Literature DB >> 19226642

Estimation and evidence in forensic anthropology: sex and race.

Lyle W Konigsberg1, Bridget F B Algee-Hewitt, Dawnie Wolfe Steadman.   

Abstract

Forensic anthropology typically uses osteological and/or dental data either to estimate characteristics of unidentified individuals or to serve as evidence in cases where there is a putative identification. In the estimation context, the problem is to describe aspects of an individual that may lead to their eventual identification, whereas in the evidentiary context, the problem is to provide the relative support for the identification. In either context, individual characteristics such as sex and race may be useful. Using a previously published forensic case (Steadman et al. (2006) Am J Phys Anthropol 131:15-26) and a large (N = 3,167) reference sample, we show that the sex of the individual can be reliably estimated using a small set of 11 craniometric variables. The likelihood ratio from sex (assuming a 1:1 sex ratio for the "population at large") is, however, relatively uninformative in "making" the identification. Similarly, the known "race" of the individual is relatively uninformative in "making" the identification, because the individual was recovered from an area where the 2000 US census provides a very homogenous picture of (self-identified) race. Of interest in this analysis is the fact that the individual, who was recovered from Eastern Iowa, classifies very clearly with [Howells 1973. Cranial Variation in Man: A Study by Multivariate Analysis of Patterns of Difference Among Recent Human Populations. Cambridge, MA: Peabody Museum of Archaeology and Ethnology; 1989. Skull Shape and the Map: Craniometric Analyses in the Dispersion of Modern Homo. Cambridge, MA: Harvard University Press]. Easter Islander sample in an analysis with uninformative priors. When the Iowa 2000 Census data on self-reported race are used for informative priors, the individual is clearly identified as "American White." This analysis shows the extreme importance of an informative prior in any forensic application. 2009 Wiley-Liss, Inc.

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Year:  2009        PMID: 19226642     DOI: 10.1002/ajpa.20934

Source DB:  PubMed          Journal:  Am J Phys Anthropol        ISSN: 0002-9483            Impact factor:   2.868


  8 in total

1.  Craniometric study for sex determination in a Thai population.

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Journal:  Anat Cell Biol       Date:  2015-12-21

2.  Validation of a physical anthropology methodology using mandibles for gender estimation in a Brazilian population.

Authors:  Suzana Papile Maciel Carvalho; Liz Magalhães Brito; Luiz Airton Saavedra de Paiva; Lucilene Arilho Ribeiro Bicudo; Edgard Michel Crosato; Rogério Nogueira de Oliveira
Journal:  J Appl Oral Sci       Date:  2013 Jul-Aug       Impact factor: 2.698

3.  Maori heads (mokomokai): the usefulness of a complete forensic analysis procedure.

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Journal:  Forensic Sci Med Pathol       Date:  2014-04-19       Impact factor: 2.007

4.  Accuracy of robotic coil positioning during transcranial magnetic stimulation.

Authors:  Stefan M Goetz; I Cassie Kozyrkov; Bruce Luber; Sarah H Lisanby; David L K Murphy; Warren M Grill; Angel V Peterchev
Journal:  J Neural Eng       Date:  2019-09-17       Impact factor: 5.379

5.  mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture Models.

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6.  Morphology of the levator veli palatini muscle using magnetic resonance imaging.

Authors:  Jamie L Perry; David P Kuehn; Bradley P Sutton
Journal:  Cleft Palate Craniofac J       Date:  2011-10-24

7.  A glimpse into the early origins of medieval anatomy through the oldest conserved human dissection (Western Europe, 13(th) c. A.D.).

Authors:  Philippe Charlier; Isabelle Huynh-Charlier; Joël Poupon; Eloïse Lancelot; Paula F Campos; Dominique Favier; Gaël-François Jeannel; Maurizio Rippa Bonati; Geoffroy Lorin de la Grandmaison; Christian Hervé
Journal:  Arch Med Sci       Date:  2013-02-28       Impact factor: 3.318

8.  Efficiency of the Adjusted Binary Classification (ABC) Approach in Osteometric Sex Estimation: A Comparative Study of Different Linear Machine Learning Algorithms and Training Sample Sizes.

Authors:  MennattAllah Hassan Attia; Marwa A Kholief; Nancy M Zaghloul; Ivana Kružić; Šimun Anđelinović; Željana Bašić; Ivan Jerković
Journal:  Biology (Basel)       Date:  2022-06-15
  8 in total

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