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Toward Modeling and Teaching Legal Case-Based Adaptation with Expert Examples

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Case-Based Reasoning Research and Development (ICCBR 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5650))

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Abstract

Studying examples of expert case-based adaptation could advance computational modeling but only if the examples can be succinctly represented and reliably interpreted. Supreme Court justices pose hypothetical cases, often adapting precedents, to evaluate if a proposed rule for deciding a problem needs to be adapted. This paper describes a diagrammatic representation of adaptive reasoning with hypothetical cases based on a process model. Since the diagrams are interpretations of argument texts, there is no one “correct” diagram, and reliability could be a challenge. An experiment assessed the reliability of expert grading of diagrams prepared by students reconstructing examples of hypothetical reasoning. Preliminary results indicate significant areas of agreement, including with respect to the ways tests are modified in response to hypotheticals, but slight agreement as to the role and import of hypotheticals. These results suggest that the diagrammatic representation will support studying and modeling the examples of case-based adaptation, but that the diagramming support needs to make certain features more explicit.

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References

  1. Ashley, K.: Modeling Legal Argument: Reasoning with Cases and Hypotheticals. MIT Press, Cambridge (1990)

    Google Scholar 

  2. Ashley, K.: What a Legal CBR Ontology Should Provide. In: Proceedings of the 22nd Int’l FLAIRS Conf. Case-Based Reasoning Track, Sanibel Island, FL (May 2009)

    Google Scholar 

  3. Ashley, K., Lynch, C., Pinkwart, N., Aleven, V.: A Process Model of Legal Argument with Hypotheticals. In: Legal Knowledge and Info. Sys., Proc. Jurix 2008, pp. 1–10 (2008)

    Google Scholar 

  4. Eisenberg, M.: The Nature of the Common Law. Harvard U. Press (1988)

    Google Scholar 

  5. Gewirtz, P.: The Jurisprudence of Hypotheticals. J. of Legal Education 32, 120–124 (1982)

    Google Scholar 

  6. Hayes-Roth, R.: Using proofs and refutations to learn from experience. In: Michalski, R., et al. (eds.) Machine Learning: An A. I. Approach, Tioga, Palo Alto, pp. 221–240 (1983)

    Google Scholar 

  7. Hurley, S.: Coherence, Hypothetical Cases, and Precedent. Oxford J. Legal Studies 10, 221–251 (1990)

    Article  Google Scholar 

  8. Johnson, T.: Oral Arguments and Decision Making on the U. S. Supreme Court, SUNY (2004)

    Google Scholar 

  9. Kolodner, J.: Case-Based Reasoning. Morgan Kaufmann, San Mateo (1993)

    Book  MATH  Google Scholar 

  10. Lakatos, I.: Proofs and Refutations. Cambridge University Press, London (1976)

    Book  MATH  Google Scholar 

  11. Landis, J., Koch, G.: The measurement of observer agreement for categorical data. Biometrics 33, 159–174 (1977)

    Article  MATH  Google Scholar 

  12. Lenat, D.B., Brown, J.S.: Why AM and EURISKO appear to work. Artificial Intelligence 23(3), 269–294 (1984)

    Article  Google Scholar 

  13. Lynch, C., Pinkwart, N., Ashley, K., Aleven, V.: What do argument diagrams tell us about students aptitude or experience? In: Workshop on ITSs for Ill-structured Domains, ITS 2008, Montreal (2008)

    Google Scholar 

  14. MacCormick, D., Summers, R. (eds.): Interpreting Precedents Ashgate/Dartmouth (1997)

    Google Scholar 

  15. Pease, A., Colton, S., Smaill, A., Lee, J.: Lakatos and Machine Creativity. In: Proceedings of the ECAI Creative Systems Workshop (2002)

    Google Scholar 

  16. Pinkwart, N., Aleven, V., Ashley, K., Lynch, C.: Evaluating legal argument instruction with graphical representations using LARGO. In: Proc. AIED 2007 (July 2007)

    Google Scholar 

  17. Pinkwart, N., Ashley, A., Aleven, V., Lynch, C.: Graph Grammars: an ITS Technology for Diagram Representations. In: Proc. 21st Int’l FLAIRS Conf., ITS Track, Coral Gables (May 2008)

    Google Scholar 

  18. Pinkwart, N., Lynch, C., Ashley, K., Aleven, V.: Re-evaluating LARGO in the Classroom: Are Diagrams Better than Text for Teaching Argumentation Skills? In: Woolf, B.P., Aïmeur, E., Nkambou, R., Lajoie, S. (eds.) ITS 2008. LNCS, vol. 5091, pp. 90–100. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  19. Prettyman Jr., E.: The Supreme Court’s Use of Hypothetical Questions at Oral Argument. Catholic University Law Review 33, 555–591 (1984)

    Google Scholar 

  20. Rissland, E.: Constrained Example Generation. COINS TR 81-24. U. Mass (1981)

    Google Scholar 

  21. Rissland, E.: Dimension-based Analysis of Hypotheticals from Supreme Court Oral Argument. In: Proc. 2nd Int’l Conf. on Artificial Intelligence and Law, pp. 111–120. ACM Press, New York (1989)

    Google Scholar 

  22. Stuckey, R., et al.: Best Practices for Legal Education, pp. 214–215. Clin. Leg. Ed. Assc. (2007)

    Google Scholar 

  23. Sullivan, W., Colby, A., Wegner, J., Bond, L., Shulman, L.: Educating Lawyers, 62, 66, 68, 75 The Carnegie Foundation for the Advancement of Teaching (2007)

    Google Scholar 

  24. Visser, W.: Reuse of Knowledge: Empirical Studies. In: Aamodt, A., Veloso, M.M. (eds.) ICCBR 1995. LNCS (LNAI), vol. 1010, pp. 335–346. Springer, Heidelberg (1995)

    Chapter  Google Scholar 

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Ashley, K., Lynch, C., Pinkwart, N., Aleven, V. (2009). Toward Modeling and Teaching Legal Case-Based Adaptation with Expert Examples. In: McGinty, L., Wilson, D.C. (eds) Case-Based Reasoning Research and Development. ICCBR 2009. Lecture Notes in Computer Science(), vol 5650. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02998-1_5

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  • DOI: https://doi.org/10.1007/978-3-642-02998-1_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02997-4

  • Online ISBN: 978-3-642-02998-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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