Statistical evidence, discrimination, and causation.
Discrimination law is a possible application of the methods of causal modelling. With it, it brings the possibility of direct statistical evidence on counterfactual questions, something that traditional techniques like multiple regression lack. The kinds of evidence that causal modelling can provide...
| Publicado en: | Synthese Vol. 200; no. 6; pp. 1 - 23 |
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| Formato: | Artículo |
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Springer Nature
Dec2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=160298317&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 160298317 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00397857 4LI jtl: Synthese issn: 00397857 maglogo: N pubinfo: dt: Dec2022 vid: 200 iid: 6 pid: 237 pub: Springer Nature artinfo: ui: 160298317 10.1007/s11229-022-03958-7 ppf: 1 ppct: 22 formats: fmt: – @attributes: type: T – @attributes: type: P size: 342KB tig: atl: Statistical evidence, discrimination, and causation. aug: au: Shin, Justin affil: History and Philosophy of Science, University of Pittsburgh, Pittsburgh, USA sug: keyword: Causal modelling Causation Discrimination Ethics Statistical evidence ab: Discrimination law is a possible application of the methods of causal modelling. With it, it brings the possibility of direct statistical evidence on counterfactual questions, something that traditional techniques like multiple regression lack. The kinds of evidence that causal modelling can provide, in large part due to its attention to counterfactuals, is very close to the key question that we ask of jurors in discrimination cases. With this new kind of evidence comes new opportunities. We can better proportion punitive damages to the severity of the discrimination that manifests in a hiring process. We can avoid making certain kinds of assumptions regarding the relationship between protected classes and hiring qualifications that other statistical methods demand from statisticians. We can also distribute restitution to individual claimants in a way that is proportionate to how their application was treated in the hiring process. Here we explore where and how causal modelling can be useful in discrimination law and policy. What elements of law provide friction with this mode of gathering statistical evidence, what new possibilities does it reveal, and how does this integrate with prior judgments regarding statistical evidence? pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Synthese is a copyright of Springer, 2022. All Rights Reserved. item: Synthese holder: Springer Nature dt: @attributes: year: 2022 holdings: @attributes: islocal: N |
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