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A taxonomy for modelling discretionary decision making in the legal domain
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Source International Conference on Artificial Intelligence and Law archive
Proceedings of the 10th international conference on Artificial intelligence and law table of contents
Bologna, Italy
SESSION: Reasoning about cases table of contents
Pages: 60 - 64  
Year of Publication: 2005
ISBN:1-59593-081-7
Authors
Uri J. Schild  Bar-Ilan University, Ramat-Gan, Israel
John Zeleznikow  Victoria University, Melbourne, Australia
Sponsors
: The International Association for Artificial Intelligence and Law
: CIRSFID
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 4,   Downloads (12 Months): 24,   Citation Count: 1
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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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Black, H. C. 1990. BLACKS Law Dictionary, West Publishing Company, St. Paul, Minnesota.
 
2
Schild, U., J., Stranieri, A. and Zeleznikow, J. 1999. Techniques for reasoning in discretionary legal domains. IASTED (Law Tech1999), ACTA Press, Anaheim, California.
 
3
Hart, H. L. A., 1961. The Concept of Law Clarendon Press. Oxford, UK.
 
4
Stranieri, A., Zeleznikow, J., Gawler, M. and Lewis, B. 1999. A hybrid-neural approach to the automation of legal reasoning in the discretionary domain of family law in Australia. Artificial Intelligence and Law 7 (2--3): 153--183
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Fletcher, G. P. 1996. Basic Concepts of Legal Thought. Oxford University Press, New York, NY.
 
8
Stranieri, A. and Zeleznikow, J. 2004. Knowledge Discovery from Legal Databases, Springer Law and Philosophy Library, Volume 69, Dordrecht, The Netherlands


Collaborative Colleagues:
Uri J. Schild: colleagues
John Zeleznikow: colleagues