The Development and Application of Random Match Probabilities to Firearm and Toolmark Identification |
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| Authors: | John E Murdock MS Nicholas DK Petraco PhD John I Thornton DCrim Michael T Neel MS Todd J Weller MS Robert M Thompson BS James E Hamby PhD Eric R Collins BS |
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| Affiliation: | 1. Contra Costa County Office of the Sheriff, Forensic Services Division, Martinez, CA;2. John Jay College of Criminal Justice, CUNY, Manhattan, NY;3. Independent Forensic Scientist (Retired), Napa, CA;4. Bureau of Alcohol Tobacco, Firearms and Explosives Forensic Laboratory, Atlanta, GA;5. Oakland Police Department Crime Laboratory, Oakland, CA;6. National Institute of Standards and Technology (NIST), Gaithersburg, MD;7. International Forensic Science Laboratory & Training Centre, Indianapolis, IN |
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| Abstract: | The field of firearms and toolmark analysis has encountered deep scrutiny of late, stemming from a handful of voices, primarily in the law and statistical communities. While strong scrutiny is a healthy and necessary part of any scientific endeavor, much of the current criticism leveled at firearm and toolmark analysis is, at best, misinformed and, at worst, punditry. One of the most persistent criticisms stems from the view that as the field lacks quantified random match probability data (or at least a firm statistical model) with which to calculate the probability of a false match, all expert testimony concerning firearm and toolmark identification or source attribution is unreliable and should be ruled inadmissible. However, this critique does not stem from the hard work of actually obtaining data and performing the scientific research required to support or reject current findings in the literature. Although there are sound reasons (described herein) why there is currently no unifying probabilistic model for the comparison of striated and impressed toolmarks as there is in the field of forensic DNA profiling, much statistical research has been, and continues to be, done to aid the criminal justice system. This research has thus far shown that error rate estimates for the field are very low, especially when compared to other forms of judicial error. The first purpose of this paper is to point out the logical fallacies in the arguments of a small group of pundits, who advocate a particular viewpoint but cloak it as fact and research. The second purpose is to give a balanced review of the literature regarding random match probability models and statistical applications that have been carried out in forensic firearm and toolmark analysis. |
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| Keywords: | forensic science coincidental match probability correspondence probabilities Daubert empirical error rate error rate false match error firearm and toolmark identification likelihood ratio likelihood ratio probability random match probabilities research random match probability statistics uncertainty |
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