Bayesian Detection of Bias in Peremptory Challenges Using Historical Strike Data.
United States law bars using peremptory strikes during jury selection because of prospective juror race, ethnicity, sex, or membership in certain other cognizable classes. Here, we extend a Bayesian approach for detecting such illegal strike bias by showing how to incorporate historical data on an a...
| Publicado en: | American Statistician Vol. 78; no. 2; pp. 209 - 220 |
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| Autores principales: | , , , |
| Formato: | Artículo |
| Publicado: |
Taylor & Francis Ltd
May2024
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=176695302&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 176695302 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00031305 STT jtl: American Statistician issn: 00031305 maglogo: Y pubinfo: dt: May2024 vid: 78 iid: 2 pid: 377 pub: Taylor & Francis Ltd artinfo: ui: 176695302 10.1080/00031305.2023.2249967 ppf: 209 ppct: 11 formats: tig: atl: Bayesian Detection of Bias in Peremptory Challenges Using Historical Strike Data. aug: au: Pandya, Sachin S. Li, Xiaomeng Barón, Eric Moore, Timothy E. affil: School of Law, University of Connecticut, Hartford, CT Department of Statistics, University of Connecticut, Storrs, CT Statistical Consulting Services, Center for Open Research Resources & Equipment, University of Connecticut, Storrs, CT su: United States Ethnicity Convenience sampling (Statistics) Race American law Jury selection Application software sug: subj: Ethnicity Convenience sampling (Statistics) Race United States Software publishers (except video game publishers) Custom Computer Programming Services Software Publishers American law Jury selection Application software keyword: Batson challenge Bayesian Peremptory strikes Power prior Batson challenge Bayesian Peremptory strikes Power prior ab: United States law bars using peremptory strikes during jury selection because of prospective juror race, ethnicity, sex, or membership in certain other cognizable classes. Here, we extend a Bayesian approach for detecting such illegal strike bias by showing how to incorporate historical data on an attorney's use of peremptory strikes in past cases. In so doing, we use the power prior to adjust the weight of such historical information in the analysis. Using simulations, we show how the choice of the power prior's discounting parameter influences bias detection (how likely the credible interval for the bias parameter excludes zero), depending on the degree of incompatibility between current and historical trial data. Finally, we extend this approach with a prototype software application that lawyers could use to detect strike bias in real time during jury-selection. We illustrate this application's use with real historical strike data from a convenience sample of cases from one court. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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