Forensic Anthropology

Stephen David Ousley (1961-2022)

2024-01-20T10:42:34-05:00

Dr. Steve Ousley—in full, Stephen David Ousley, PhD—American biological anthropologist, data analyst, general contrarian, and well-known beer aficionado, was at the forefront of forensic and biological anthropology. He was a quantitative star in the anthropological universe. On 6 November 2022, Steve succumbed to cancer, leaving behind a legacy of courage and dedication. His impact on the field of biological anthropology will be remembered for generations to come. Colleagues, friends, and family alike will always hold him dear in their hearts, celebrating his accomplishments and the unwavering spirit with which he approached life. Steve’s life and legacy serve as an inspiring reminder of the power of determination, perseverance, and dedication. His contributions to forensic anthropology and his dedication to friends and family exemplify the depth of his character. Although he is no longer with us, his legacy lives on through his work, the lives he touched, and the memories he left behind.

Ousley—Repatriation and the Smithsonian

2024-10-11T16:29:25-04:00

The repatriation of Native American human remains has been a significant issue at the Smithsonian’s National Museum of Natural History for the past 40 years. Following the requirements of the National Museum of the American Indian Act of 1989, which mandated the use of the best available scientific and historical documentation to trace tribal origins, the Museum created the Repatriation Osteology Laboratory, which Stephen Ousley directed for the majority of his career at the Smithsonian. For nearly a decade, Ousley led exemplary osteological research in the service of repatriation, applying techniques of forensic anthropology, innovating craniometric and statistical analyses, and working collaboratively with the museum’s Native American partners. His high standards for the research and objective treatment of osteological evidence requiring critical thinking have served as a model for the Repatriation Office, students, and Native and non-Native researchers he worked with during his time at the Smithsonian and beyond.

Short Time, Big Impact

2024-09-03T11:28:58-04:00

Academic impact is often measured in the amount of publications, number of students mentored, and what seminal research is contributed to a field. However, beyond this physical component of a person’s legacy is the influence they have on the field’s current and future practitioners and their perceptions of the field. Stephen Ousley’s contributions to both academic impact and lasting influence on its members are innumerable. This article seeks to provide a retrospective look into his teaching and mentorship style, highlight some of his contributions to the field, and then provide a prospective of new research Steve envisioned based on his last project, which was presented at the 2023 AABA conference.

The Second Revolution in Forensic Anthropology

2024-04-15T11:25:36-04:00

This article tells the story of Steve Ousley’s vision for skeletal data in anthropology: an update to the Forensic Data Bank for the twenty-first century, based on the Commingled Remains Analytics (CoRA) ecosystem, with the aim of accumulating high-quality “big data” and harnessing artificial intelligence/machine learning algorithms for research, casework, and education. We share our recollections of events leading up to a meeting of the minds at the Defense POW/MIA Accounting Agency (DPAA) at Offutt Air Force Base in Nebraska in 2019 and offer a few thoughts about next steps. We have tried to tell this story through Steve’s eyes, using his words to describe his vision by including several emails that communicate his love of data, spirit, and wonderful sense of humor.

Roadmap to the Future

2024-04-15T10:30:38-04:00

Steve Ousley was our friend, colleague, and collaborator. This article reflects on the impact of his work in modernizing three-dimensional cranial data collection. By building the 3Skull software program, something he is less well known for than FORDISC, he allowed generations of researchers to collect cranial and other skeletal coordinate data in a meticulous yet efficient manner. This contribution not only allowed for the creation of new knowledge, but it also served to facilitate repatriation at the Smithsonian. At the time of his death, Steve was working on the next great leap in skeletal data collection, virtual osteology. We discuss this growing component of our field, including how it is grounded in Steve’s prior work, ethical concerns, and promise for the future.

Using Multivariate Analysis within the Vertebral Column to Identify Individual Vertebrae

2024-10-11T16:41:42-04:00

This article demonstrates the utility of a multivariate analysis of vertebrae in an applied context. The human vertebral column is a morphologically complex group of elements. Current methods rely on morphological characteristics to classify isolated vertebrae qualitatively. This research provides a bridge between morphological assumptions for vertebral designations and quantitative classification. These osteometric methods and statistical analyses provide quantifiable information relating to the accuracy of vertebrae classification. The sample used for this analysis consists of osteometric vertebral measurements from intact vertebral columns from 59 individuals. In order to assess the potential for these vertebral measurements to classify vertebrae, regional grouping models based on vertebral column segments were developed and analyzed. The data were tested for multivariate normality and homogeneity of variance–covariance matrices in order to comply with the assumptions required by the statistical analyses used for classification. Linear discriminant function analysis was used for classification. The sensitivity and specificity of each vertebral group prediction were used for evaluation. This research demonstrates that by using osteometric methods and statistical analyses, the accuracy of vertebrae classification is quantifiable. This method has been developed to assist with the sorting and analysis of commingled and fragmentary skeletal remains.

