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Universal methodology for developing univariate sample-specific sex determination methods: an example using the epicondylar breadth of the humerus
Institution:1. Department of Sociology and Anthropology, University of Windsor, Windsor, Ontario N9B 3P4, Canada;2. Departamento de Zoologia e Antropologia (Museu Bocage), Museu Nacional de História Natural, Rua da Escola Politécnica, 58, 1269-102 Lisboa, Portugal;3. Department of Anthropology, McMaster University, Hamilton, Ontario L8S 4L9, Canada;1. Laboratoire de Médecine Légale et d’Anthropologie médico-légale, Université de Nice Sophia Antipolis, Faculté de Médecine, 28 Avenue de Valombrose, 06107 Nice cedex 2, France;2. Edhec Bussiness School, 393 Promenade des Anglais, BP 3116, 06202 Nice Cedex 3, France;3. CEPAM (Cultures et Environnements, Préhistoire, Antiquité, Moyen Âge), UMR7264-CNRS Université Nice Sophia Antipolis, Campus Saint-Jean d’Angély 3, 24, avenue des Diables Bleus, 06357 Nice Cedex 4, France;1. Department of Medical Biology, Section Clinical Anatomy and Embryology, Academic Medical Center, University of Amsterdam, The Netherlands;2. Department of Anthropology, University of Nevada, Reno, NV, USA;3. Department of Anatomy, University of Pretoria, South Africa;4. Department of Radiology, Academic Medical Center, University of Amsterdam, The Netherlands;5. Department of Pathology, Academic Medical Center, University of Amsterdam, The Netherlands;6. Netherlands Forensic Institute, The Hague, The Netherlands;1. Departamento de Anatomía, Facultad de Medicina, Universidad Nacional Autónoma de México, Av. Universidad 3000, UNAM-C.U., Coyoacán, Ciudad de México 04510, Mexico;2. Posgrado en Antropología Física, Escuela Nacional de Antropología e Historia, Periférico sur y Zapote s/n, Isidro Fabela, Tlalpan, Ciudad de México 14030, Mexico;1. Research Centre for Anthropology and Health, Department of Life Sciences, University of Coimbra, Coimbra, Portugal;2. Laboratory of Forensic Anthropology, Department of Life Sciences, University of Coimbra, Coimbra, Portugal;3. Interdisciplinary Center for Archaeology and Evolution of Human Behavior, University of Algarve, Faro, Portugal;4. Centre for Functional Ecology, Department of Life Sciences, University of Coimbra, Coimbra, Portugal;1. Research Centre for Anthropology and Health, Department of Life Sciences, University of Coimbra, Coimbra, Portugal;2. Interdisciplinary Center for Archaeology and Evolution of Human Behavior, University of Algarve, Faro, Portugal;3. Laboratory of Forensic Anthropology, Department of Life Sciences, University of Coimbra, Coimbra, Portugal;4. Centre for Functional Ecology, Department of Life Sciences, University of Coimbra, Coimbra, Portugal;5. Archaeosciences Laboratory, Directorate General for Cultural Heritage and LARC/CIBIO/InBIO, Lisboa, Portugal
Abstract:In this paper we present a new methodology for developing sample-specific metric sex determination methods using unidentified individuals that can be applied to archaeological samples. This methodology does not require the assessment of sex of a large sample from pelvic morphological features as a first step in developing the method and instead is developed from a sample of individuals with sex unknown. The procedure involves using the overall mean of a measurement collected from the sample of unknowns as the discriminant criteria for determining the sex of the individuals in that same sample. Experiments with various sample sizes and sex ratios using distal humerus measurements from the Coimbra Collection (Portugal) suggest that allocation accuracies of 83–96% can be expected when the sample used to develop the method is greater than 40 individuals and the sex ratio is less than 1.5:1. The utility of the methodology is explored using the Lisbon Collection (Portugal) and an archaeological sample from Belleville (Canada) is tested as an example. The Lisbon Collection data indicate that joint measurements of long bones will provide the highest allocation accuracies. The results from the Belleville sample confirm that humerus joint measurements consistently provide the highest allocation accuracies (88–100%) even when the sex ratio in the sample used to develop the method is estimated at 1.9:1.
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