Multi-criteria coherence ranking of legal theories: the aggregation problem and possible solutions

Abstract: While coherentist approach to justification has been trending in law and numerous multi-criteria accounts of theory coherence have been established, it mostly remains unknown how a legal decision maker can obtain an overall coherence ranking among legal theories from the multiple criteria, such that he can tell legal theories from better to worse and figure out which legal judgment is best justified. This paper intends to unravel this puzzle. Inspired by social choice theory, the puzzle is presented as a preference aggregation problem in a multi-criteria decision making context. A common problem setting as well as relevant rational conditions are first generalized from three motivating examples. Such generalization gives rise to a formalization in terms of decision matrix. The problem of obtaining an overall coherence ranking is thereby a problem of making appropriate use of the coherence evaluation matrix, and the aggregation function is defined as a coherence evaluation functional (\(\mathtt{CEFL}\)). Three \(\mathtt{CEFL}\) respectively on the basis of simple majority, Borda count and normalized summation are then formulated, with a detailed examination of their strengths and weaknesses for legal decision making.

Recommended citation: Tianwen Xu. (2023). "Multi-criteria coherence ranking of legal theories: the aggregation problem and possible solution." Logics for AI and Law: Joint Proceedings of the Third International Workshop on Logics for New-Generation Artificial Intelligence and the International Workshop on Logic, AI and Law. College Publications.
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