Sex estimation in bioarchaeological research is paramount for comparative analyses of skeletal remains and developing estimates of other demographic variables. Frequently, sex is estimated utilizing the morphology of pelvic and cranial bones in archaeological skeletal samples. Regrettably, these bones are often damaged, destroyed, or lost and cannot be employed for the estimation of sex. Fortunately, a variety of metric and visual sex estimation methods have been developed on modern skeletal samples with known demography. Disappointingly, due to the population specific nature of many of these metric methods, they cannot be accurately applied directly to alternate skeletal samples. However, these methods can be redeveloped and retested for archaeological skeletal samples if the proper protocol is utilized. This research utilizes the protocol for developing methods of sex estimation on samples with unknown sex developed by Murail et al. (1999). Utilizing select hand and foot bones from four prehistoric Native American skeletal samples from Alabama and Illinois, multiple discriminant functions were developed and tested on both Archaic and Mississippian Period skeletal samples. Furthermore, the four individual site samples were combined into two geographical and two temporal samples, as well as an all pooled sample in order to test the broader applicability of these methods. The results indicate that sex estimation methods can be developed on samples where sex is not known. Additionally, the discriminant functions developed produce high levels of classification for the sites, individually, as well as for the geographic, temporal, and all pooled samples. The latter suggests these functions have broader applicability for these regions and temporal periods. Moreover, the concordance rates for these functions are similar to the accuracy rates when these bones were applied to samples with known sex.

While postcraniometric sex estimation has shown promising results in North American (NA) samples, methods and standards for sex estimation in South Africa (SA) are restricted by incomplete samples and a lack of robust statistical techniques. The purpose of this study was to evaluate accuracies of sex estimation in the postcrania of modern South Africans using multivariate statistics and to compare pattern expression of sexual dimorphism in black, white and coloured groups. The study included analysing the skeletons of a total of 360 SA black, white and coloured individuals and the data of 240 NA black and white individuals (equal sex and ancestry). Sympercents expressed sexual dimorphism and where compared in the three SA groups and with the NA individuals. The creation of different bone models and a variety of multivariate models revealed the potential of multivariate techniques. Comparisons of linear discriminant analysis (LDA), flexible discriminant analysis (FDA) and logistic regression indicated which model provided the greatest discriminatory power between sex and sex-ancestry groups in SA. Among the SA groups coloureds were the most sexually dimorphic; however, overall NA individual showed the greatest differences between the sexes. Multivariate classification accuracies using bone models (various measurements from individual bones) ranged between 75% and 91%, whereas classification accuracies using multivariate subsets (combinations of measurements from different bones) ranged from 85% to 98%. When classifying into sex and ancestry, a multivariate subset using eight measurements achieved classification accuracies of up to 80%. Overall FDA achieved the best results, whereas logistic regression achieved the lowest results for both bone models and multivariate subsets. Postcranial bones achieve comparable classification accuracies to the pelvis and higher accuracies than metric or morphological techniques using the cranium in SA. Large differences in sexual dimorphism between NA and SA warrant the creation of population-specific standards and custom databases for SA. / Dissertation (MSc)--University of Pretoria, 2015. / Anatomy / MSc / Unrestricted