Differences in the Shape of the Frontal Bone between 20th-Century Euro-Americans and Germans

2024-10-11T16:48:13-04:00

Geometric morphometrics is a very useful but rarely applied concept in forensic anthropology. It uses information on the shape of an object for data analysis. For this study, geometric morphometrics has been used to compare the shape of the frontal bone between a German and a Euro-American sample (both early 20th century). Results were compared using size-only, shape-only and size-and-shape combined.

Results show that the frontal shapes of the two study populations can clearly be distinguished from one another. The best classification results could be achieved when combining size and shape data for analysis. Centroid size showed significant variation by group and sex, and that Euro-Americans are more sex dimorphic than Germans. We conclude that shape data provides a considerable amount of extra information for population affinity estimation, even on a single cranial bone like the frontal. A broader application of geometric morphometrics in forensic anthropology could thus help generating a more reliable biological profile, as well as providing additional insight into German-American morphometric differentiation.

MaMD Analytical 1.0

2024-04-08T09:59:25-04:00

We outline the functionalities and application of MaMD Analytical—a new, freely available software package for the estimation of population affinity using human cranial macromorphoscopic (MMS) traits. MaMD Analytical captures MMS scores using line drawings following the procedures outlined by Hefner and Linde (2018). MaMD Analytical generates classifications (with estimated likelihoods) into forensically significant populations using an artificial neural network and reference samples drawn from the Macromorphoscopic Databank (MaMD). Summary data (sensitivity, specificity, x-validated classification accuracies) are provided. In this article, we apply MaMD Analytical to a large sample of identified individuals not used in the original model building to assess utility and demonstrate the typical outputs for MaMD Analytical. MaMD Analytical facilitates construction of the biological profile and provides a number of safeguards in summary statistics as a valuable addition to the forensic anthropological analysis toolkit. MaMD Analytical is written in
the open-source R environment integrating a previously developed artificial neural network model to estimate population affinity using well-documented and validated approaches.

Exploring Mutual and Exclusive Biological Information in Cranial Metric and Morphological Variables

2024-07-23T11:02:29-04:00

Evidence suggests that both craniometric and cranial morphoscopic (MMS) traits elucidate information about cranial phenotypic variation and are appropriate proxies of genetic variation. Yet, the types of variation underlying the expression of craniometric and MMS traits are unknown. Recent data sets of matched skeletal metric and MMS data enable a holistic exploration into the cranial phenotype. Subsequently, the current study strived to provide a better understanding of cranial data used to measure human variation in biological anthropology. Two contemporary U.S. samples were pooled to increase sample size and diversity. Following down-sampling for balanced representation of reported biological males and females, the final sample comprised 310 individuals. Twenty-five interlandmark distances and 11 MMS traits were used in numerous analyses: polychoric correlation, mutual information, mixed factor analysis, and factor analysis of mixed data. No demographic information besides reported biological sex was retained in the analyses. The results consistently indicate that having information about one data type does not provide certainty of another data type, even when the variables are analogous (i.e., nasal breadth and nasal aperture width). Findings reassert that skeletal variables should be analyzed jointly rather than independently to best capture the cranial phenotype. The results also highlight the differential influence of biological variables, such as sexual dimorphism, on the two types of cranial data. As data availability increases and additional matched data-type comparisons can be conducted, we will continue to gain a better understanding of the complexities surrounding skeletal phenotypic variation, evolutionary theory, and population affinity

We Think There’s Been a Glitch

2024-10-11T17:01:35-04:00

Forensic anthropology plays a pivotal role in the medicolegal system analyzing skeletal remains in forensic casework. With the increased incorporation of artificial intelligence (AI) and machine learning (ML), their continued application in the field promises
enhanced efficiency and accuracy in identification processes, trauma analyses, and decision-making. However, the integration of AI/ML also raises critical ethical concerns. The use of any technology involving human skeletal remains poses challenges related to privacy, consent, and the potential for dehumanization. Furthermore, the risk of bias within algorithms cannot be ignored—specifically, the inadvertent perpetuation of existing biases in training data, which can lead to incorrect identifications or skewed results. Addressing these concerns requires a balanced approach. Transparency in AI/ML design, clear guidelines for data collection and integration, and ongoing evaluation of algorithmic performance are essential. Additionally, interdisciplinary collaboration between anthropologists, ethicists, computer scientists, and legal experts would be a crucial step forward to ensure that the benefits of AI/ML are maximized while capturing the accountability and responsibilities within a legal and ethical context. Only through such an integrated approach can the potential of AI/ML in forensic anthropology be utilized as a tool responsibly, preserving the dignity of the deceased.

What Should Be Typical about the Way We Calculate Typicality?

