Law Probability & Risk最新文献

From specific-source feature-based to common-source score-based likelihood-ratio systems: ranking the stars 从基于特定来源的特征到基于共同来源的分数的似然比系统:对星星进行排名

IF 0.7 4区社会学

Law Probability & Risk Pub Date : 2023-05-12 DOI: 10.1093/lpr/mgad005

P. Vergeer

{"title":"From specific-source feature-based to common-source score-based likelihood-ratio systems: ranking the stars","authors":"P. Vergeer","doi":"10.1093/lpr/mgad005","DOIUrl":"https://doi.org/10.1093/lpr/mgad005","url":null,"abstract":"\u0000 This article studies expected performance and practical feasibility of the most commonly used classes of source-level likelihood-ratio (LR) systems when applied to a trace–reference comparison problem. The article compares performance of these classes of LR systems (used to update prior odds) to each other and to the use of prior odds only, using strictly proper scoring rules as performance measures. It also explores practical feasibility of the classes of LR systems. The present analysis allows for a ranking of these classes of LR systems: from specific-source feature-based to common-source anchored or non-anchored score-based. A trade-off between performance and practical feasibility is observed, meaning that the best performing class of LR systems is the hardest to realize in practice, while the least performing class is the easiest to realize in practice. The other classes of LR systems are in between the two extremes. The one positive exception is a common-source feature-based LR system, with good performance and relatively low experimental demands. This article also argues against the claim that some classes of LR systems should not be used, by showing that all systems have merit (when updating prior odds) over just using the prior odds (i.e. not using the LR system).","PeriodicalId":48724,"journal":{"name":"Law Probability & Risk","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46071750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Information economics in the criminal standard of proof 刑事证据标准中的信息经济学

IF 0.7 4区社会学

Law Probability & Risk Pub Date : 2023-03-14 DOI: 10.1093/lpr/mgad004

Christian Dahlman, A. Nordgaard

引用次数: 1

Signal detection theory fails to account for real-world consequences of inconclusive decisions 信号检测理论无法解释不确定决策的现实后果

IF 0.7 4区社会学

Law Probability & Risk Pub Date : 2023-02-07 DOI: 10.1093/lpr/mgad001

Maneka Sinha, Richard Gutíerrez

引用次数: 3

A plague on both your houses: The debate about how to deal with ‘inconclusive’ conclusions when calculating error rates 一场瘟疫困扰着你的两家：关于如何在计算错误率时处理“不确定”结论的辩论

IF 0.7 4区社会学

Law Probability & Risk Pub Date : 2022-11-23 DOI: 10.1093/lpr/mgac015

G. Morrison

引用次数: 3

Erosion of the basic human rights 基本人权受到侵蚀

IF 0.7 4区社会学

Law Probability & Risk Pub Date : 2022-11-16 DOI: 10.52340/law.2022.01

Nugzar Saria

引用次数: 0

Inconclusives are not errors: a rejoinder to Dror 结论不是错误：对Dror的反驳

IF 0.7 4区社会学

Law Probability & Risk Pub Date : 2022-10-12 DOI: 10.1093/lpr/mgac009

H. Arkes, J. Koehler

引用次数: 5

‘This Crime is Not That Crime’—Classification and evaluation of four common crimes “本罪非彼罪”——四种常见犯罪的分类与评价

IF 0.7 4区社会学

Law Probability & Risk Pub Date : 2022-07-14 DOI: 10.1093/lpr/mgac006

K. Xu, Han Liu, Fang Wang, Han Wang

{"title":"‘This Crime is Not That Crime’—Classification and evaluation of four common crimes","authors":"K. Xu, Han Liu, Fang Wang, Han Wang","doi":"10.1093/lpr/mgac006","DOIUrl":"https://doi.org/10.1093/lpr/mgac006","url":null,"abstract":"\u0000 As the basis of criminal penalty, criminal conviction, integral to the protection of fundamental rights and freedom of people constitutes the basis and the core issue of criminal trials. Based on the data published on China Judgments Online, we proposed two types of classification models to apply the data of four common crimes from China Judgments Online and expounded their applications in identifying ‘abnormal cases’, defined as wrongly sentenced cases in this article. The two types of classification models we proposed are a two-stage model and two deep learning models. To construct the two-stage model, we first used three keyword-extraction models to extract the keywords and vectorize all the keywords, then used five classification models to build the two-stage model. For the deep learning models, we applied two different deep neural network models in the data to build the classifier. We then applied these two types of classification models to discover ‘abnormal cases’ in two steps. In the first step, we applied the two-stage model to extract the ‘important words’ which will significantly improve the probability of the two-stage model to classify cases into crimes of intentional injury. In the second step, we constructed a validation data set of cases whose verdicts are changed in the second instance rulings to test the ‘important words’ extracted in first step and the ability of the two-stage model and the two deep learning models to discover ‘abnormal cases’. The results of this exercise show that: (1) ‘important words’ extracted in the first step are often associated with ‘abnormal cases’; (2) these two types of classification models can effectively discover ‘abnormal cases’, but compared with the two deep learning models, the two-stage model (aka. Term Frequency-Inverse Document Frequency and Artificial Neural Network, the combination of a keyword extraction model and a classic machine-learning model) is more capable of discovering ‘abnormal cases’.","PeriodicalId":48724,"journal":{"name":"Law Probability & Risk","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44673809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

OUP accepted manuscript OUP接受稿件

IF 0.7 4区社会学

Law Probability & Risk Pub Date : 2022-01-01 DOI: 10.1093/lpr/mgac002

引用次数: 1

OUP accepted manuscript OUP接受稿件

IF 0.7 4区社会学

Law Probability & Risk Pub Date : 2022-01-01 DOI: 10.1093/lpr/mgac004

引用次数: 0

Custody of Digital Assets 数字资产托管

IF 0.7 4区社会学

Law Probability & Risk Pub Date : 2021-10-05 DOI: 10.2139/ssrn.3936876

Wulf A. Kaal, Hayley Howe

引用次数: 0