Advertisement

Credibility Assessment, Common Law Trials and Fuzzy Logic

Chapter

Abstract

Judges or juries make decisions about the credibility of witnesses, decisions that might send one person to prison for years, strip another of her fortune or deny a parent full access to his children. An on-going judicial research project has been studying how such questions of contested fact are determined in a trial (Seniuk 1994). The project reached out to experts from outside the legal profession to assess what knowledge or insight these other disciplines might shed on this question. For example, knowledge of forensic psychology and what the discipline has learned of credibility assessment and lie detection has greatly assisted this project (see Seniuk and Yuille 1996; ten Brinke and Porter present volume).

Keywords

Credibility Assessment Fuzzy Logic Analysis Forensic Psychology Demeanor Evidence Crisp Line 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgment

Thanks to Dr. Madan M. Gupta, University of Saskatchewan, College of Engineering, for explaining fuzzy logic and for guiding the development of the fuzzy logic charts.

References

  1. Allen, R. J. (1994a). Burdens of proof, uncertainty and ambiguity in modern legal discourse. Harvard Journal of Law and Public Policy, 17, 627–646.Google Scholar
  2. Allen, R. J. (1994b). Factual ambiguity and a theory of evidence. Northwestern Law Review, 88, 604–640.Google Scholar
  3. Allen, R. J., & Seniuk, G. T. G. (1997). Two puzzles of juridical proof. Canadian Bar Review, 76, 65.Google Scholar
  4. Anderson, T., & Twinning, W. (1991). Analysis of evidence. London: George Weidenfeld and Nicholson.Google Scholar
  5. Ding, H., & Gupta, M. M. (2000). Competitive and cooperative adaptive reasoning with fuzzy causal knowledge. Journal of Intelligent and Fuzzy Systems, 9, 191–196.Google Scholar
  6. Ekman, P. (1992). Telling lies. New York: W.W. Norton.Google Scholar
  7. Frank, J. (1949). Courts on trial. Princeton: Princeton University Press.Google Scholar
  8. Kaufmann, A., & Gupta, M. M. (1985). Introduction to fuzzy arithmetic: Theory and applications. New York: Van Nostrand Reinhold Company Inc.Google Scholar
  9. Polya, G. (1988). Mathematics and plausible reasoning: Patterns of plausible inference (Vol. 2). Princeton: Princeton University Press.Google Scholar
  10. R. v. B. (K.G.) (1948) 7 C.R. 342.Google Scholar
  11. R. v. Belland and Phillips, (1987) 2 S.C.R. 398.Google Scholar
  12. R. v. J.H.S., (2008) SCC 30.Google Scholar
  13. R. v. Lifchus (1997) 5 C.R. (5th) 1 S.C.C.Google Scholar
  14. R. v. Mackenzie (1993) 18 C.R. (4th) 133.Google Scholar
  15. R. v. Presley, (1948) 7 C.R. 342.Google Scholar
  16. R. v. Starr (2001) 36 C.R. (5th) 1.Google Scholar
  17. Seniuk, G. T. G. (1992). Judicial fact-finding and a theory of credit. Saskatchewan Law Review, 56, 79.Google Scholar
  18. Seniuk, G. T. G. (1994). Judicial fact-finding and contradictory witnesses. Criminal Law Quarterly, 37, 70.Google Scholar
  19. Seniuk, G. T. G., & Yuille, J. C. (1996). Fact finding and the judiciary. Saskatoon: Commonwealth of Learning.Google Scholar
  20. Zadeh, L. A. (2004). Fuzzy logic systems: Origin, concepts, and trends. Hong Kong: Paper presented at the Web Intelligence Consortium.Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Provincial Court of Saskatchewan, Visiting Scholar, College of LawUniversity of SaskatchewanSaskatoonCanada

Personalised recommendations