Statistical Evaluation of Randomly Acquired Characteristics on Outsoles with Implications Regarding Chance Co-Occurrence and Spatial Randomness
Nicole Richetelli · 2020
Footwear evidence holds tremendous forensic value, owing to its ability to formulate linkages between victims, suspects and scenes. Naturally, the strength of these linkages is a function of the perceived clarity, quality and rarity of class, subclass and randomly acquired characteristics (RACs), which are the fundamental outsole features used to formulate source associations. In order to reach a conclusion when performing a footwear comparison, forensic examiners must assign value to the observed similarities and differences that exist between questioned crime scene and test impressions. Embedded within this process is an evaluation of the random association between unrelated shoes as a function of both class and acquired wear characteristics. To date, weight of evidence within this space has been largely informed by the training and subjective casework experience accumulated by an examiner over the life of his or her career. In pursuit of supporting the foundational validity of this comparison process, this research sought to quantify the chance association of RACs on unrelated shoes and the spatial distribution of these features on outsoles, with the long-term goal of aiding weight of evidence assessments in forensic footwear examinations. Using a large-scale database of 1,300 unrelated outsoles, the position and shape of 72,306 RACs was investigated. Features with consistent position and shape-classification were pairwise compared and sorted using a numerical estimate of similarity. Based on this assessment, more than 91,000 of the most quantitatively similar features were visually evaluated in order to model the relationship between numerical similarity and visual indistinguishability. Using this model, more than 1 million additional feature comparisons were evaluated in order to predict the potential for visual confusion. Subsequently, empirical and modeled probabilities of indistinguishability were combined with the chance for positional overlap to yield location- and shape-specific estimates of chance association. The results indicated that RACs exhibit high discriminating potential, with median chance associations ranging from 1 in 541,276 to 1 in 18,031,824, depending upon shape. However, additional inspection revealed that chance association was not constant across an outsole. Given this secondary observation, the spatial distribution of RACs on outsoles was further investigated. In order to conduct this analysis, a set of over 1.7 million null and 1.9 million alternative contact-modified synthetic distributions were simulated for comparison against the collected empirical data. Results indicated that Poisson null distributions (both synthetic and modeled) well-describe the frequency of RACs across approximately 64% of an outsole. Moreover, the regions not well