
description 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 modeling 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 practicing prosecutors and other lawyers, the crime-type bias is much smaller, yet still correlates with the seriousness of the crime.
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spelling pubmed-64360872019-04-29 Modelling the effects of crime type and evidence on judgments about guilt Pearson, John M. Law, Jonathan R. Skene, Jesse A. G. Beskind, Donald H. Vidmar, Neil Ball, David A. Malekpour, Artemis Carter, R. McKell Skene, J. H. Pate Nat Hum Behav Article 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 modeling 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 practicing prosecutors and other lawyers, the crime-type bias is much smaller, yet still correlates with the seriousness of the crime. 2018-10-29 2018-11 /pmc/articles/PMC6436087/ /pubmed/30931399 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms;
spellingShingle Article
Pearson, John M.
Law, Jonathan R.
Skene, Jesse A. G.
Beskind, Donald H.
Vidmar, Neil
Ball, David A.
Malekpour, Artemis
Carter, R. McKell
Skene, J. H. Pate
Modelling the effects of crime type and evidence on judgments about guilt
title Modelling the effects of crime type and evidence on judgments about guilt
title_full Modelling the effects of crime type and evidence on judgments about guilt
title_fullStr Modelling the effects of crime type and evidence on judgments about guilt
title_full_unstemmed Modelling the effects of crime type and evidence on judgments about guilt
title_short Modelling the effects of crime type and evidence on judgments about guilt
title_sort modelling the effects of crime type and evidence on judgments about guilt
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6436087/
https://www.ncbi.nlm.nih.gov/pubmed/30931399
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