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The Problematic Value of Mathematical Models of Evidence

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  • Ronald J. Allen
  • Michael S. Pardo

Abstract

This paper discusses mathematical modeling of the value of particular items of evidence. We demonstrate that such formal modeling has only limited use in explaining the value of legal evidence, much more limited than those investigators who construct and discuss the models assume, and thus that the conclusions they draw about the value of evidence are unwarranted. This is done through a discussion of several recent examples that attempt to quantify evidence relating to carpet fibers, infidelity, DNA random-match evidence, and character evidence used to impeach a witness. This paper makes the following contributions. Most important, it is another demonstration of the complex relationship between algorithmic tools and legal decision making. Furthermore, at a minimum it highlights the need for both analytical and empirical work to accommodate the reference-class problem and the risk of failing to do so.

Suggested Citation

  • Ronald J. Allen & Michael S. Pardo, 2007. "The Problematic Value of Mathematical Models of Evidence," The Journal of Legal Studies, University of Chicago Press, vol. 36(1), pages 107-140, January.
    • Handle: RePEc:ucp:jlstud:v:36:y:2007:p:107-140
    DOI: 10.1086/508269
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    Cited by:

    1. Antonio Nicita & Matteo Rizzolli, 2014. "In Dubio Pro Reo. Behavioral Explanations of Pro-defendant Bias in Procedures," CESifo Economic Studies, CESifo, vol. 60(3), pages 554-580.
    2. Edward K. Cheng, 2014. "Comment on Dawid, Faigman, and Fienberg (2014)," Sociological Methods & Research, , vol. 43(3), pages 396-400, August.
    3. Jonathan J. Koehler, 2011. "If the Shoe Fits They Might Acquit: The Value of Forensic Science Testimony," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 8(s1), pages 21-48, December.
    4. Matteo Rizzolli & Margherita Saraceno, 2013. "Better that ten guilty persons escape: punishment costs explain the standard of evidence," Public Choice, Springer, vol. 155(3), pages 395-411, June.
    5. Matteo Rizzolli & Margherita Saraceno, 2009. "Better that X guilty persons escape than that one innocent suffer," Working Papers 168, University of Milano-Bicocca, Department of Economics, revised Jul 2009.
    6. Zhihui Li & Yao Liu & Xiyuan Hu & Guiqiang Wang, 2022. "A new uniform framework of source attribution in forensic science," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-11, December.

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