Sex and ancestry are most commonly estimated by anthropologists using the skull. Typically, measurements and observations are taken on the skull itself, but for the purpose of convenience, computed tomography (CT) scans are increasingly used in place of skulls in research and forensic casework. Researchers work under the assumption that the dry skull-to-CT scan ratio is one-to-one; however, research on the accuracy of CT scans is sparse. In this study, eight skulls from the Boston University Donated Skeletal Collection were scored for sex and ancestral morphological traits following Buikstra and Ubelaker (1994) and Hefner and Ousley (2014), and measured using standard cranial measurements according to Langley et al. (2016). CT scans were then taken of the eight skulls and the same morphological observations and measurements were taken using the RadiAnt 5.5.1 CT viewer. Additionally, the measurements of each skull and scan were entered into FORDISC 3.1, a software program that provides discriminant functions for the processes of sex and ancestry estimation. The measurements for each dry skull-CT scan pairing were then analyzed for variance and mean differences. The results of the morphological and metric analyses indicate that the majority of the data gathered from dry skulls did not vary significantly from the measurements taken on the CT scans. The morphological sex estimation resulted in the same estimation for each skull-to-CT scan pairing; however, the morphological ancestry estimation results indicated that skeletal information lost in CT scans can make full visualization and therefore assessment of the facial region difficult. The FORDISC 3.1 results generally support the indication that there is not a significant difference between skull and CT scan measurements, with consistent sex estimation results for each dry skull-to-CT scan pairing and consistent ancestry estimation results for the majority of the pairings. However, the sex and ancestry estimations were not always accurate considering the true ancestral backgrounds of the individuals. Based on these outcomes, it is evident that CT scans can be used to obtain reliable morphological assessments and measurements of a skull, which can then be used to estimate sex using FORDISC 3.1. However, to ensure accuracy of the sex and ancestry estimations, other methods should be used in conjunction with FORDISC 3.1.

In forensic anthropology, methods for estimating sex from the skeleton have historically been developed on skeletal collections comprised exclusively U.S. Black and white populations and thus inherently rely on ancestry estimation as a foundational component for the construction of the biological profile. However, these population-specific methods of sex estimation fundamentally limit the applicability, accuracy, and reliability of the method for use on remains of diverse population affiliations (ancestry). A reliable and population-inclusive method for estimating sex in the skeleton can serve as a useful tool for forensic investigators, especially in cases with unidentified remains where the population affiliation is indeterminate and in light of recent discourse involving the removal of ancestry estimation from the biological profile as a whole This study assessed the reliability of population-inclusive nonmetric and metric sex estimation from 3D-volume rendered computer tomography (CT) scans of the skull. The study sample was comprised of 431 individuals (242 males and 189 female) from the New Mexico Decedent Imaging Database (NMDID) and included a relatively equal distribution of African American, Asian American, European American, Latin American, and Native American population affinities. The images were obtained from the CT slices using 3D-reconstructions and volume rendering technique (VRT) in the Digital Imaging and Communications in Medicine (DICOM) viewer, exported to Meshmixer™ and then processed to isolate the skull from the postcranial skeleton and remove identifying objects. In Meshmixer™, nonmetric traits were scored following Buikstra and Ubelaker (1994) and Walker (2008) and included the supraorbital ridge/glabella, supraorbital margin, mastoid process, mental eminence and nuchal crest. The metric traits, following Spradley and Jantz (2011), included 18 points of measurement of the cranium and mandible. Binary logistic regression (BLR) and discriminant function analyses (DFA) were used to produce models and probabilities from the nonmetric a metric data respectively and an additional binary logistic regression was developed that combined both the nonmetric and metric data. Overall, the population-inclusive nonmetric and metric model produced classification accuracies that ranged from 81-87% and 86.7-87% respectively, and performed as well as population-specific models in estimating sex and were not significantly different from population-specific accuracies. When some of the population-specific models were applied across population, particularly the European American model, the classification accuracy was significantly reduced relative to the population-inclusive model. Intraobserver error was assessed for the nonmetric and metric data collection and confirmed that the nonmetric and metric methods of data collection for the volume-rendered images was consistent. The results of this study indicate that a population-inclusive nonmetric and metric models of sex estimation using the skull can be used in place of more traditional population-specific models in cases where ancestry is unknown, indeterminate, or in the event ancestry is removed from the biological profile.

