As submitted by the proposer:
The current forensic anthropological techniques and methodologies incorporating cranial nonmetric, or macromorphoscopic, traits to assess the ancestry of skeletonized and unknown human remains are of uncertain reliability, due in large part to a lack of reference and baseline data associating these traits to the population groups frequently encountered in medico-legal death investigation. This research will address this significant gap in best practice and minimum standards through an effort that: (1) correlates ancestry, character state expression, and modern human variation in a large and globally-diverse sample; (2) collects data on macromorphoscopic traits from current forensic case files at medical examiner offices and forensic anthropology laboratories across the country to establish a standardized database (the Macromorphoscopic Databank); and, (3) develops appropriate statistical methods to be used in the identification of ancestry within a computer program.
This proposal identifies a significant gap in best practice in forensic anthropological method and theory. This research will develop standard and novel statistical classification methods that minimize among group variation (and maximize between group variation) to identify patterns in the distribution of macromorphoscopic traits. The predictive analysis will use classification models generated using data collected from known skeletal populations (i.e., individuals of known age, sex, ancestry, etc.). The ultimate aim is the computation of a statistical probability of group membership based on the observed suite of macromorphoscopic traits. To assist researchers and professionals in forensic anthropology, a computer program that compares the unknown individual to a known database and then calculates the probability, or likelihood, of group membership will be developed.
This project contains a research and/or development component, as defined in applicable law.