Comparing Categorical and Probabilistic Fingerprint Evidence

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Date
2018-04-23
Authors
Garrett, Brandon
Mitchell, Gregory
Scurich, Nicholas
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Center for Statistics and Applications in Forensic Evidence
Abstract

Fingerprint examiners traditionally express conclusions in categorical terms, opining that impressions do or do not originate from the same source. Recently, probabilistic conclusions have been proposed, with examiners estimating the probability of a match between recovered and known prints. This study presented a nationally representative sample of jury‐eligible adults with a hypothetical robbery case in which an examiner opined on the likelihood that a defendant's fingerprints matched latent fingerprints in categorical or probabilistic terms. We studied model language developed by the U.S. Defense Forensic Science Center to summarize results of statistical analysis of the similarity between prints. Participant ratings of the likelihood the defendant left prints at the crime scene and committed the crime were similar when exposed to categorical and strong probabilistic match evidence. Participants reduced these likelihoods when exposed to the weaker probabilistic evidence, but did not otherwise discriminate among the prints assigned different match probabilities.

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This is a manuscript of an article published as Garrett, Brandon, Gregory Mitchell, and Nicholas Scurich. "Comparing Categorical and Probabilistic Fingerprint Evidence." Journal of forensic sciences 63, no. 6 (2018): 1712-1717. Posted with permission of CSAFE.

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Mon Jan 01 00:00:00 UTC 2018
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