Dr. Joseph Hefner is an assistant professor specializing in forensic anthropology and quantitative methods. His interests in forensic anthropology include the estimation of ancestry using macromorphoscopic (cranial nonmetric) traits and cranial and postcranial metrics. The focus of Dr. Hefner’s research is the standardization and quantification of macromorphoscopic traits with robust and appropriate classification statistics, including data mining techniques and machine learning methods. One aspect of this type of research is the seemingly endless need for more data. To that end, Dr. Hefner is currently establishing the Forensic Macromorphoscopic Databank at MSU, with a grant provided by the National Institute of Justice. Dr. Hefner’s professional activities center on forensic anthropological method and theory and statistical approaches to biological anthropology, including biodistance analysis, categorical data analysis, geometric morphometric methods, data excavation, and parametric/nonparametric classification statistics.
Dr. Hefner’s graduate students participate in current research on cranial macromorphoscopic traits and pursue their own academic/applied interests.
Dr. Hefner is a board certified forensic anthropologist (D-ABFA) and a founding editor of Forensic Anthropology (journal). He is a Fellow of the American Academy of Forensic Sciences, a member of the Register of Professional Archaeologists, American Association of Anatomists, Sigma Xi, and he is an Assessor for the American Society of Crime Laboratory Directors, Laboratory Accreditation Board.
Industry Expertise (3)
Writing and Editing
Areas of Expertise (8)
Categorical Data Analysis
The Joint Civilian Service Commendation Award, (professional)
The Joint Civilian Service Commendation Award, Department of Defense, Joint POW/MIA Accounting Command-Central Identification Laboratory - 2014
University of Florida: Ph.D., Anthropology 2007
University of Florida: M.A., Anthropology 2003
Mercyhurst College: P.B., Forensic Anthropology 2000
Western Carolina University: B.S., Anthropology 1997
Journal Articles (5)
2018 The development of identification standards in forensic anthropology requires large and appropriate reference samples comprising individuals with modern birth years. Recent advances in macromorphoscopic trait data collection and analysis have created a need for reference data for classification models and biological distance analyses. The Macromorphoscopic Databank (N ∼ 7,397) serves that function, making publicly available trait scores for a large sample (n = 2,363) of modern American populations and world-wide groups of various geographic origins (n = 1,790). In addition, the MaMD stores reference data for a large sample (n = 3,244) of pre-, proto- and historic Amerindian data, useful for biodistance studies and finer-levels of analysis during NAGPRA-related investigations and repatriations. In developing this database, particular attention was given to the level of classification needed during the estimation of ancestry in a forensic context. To fill the knowledge gap that currently exists in the analysis of these data, the following overview outlines many of the issues and their potential solutions. Developing valuable tools that are useful to other practitioners is the purpose of growing a databank. As the Macromorphoscopic Databank develops through data collection efforts and contributions from the field, its utility as a research and teaching tool will also mature, in turn creating a vital resource for forensic anthropologists for future generations.
2018 Welcome to Forensic Anthropology, the only journal devoted to the advancement of the science and professional development of the fields of forensic anthropology and forensic archaeology. Forensic Anthropology is an inclusive venue created to foster professional discussions about research, policy, and the application of forensic anthropology globally. Issues will (at least initially) be published quarterly and available in electronic and print format. Subscription information, submission instructions, and other details can be found on the journal’s website: http://journals.upress.ufl.edu/fa.
2018 Fractography is the study of fracture surface morphology, and it can be used to assess a material’s mechanical properties as well as to determine the underlying mechanisms leading to material failure. Fracture surfaces reveal information about fracture initiation and propagation in bone, yet little consideration has been given to bone fracture surfaces in forensic contexts. Moreover, the science of fractography has never been applied to bone in forensic anthropological contexts. Here we test the application of principles of fractography to the analysis of fractured femoral cortical bone to assess the utility of fractography in the forensic analysis of skeletal trauma. We find that features, which we term bone mirror, arrest ridges, bone hackle, wake features, and cantilever curl, can be used to reliably determine the point of fracture nucleation and direction of fracture propagation. These features can generally be seen with the unaided eye and are further enhanced using oblique lighting, contrast medium application, and low-power microscopy. This approach is reliable and can be easily and inexpensively applied in forensic anthropological examinations.
2018 As part of a much larger investigation into the use of macromorphoscopic trait data by forensic anthropologists to estimate ancestry from unidentified skeletal remains, we conducted a fourteen-year (2002-2016) intraobserver error study. Motivated by the development of a large macromorphoscopic database-which will potentially utilize data collected in 2002-quantification of observer error, the impact of technological improvements in macromorphoscopic trait data collection and observer experience is necessary. To maximize comparisons between the two samples, ten macromorphoscopic traits were assessed. Results revealed three patterns of error relating to observer experience, the introduction of new technologies, and error inherent in the method. Overall, this study found the effect of error on macromorphoscopic trait analysis could be predicted and did not significantly impact their utility.
2017 This manuscript describes the use of comparative radiography of the chest to facilitate positive identification of human remains in advanced stages of decomposition. The method reported by Stephan et al. for positive identification of dry, disarticulated skeletal elements was used on semifleshed, decomposing remains. Positive identification was established through multiple points of concordance observed in radiographs of the left and right clavicles and the C5-T1 vertebrae. This case study demonstrates the applicability of the Stephan et al.'s method in cases involving decomposing remains.