All individuals were of known age, sex, and birth region. The complex population and demographic history of Colombia makes ancestry assessment particularly difficult in that country. To that end, this study explored inter-regional variation throughout Antioquia, using birthplace to determine whether forensic anthropologists can provide finer levels of detail beyond identifying an unknown set of human remains as 'Colombian' or, more generally, Hispanic. State and local levels of identification resulting from the varied population histories of each state within Antioquia enabled finer resolution, but only to a degree of certainty. Artificial neural networks (aNN) correctly classified only 18.6 percent of a validation sample, following modest classification accuracies of test/tuning (11.6 percent) and training (82.8 percent) samples to original birthplace. As with most neural networks, overfitting is an issue with these analyses. To remedy this overfitting and to document the applicability of aNNs to the assessment of ancestry in Colombia, the study pooled the sample of Colombian data and compared that to modern American samples. In those analyses, the best aNN model correctly classified 48.4 percent (validation) of the sample. Given these results, finer levels of analysis in Colombia are not yet possible using only macromorphoscopic trait data. (publisher abstract modified)
Macromorphoscopic trait expression in a cranial sample Medellin, Colombia
NCJ Number
255189
Journal
Forensic Science International Volume: 266 Dated: September 2016 Pages: 574.e571-574.e578
Date Published
September 2016
Length
8 pages
Annotation
The primary purpose of this research was to document cranial macromorphoscopic trait variation in a sample of 244 individuals from Antioquia, Medellin, Colombia, using methods previously developed in the United States.
Abstract