Forensic Anthropology At La Línea: Advances In Computational Methods For The Identification Of The U.S.-México Border Dead.

C.E. Credits: P.A.C.E. CE Florida CE
Speaker
  • Senior Research Scientist, Center for Comparative Studies in Race and Ethnicity, Stanford University
    Biography
      Bridget FB Algee-Hewitt, PhD, is a broadly trained anthropologist, who studies how biological - skeletal and genetic - and cultural traits vary among contemporary peoples, across space and through time. As a forensic scientist, she develops new computational methods, using machine learning/AI and geographic mapping algorithms, and hands-on DNA and osteology laboratory approaches to improve estimation of the personal identity parameters - like sex, ancestry, stature, and age - that are essential components of the biological profile used in the identification of unknown human remains. Her social justice work focuses on migration, displacement, poverty, and violence in Latin America, addressing, in particular, the crisis of migrant deaths along the US-México border. As an advocate for immigrant rights globally, she draws upon her community-engaged research with refugee groups to inform her expert testimony for asylum petitions and to support her recommendations for policy development and reform.

    Abstract

    The ever-increasing number of deaths along the U.S.-México border and the diversification in the demographic characteristics of the Latin American migrants, who perish in this region, demand new approaches to forensic anthropological casework. Current rates of positive identification must be improved so that the unknown forensic case can be re-associated with the once living person, the individual’s remains returned to the family, and the needs of social justice can be served. Studies using genetic and skeletal data alike have revealed differences in ancestry for many of the spatially-defined groups that are distributed across Latin America. Demographic research on migration networks for México have found distinctive transit pathways El Norte, whereby migrants of different origins are associated with particular destinations across the U.S.-México border. In this presentation, I will argue for the value of extending these two lines of research on the living to the identification of the dead for methodological improvement in the forensic context. Specifically, I will show how, when combined, information on geographic variation in ancestry composition and spatial trends in migration are critical to building statistical models optimized for the probabilistic determination of personal identity for migrant fatalities recovered along our southern border. By quantifying these biogeographic patterns in terms of the unknown individual’s relative estimates of continental-level ancestry, geographic location of origin, and place of death along the border, I will demonstrate that it is possible to predict the individual’s sending region. Through this discussion, I will illustrate how geospatial and machine learning methods can be used to improve traditional forensic procedures by directing case investigation, providing probable locations for finding next of kin, and reducing the pool of potential matches from missing persons lists. In conclusion, I will advocate for adopting a bio-cultural approach to identification that leverages multi-disciplinary methods to aid in this human rights work.

    Learning Objectives:

    1. Introduce the concept of biogeography and explain its value as an alternative biological profile parameter to single-group ancestry

    2. Demonstrate how novel geospatial and machine learning methods can be used to infer place of origin for unknown remains

    3. Explain how trihybrid ancestry estimates can be generated from skeletal data using admixture algorithms comparable to those employed in forensic genetics


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