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Worldwide Population Variation in Pelvic Sexual Dimorphism: A Validation and Recalibration of the Klales et al. Method

NCJ Number
252251
Journal
Forensic Science International Volume: 277 Dated: August 2017 Pages: 259.e1-259.e8
Author(s)
Michael W. Kenyhercz; Alexandra R. Klales; Kyra E. Stull
Date Published
2017
Length
1 page
Annotation
In this study, a total of 1,915 innominates from four diverse geographic populations - U.S. Blacks and Whites, South-African Blacks and Whites, Thai, and unidentified Hispanic border-crossers - were scored in accordance with Klales et al. (2012).
Abstract

Sex estimation is an integral aspect of biological anthropology. Correctly estimating sex is the first step to many subsequent analyses, such as estimating living stature or age-at-death. Klales et al. (2012) provided a revised version of the Phenice (1969) method that expanded the original three traits (ventral arc, subpubic concavity/contour, and medial aspect of the ischio-pubic ramus) into five character states to capture varying degrees of expression within each trait. The Klales et al. (2012) [6] method also provided associated probabilities with each sex classification, which is of particular importance in forensic anthropology; however, the external validity of this method must be tested prior to applying the method to different populations from which the method was developed. In the current study, trait scores for each innominate were entered into the equation provided by Klales et al. (2012) for external validation. Additionally, recalibration equations were calculated with logistic regression for each population and for a pooled global sample. Validation accuracies ranged from 87.5 percent to 95.6 percent, and recalibration equation accuracies ranged from 89.6 percent to 98 percent total correct. Pooling all samples and using Klales' et al. (2012) equations achieved an overall validation accuracy of 93.5 percent. The global recalibration model achieved 95.9 percent classification accuracy and can be used in diverse worldwide populations for accurate sex estimation without the need for population-specific equations. (Publisher abstract modified)