This dissertation examines geographic mortality patterns and the skeletal attributes among deceased Mexican-border crossers, using a mixed-model framework, to provide insights into route selection.
The author reports on research that investigated the spatial and skeletal properties of deceased undocumented border crossers (UBCs) recovered in the southern Arizona desert, and the relationship between recovery location and country of origin. The goal of the research project was to improve country of origin prediction during the identification process. The author developed an optimized global linear model using craniometric and macromorphoscopic factors for a sample of 25 identified Mexican and Guatemalan individuals analyzed at the Pima County Office of the Medical Examiner (PCOME), and incorporated the model into several geographically weighted regression (GWR) platforms to predict country of origin. Model testing on eight individuals with presumptive Mexican identifications resulted in the correct allocation for country of origin for two individuals, and provided promising results for future allocation. The author demonstrates the potential demonstrated by this research project, emphasizing that as more individuals are identified and added to the model reference sample, the utility of the predictive method will improve. The author’s goal is to provide the forensic and humanitarian community with supplemental information to aid in the investigation of undocumented border crossers recovered from the southern Arizona desert, and to enhance the identification process in missing persons cases.
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