A skeletal assessment of ancestry relies on morphoscopic traits and skeletal measurements. Using a sample of American Black (n = 38), American White (n = 39), and Southwest Hispanics (n = 72), the present study investigates whether these data provide similar biological information and combines both data types into a single classification using a random forest model (RFM). Our results indicate that both data types provide similar information concerning the relationships among population groups. Also, by combining both in an RFM, the correct allocation of ancestry for an unknown cranium increases. The distribution of cross-validated grouped cases correctly classified using discriminant analyses and RFMs ranges between 75.4% (discriminant function analysis, morphoscopic data only) and 89.6% (RFM). Unlike the traditional, experience-based approach using morphoscopic traits, the inclusion of both data types in a single analysis is a quantifiable approach accounting for more variation within and between groups, reducing misclassification rates, and capturing aspects of cranial shape, size, and morphology.
This article focuses on the role of the forensic anthropologist in the identification of migrant remains in the American Southwest. These migrant cases present a unique set of circumstances that necessitate a regional approach to identification. The Pima County Office of the Medical Examiner (PCOME), located in Tucson, Arizona has developed best practices that facilitate high identification rates of migrant deaths. These best practices have provided a foundation for other agencies that are faced with similar issues; namely, developing specific protocols for migrant deaths, working with nongovernmental humanitarian organizations, and sharing information have maximized identification efforts. In 2012, Texas surpassed Arizona in the number of migrant deaths. The Forensic Anthropology Center at Texas State (FACTS) began identification efforts for migrant remains found in Brooks County, Texas in 2013. Informed by best practices from the PCOME, FACTS has made successful identifications. Descriptions of the processes at both the PCOME and FACTS are described in detail.
Racial designations have evolved over the years to accommodate the changes in our population demographics. The Federal Office of Management and Budget (OMB) has developed Federal Standards to assist with the uniform documentation and reporting of race and ethnicity. A minimum of five defined categories currently exist for race (American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander and White). Ethnicity is separated into either Hispanic origin or Non-Hispanic origin. Current death certificates allow for the selection of one or more races; however, only one ethnicity may be chosen. Race of unknown decedents is either based subjectively on the observer's opinion or, in severely decomposed or skeletal remains, by anthropological analysis utilizing sound statistical methodology. If the data and statistical analysis suggest a good classification, the race determination will be correct more often than not. Information obtained from the National Missing and Unidentified Persons System (NamUs) indicates that absence of race determination does not hinder the identification potential. Mortality rates, life expectancy, disease risk and causes of death are often disaggregated by race and/or ethnicity. Differences in the presentation, etiology and outcomes of many diseases have been based on race and ethnicity data. Uniform collection of this data is the key to its importance. Medical examiners, coroners and others tasked with examination of decedents should utilize the defined categories set forth in the OMB Revised Standards for race and ethnicity documentation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.