2024-04-15T10:54:33-04:00

The probability of correct classification, and ultimately identification, lies at the heart of forensic anthropological analyses. To this end, practitioners rely on a variety of ways to assess the error or uncertainty of their estimates, including the use of statistically
based analytical packages such as FORDISC. This article addresses typicality probabilities and specifically examines issues and assumptions with calculating F-statistic typicalities both statistically and within FORDISC. It uses multiple methods to calculate F-test typicality from publicly accessible craniometric data drawn from the Howells data set, a data set also included as reference groups within FORDISC. While the results of these calculations agree across various F-tests proposed by different authors, the results do not match the “TypF” values generated by FORDISC when using the “resubstitution” option. Through additional calculations and various reproducibility exercises, the authors demonstrate how and why “TypF” in FORDISC produces erroneous typicality values with the “resubstitution” option. They also identify the correct equation to incorporate into the software to rectify this problem. This work represents the logical conclusion of a long-running debate the authors had with Stephen D. Ousley and a desire to improve the accuracy and interpretability of analyses generated in FORDISC.

Ongoing Work with Adult Skeletal Age Estimation

2024-10-11T17:07:18-04:00

Improving adult age-at-death estimates using visible features of the human skeleton has been the subject of much research because such assessments are critical elements of forensic investigations and bioarchaeological studies. Beginning in 2014, a National Institute of Justice (NIJ)–funded research team developed a set of age-informative skeletal traits; collected reference data from collections in the United States, Portugal, Thailand, and South Africa; evaluated traits for their applicability; and developed alternative ways to generate age estimates from those traits. Here we present a comparison of two ways to produce age estimates: Stephen D. Ousley’s machine learning approach available as beta version computer software (TA3-ML) and an analytical procedure that originated with the version of transition analysis introduced two decades ago with different skeletal characteristics (TA3-TA). The two approaches are evaluated using the same 41 modern Portuguese and American skeletons. Both methods rely on NIJ-project skeletal data (TA3), but the number of traits used differs, as do reference sample sizes and compositions. Estimates generated through TA3-TA more closely approximate reported ages throughout adulthood than those from TA3-ML. Nevertheless, there remains a problem with underestimation in the TA3-TA approach, and neither method is ready for widespread implementation. Ongoing work is being directed toward resolving these issues by adjusting the mix of NIJ-project traits used in TA3-TA.

Craniometric Relationships of Migrant Victims of the April 18, 2015 Shipwreck Off the Coast of Libya

2024-07-12T11:45:10-04:00

One of the most tragic events involving African migrants’ attempts to get to Europe was the 2015 shipwreck off the coast of Libya. More than 300 crania were recovered and are currently in the Laboratory of Forensic Anthropology and Odontology, Milan, Italy, where attempts are being made to identify them. This paper analyzes the cranial morphometrics in relation to what is known of African cranial variation. It also addresses questions of population subdivision on the ship as well as secular changes that may be reflected in cranial morphology. Crania were digitized using the 3skull software, which also computes Howells measurements from the coordinates. Migrant crania were compared to African reference samples consisting of both 19th-century sub-Saharan West Africans and East Africans. Statistical procedures were discriminant and canonical variate analysis and Mahalanobis distances. K-means unsupervised clustering was also used. Results showed that the migrant samples differed from the 19th-century samples systemically; the differences consisted mainly of lower facial projections and higher cranial vaults and bases. Position on the ship, whether on the deck or below in the holds, showed subdivision. Holds had a higher proportion of West Africans, and the deck had a higher proportion of East Africans. K-means clustering also found groups contrasting between the deck and the holds. Comparing migrant cranial morphology to 19th-century Africans using variables that respond to secular change showed that migrants reflect changes that have occurred in Africa over the past 200 years. We conclude that morphometric analysis can provide useful information concerning the composition of unidentified victims of tragic events such as the 2015 shipwreck.

Steven D. Ousley

2024-04-15T12:36:37-04:00

Early in his career, Steven D. Ousley established his view on the need for biological anthropologists to provide empirical
support for their findings. He, like many of his mentors and contemporaries, became acutely aware of the need for more statistical rigor in forensic anthropology. His research and the scholarly products he produced explored the relationship and linkage between method and theory, between what can be observed, what can be explained, and what can be quantified. Driven by an insatiable curiosity and a commitment to advancing knowledge, Steve’s work has left an indelible mark on the intersection between biological anthropology and statistical approaches to the study of human variation and has enriched our understanding of population affinity estimation. With a career characterized by rigor, innovation, and a passion for discovery, his pioneering insights continue to reverberate through academia and the applied world encompassing forensic anthropology. As we delve into this collection of scholarly works, we embark on a journey through the intellectual landscape Steve so profoundly shaped, celebrating his legacy and the lasting impact of his ideas. We present herewith a compilation of Steve’s works, thesis, dissertation, published papers, grants and awards, software, student mentorships, and data collection activities. These illustrate the breadth of his knowledge and contributions to our discipline.

The Machines are Winning

2024-10-11T15:59:33-04:00

Stephen D. Ousley left us too damn early. We were not expecting it, so the hole he left is felt, in one way or another, nearly every day. The many words you are about to read cover only a hair’s breadth of his contributions and only scratch the surface of his enormous influence on a wide variety of topics in the field and the many research methods used by forensic and biological anthropologists today. To honor Steve Ousley, his friends and colleagues, former students, and family members produced this collection of papers. This Festschrift should have been while he was alive—to thank him, honor him, and recognize his many and varied contributions. But that was not the case, so here we present a posthumous honor to our friend.