{"title":"Can criminal justice be predicted? Using regression analysis to predict judges’ decisions on petitions for new criminal trials","authors":"Moa Lidén","doi":"10.1016/j.scijus.2023.12.001","DOIUrl":null,"url":null,"abstract":"<div><p>Predictability of legal decisions is usually considered a prerequisite for the rule of law, following the maxim ‘like cases should be treated alike’. Yet, this presupposes that the case outcome can be predicted based on the <em>merits</em> of the case, rather than other factors. The purpose of this study was to test whether and to what extent legal decisions on petitions for new criminal trials can be predicted on the basis of other fairly superficial criteria that one could access without even reading the case file, e.g. which Court decided, whether the applicant had legal representation etc. To this end, all petitions for new criminal trials submitted to the Swedish Supreme Court and the six Courts of Appeal in the time period 2010–2020 (n = 3915) were reviewed. This data formed the basis of a regression model which was then used to predict decisions regarding petitions in 2021. On the basis of access to legal representation and crime type, the regression model predicted accurately 100 % of the decisions made in 2021. This raises questions about the evidentiary basis for the decisions and also the role of judges in situations where their decisions are fully predictable.</p></div>","PeriodicalId":49565,"journal":{"name":"Science & Justice","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2023-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1355030623001296/pdfft?md5=0c812f8727ec4eda645080cd6066114f&pid=1-s2.0-S1355030623001296-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science & Justice","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1355030623001296","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICINE, LEGAL","Score":null,"Total":0}
引用次数: 0
Abstract
Predictability of legal decisions is usually considered a prerequisite for the rule of law, following the maxim ‘like cases should be treated alike’. Yet, this presupposes that the case outcome can be predicted based on the merits of the case, rather than other factors. The purpose of this study was to test whether and to what extent legal decisions on petitions for new criminal trials can be predicted on the basis of other fairly superficial criteria that one could access without even reading the case file, e.g. which Court decided, whether the applicant had legal representation etc. To this end, all petitions for new criminal trials submitted to the Swedish Supreme Court and the six Courts of Appeal in the time period 2010–2020 (n = 3915) were reviewed. This data formed the basis of a regression model which was then used to predict decisions regarding petitions in 2021. On the basis of access to legal representation and crime type, the regression model predicted accurately 100 % of the decisions made in 2021. This raises questions about the evidentiary basis for the decisions and also the role of judges in situations where their decisions are fully predictable.
期刊介绍:
Science & Justice provides a forum to promote communication and publication of original articles, reviews and correspondence on subjects that spark debates within the Forensic Science Community and the criminal justice sector. The journal provides a medium whereby all aspects of applying science to legal proceedings can be debated and progressed. Science & Justice is published six times a year, and will be of interest primarily to practising forensic scientists and their colleagues in related fields. It is chiefly concerned with the publication of formal scientific papers, in keeping with its international learned status, but will not accept any article describing experimentation on animals which does not meet strict ethical standards.
Promote communication and informed debate within the Forensic Science Community and the criminal justice sector.
To promote the publication of learned and original research findings from all areas of the forensic sciences and by so doing to advance the profession.
To promote the publication of case based material by way of case reviews.
To promote the publication of conference proceedings which are of interest to the forensic science community.
To provide a medium whereby all aspects of applying science to legal proceedings can be debated and progressed.
To appeal to all those with an interest in the forensic sciences.