A Taxonomy for Modelling Discretionary Decision Making in the Legal Domain

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Schild, Uri J and Zeleznikow, John ORCID: 0000-0002-8786-2644 (2005) A Taxonomy for Modelling Discretionary Decision Making in the Legal Domain. In: Proceedings of the Tenth International Conference on Artificial Intelligence and Law. ACM Press, pp. 60-64.

Abstract

In attempting to model how legal discretion is exercised, we have previously discussed the notion of open texture and introduced the notion of boundedness of legal domains. Through a series of case studies we have noticed that an important factor has been overlooked: namely whether the decisions made in a given domain are binary. We develop a set of three criteria for computer modeling of legal discretion and discuss the eight octants that arise from the three-dimensional space formed by these criteria.

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Additional Information	Conference : ICAIL 2005 10th International Joint Conference on Artificial Intelligence and Law Bologna, Italy — June 06 - 11, 2005
Item type	Book Section
URI	https://vuir.vu.edu.au/id/eprint/10654
DOI	10.1145/1165485.1165495
Official URL	http://dl.acm.org/ft_gateway.cfm?id=1165495&ftid=3...
ISBN	1595930817
Subjects	Historical > RFCD Classification > 280000 Information, Computing and Communication Sciences Historical > FOR Classification > 0801 Artificial Intelligence and Image Processing Historical > FOR Classification > 0806 Information Systems Historical > FOR Classification > 1801 Law Historical > Faculty/School/Research Centre/Department > School of Management and Information Systems
Keywords	ResPubID8609, legal software system, case-based reasoning, machine learning, knowledge discovery, jurisprudence, alternative dispute resolution, ADR, discretionary reasoning
Citations in Scopus	1 - View on Scopus
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