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.

最近，人们对在法律调查中采用基于模型的实际因果关系定义越来越感兴趣。这种方法的形式精度有望比更传统的方法有所改进。然而，只有能够提供合适的法律案例模型，基于模型的方法才是可行的，而提供这种模型有时很困难。我认为基于因果模型的定义以间接的方式有利于法律调查。他们明确提出了因果假设，需要使这些假设变得合理才能捍卫实际因果关系的特定主张。我的论点涉及对涉及双重预防和因果冗余相结合的法律案例的分析。我表明，法律理论家之间关于此类案件的讨论有时会受到关于因果结构的模糊假设的影响。我的叙述表明，因果模型可以作为澄清此类假设的启发式工具，并且因果模型为涉及复杂因果结构的法律案件提供了更准确分析的框架。