No more hung juries with Bayesian verdicts

We explain our novel solution to the problem of hung juries in this paper (“Why don’t juries try range voting?“), which was published in the Criminal Law Bulletin (vol. 51, no. 3) earlier this year. (In criminal cases, the jury’s verdict must be unanimous, so a hung jury occurs if just one juror disagrees with the remaining jurors about the outcome.) Bayesian voting, however, could solve this problem. In summary, rather than voting “guilty” or “not guilty,” jurors would instead keep a scorecard and score the evidence presented by the prosecutor at trial. Each juror’s scorecard could be based on a ten-point scale, with 10 being the highest possible score (an open and shut case) and 0 being the lowest score (no evidence in support of the prosecution’s case). So, for example, if a juror believes that the prosecution has proved its case beyond a reasonable doubt, the juror would assign a high score, such as a 9 or a 10, or if the juror thinks the case is too close to call, he or she could assign a 5. Accordingly, the jury’s “verdict” would consist of a numerical value–either the average value or the sum total of all their individual scores (I refer to this collective score as the “range verdict.”) Under this system, the prosecution would win a conviction only if the average value or sum total of the jury’s collective score exceeded some critical threshold value.

About F. E. Guerra-Pujol

When I’m not blogging, I am a business law professor at the University of Central Florida.
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