Broken brakes and dreaming drivers

  • Recently, there has been an increased interest in employing model-based definitions of actual causation in legal inquiry. The formal precision of such approaches promises to be an improvement over more traditional approaches. Yet model-based approaches are viable only if suitable models of legal cases can be provided, and providing such models is sometimes difficult. I argue that causal-model-based definitions benefit legal inquiry in an indirect way. They make explicit the causal assumptions that need to be made plausible to defend a particular claim of actual causation. My argument concerns the analysis of legal cases involving a combination of double prevention and causal redundancy. I show that discussions among legal theorists about such cases sometimes suffer from ambiguous assumptions about the causal structure. My account illustrates that causal models can act as a heuristic tool for clarifying such assumptions, and that causal models provide a framework for more accurate analyses of legal cases involving complex causal structure.

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Metadaten
Author:Enno FischerORCiDGND
URN:urn:nbn:de:hbz:294-108970
DOI:https://doi.org/10.1007/s13194-023-00563-4
Parent Title (English):European journal for philosophy of science
Subtitle (English):the heuristic value of causal models in the law
Publisher:Springer
Place of publication:Berlin
Document Type:Article
Language:English
Date of Publication (online):2024/02/19
Date of first Publication:2024/01/25
Publishing Institution:Ruhr-Universität Bochum, Universitätsbibliothek
Tag:Actual causation; Causal models; Causal redundancy; Double prevention; Legal cases
Volume:14
Issue:Article 5
First Page:5-1
Last Page:5-20
Note:
Dieser Beitrag ist auf Grund des DEAL-Springer-Vertrages frei zugänglich.
Institutes/Facilities:Institut für Philosophie I
Dewey Decimal Classification:Philosophie und Psychologie / Philosophie
open_access (DINI-Set):open_access
faculties:Fakultät für Philosophie und Erziehungswissenschaft
Licence (English):License LogoCreative Commons - CC BY 4.0 - Attribution 4.0 International