Findings and methodology are presented for a study with the goal of constructing a “black box” study modeled after the FBI/Noblis study that meets specified criteria for the discipline-wide error-rate estimate for the comparison of palmar impressions.
The following criteria should be met to establish an informative error rate for palmar impressions: 1) Palmar impressions should be presented and error rates constructed for them separate from those of distal phalanges; 2) Test impressions at different quality levels should be used and error rates calculated for each, so that meaningful comparisons to casework images can be made; and 3) Close non-matches should be incorporated to present a realistic chance of making a false-positive. In the current study, palm marks of known sources were collected from 50 individuals at six partner laboratories. The donated impressions produced 725 known source mark/exemplar pairings (cases). Marks were made on a variety of substrates using a variety of development techniques to mimic casework. Once the cases had been selected, random draws of 75 cases were made for each participant, so that each received 53 same sources and 22 different sources. In all, 12,279 analysis determinations and 9,460 comparison decisions were rendered. Each case was viewed by an average of 23 examiners. A global overview of the results for all participants. shows that as the difficulty of the comparison increases, so does the false negative error rate. This supports the concept of defining thresholds for comparison difficulty and documenting these levels in case notes. A summary is provided of false negative error rates stratified by the areas of the palm from which the mark originated. There are clearly areas of the palm that pose greater and lesser challenges to examiners.
Downloads
Similar Publications
- Forensic Discrimination of Dyed Hair Color: I. UV-Visible Microspectrophotometry
- The St. Louis Police Partnership: An Individualized Focused Deterrence Implementation Guide
- Evaluation of Cannabis Product Mislabeling: The Development of a Unified Cannabinoid LC-MS/MS Method to Analyze E-liquids and Edible Products