Defending the Hierarchical Result Models of Precedential Constraint
This addresses a theoretical problem in legal reasoning models for researchers in AI and law, but it is incremental as it responds to existing critiques without introducing new methods.
The paper defends van Woerkom's hierarchical result models of precedential constraint against criticisms by Trevor Bench-Capon, arguing that applying a dimension-based version of these models resolves the issues raised in specific examples.
In recent years, hierarchical case-based-reasoning models of precedential constraint have been proposed. In various papers, Trevor Bench-Capon criticised these models on the grounds that they would give incorrect outcomes in some cases. In particular, the models would not account for the possibility that intermediate factors are established with different strengths by different base-level factors. In this paper we respond to these criticisms for van Woerkom's result-based hierarchical models. We argue that in some examples Bench-Capon seems to interpret intermediate factors as dimensions, and that applying van Woerkom's dimension-based version of the hierarchical result model to these examples avoids Bench-Capon's criticisms.