This is the Final Summary Overview of a study that examined 1) the benefits and limitations of using objective statistical models to determine the sufficiency of a latent print at the analysis stage and 2) the benefits and limitations of using statistical models for calculating likelihood ratios (LR) of close non-matches (CNM) and verified latent print identifications at the evaluation stage.
The project relied on a large dataset of casework latent prints maintained and examined by the Denver Police Department Crime Laboratory (DPDCL), which contained latent prints collected as evidence within the City and County of Denver. Analytical information documented included the presence of pattern type, ridge characteristics, movement distortion effects, and substrate interference. The project concludes that it is inappropriate to decide whether likelihood ratio (LR) information would be considered beneficial to criminal justice policy without additional research and consultation with the court system regarding project findings. Additional research would assist in determining how critical the court deems LRs for latent-print examiner testimony compared to the current testimony practices, given the significant increase in time spent per case. This study also concluded that additional research is needed to expand the capabilities of available LR software, particularly the inclusion of differences between a latent print and a known print to provide more accurate LR. 4 figures, 1 table, and 2 references
National Institute of Justice (NIJ)
810 Seventh Street NW, Washington, DC 20531, United States
US Dept of Justice NIJ Pub
810 Seventh Street, NW, Washington, DC 20531, United States
Report (Grant Sponsored)
United States of America