Due to disproportionate violence impacting the trans community, forensic anthropologists may increasingly encounter the remains of trans and non-binary individuals; however, it is presently unknown how often trans remains are represented in casework and if practitioners have sufficient knowledge about trans personhoods. After contextualizing forensically relevant demographics for the trans community, this study uses anonymous survey data of forensic anthropologists to explore the collective knowledge of and experience working with trans remains; practitioners’ perceptions of sex and gender; and potential opportunities for trans-oriented research in forensic anthropology. The results indicate that 28.9% of respondents have worked with trans remains in casework, but 75.0% of forensic anthropologists were unfamiliar with trans-related surgical procedures. Additionally, the survey indicates that forensic anthropologists struggle with the binary nature of forensic sex estimation, with 42.4% agreeing that sex is binary and 56.2% disagreeing. Similar opposition was found with reporting gender: 39.5% indicated that gender should be reported in casework and 31.0% disagreed. Moreover, current sex estimation methods and reporting are: rigidly binary; not reflective of human biological variation; and inadequate for trans and non-binary individuals. In order to dismantle rigidly binary sex categorization, we propose the adoption of a biocultural and queer theoretical approach to forensic sex estimation and in sexual dimorphism research that challenges heteronormative assumptions, questions typological two-sex categorization, and combats the presumptions that gender and sex are stable, independent entities that convey universal meaning. Relatedly, trans-oriented research, which is supported by 95.8% of respondents, will further improve methodological accuracies. / 2022-02-23T00:00:00Z

Assigned sex estimation via the greater sciatic notch (GSN) is traditionally performed via physical/visual examination and ordinal scoring; however, this relies on the subjective assessment of morphology for typological classification which may not be reflective of human variation. Three-dimensional (3D) photogrammetry may offer a technologically advanced, low cost, and more objective alternative to assess the complex curvature of anatomical landmarks. This research explores the accuracy of photogrammetry derived 3D models by comparing digital measurements to those obtained from the skeletal elements and to streamline the application of curvature analysis for the estimation of assigned sex from the GSN. This study utilizes the left and right os coxae from 15 skeletal individuals (5 females, 10 males) from the Boston University Chobanian & Avedisian School of Medicine. A Fujifilm X-Pro2 and Fujifilm 35 mm prime lens captured 123 images per element, which were processed in Meshroom by AliceVision® to create a 3D textured mesh. The mesh was exported into Blender for cleanup, scaling, measurement, and curvature analysis. The measurements were between 96.54% and 99.94% consistent across methods and observations. The consistency between digital metric observations increased by an average of 0.07% when compared to the consistency of the dry bone measurements. Additionally, curvature analysis of the GSN correctly estimated the assigned sex of all os coxae in the sample. This study demonstrates that photogrammetry is an accurate and reliable method for the digitization of remains that enables analytical techniques to better capture skeletal variation compared to traditional methods.

When analyzing skeletal remains in bioarchaeology, the pelvis and skull provide the most accurate results for sex estimation; however, these are not always present or sufficiently preserved to provide quality data for this purpose. In addition, the amount of time spent analyzing human remains in field or museum collection contexts may be constrained. Therefore, alternate methods of sex estimation that also increase efficiency should be explored. This study aims to establish the minimum number of key measurements of the talus necessary to estimate biological sex with a level of accuracy comparable to published studies that are more time intensive in their data collection. Measures of talus width, length, height, and volume were collected on individuals from two ancient Egyptian (N=162) and three ancient Maya (N=98) archaeological populations. Set points and allocation ranges for these four measures were applied to individuals of known sex and indeterminate sex from these populations to test their accuracy and then compared with the accuracies achieved in existing research using the talus in sex estimation. The four measures used in this study resulted in comparably high accuracy in sex estimation when compared with prior research based on more extensive methods using the talus. The most significant limitation of this study was the small number of individuals available for data collection from three of the smaller site populations. Nevertheless, the method used in this study directly addresses logistical and ethical concerns surrounding the analysis of human remains as it requires less time spent handling the remains and less time spent on analysis out of the field while still providing comparable accuracy. This study also contributes population data for ancient Egyptians and ancient Maya which will facilitate further investigations of sexual dimorphism and sex estimation in these populations.

Osteological sex estimation is a key component of the biological profile in forensic anthropological casework. However, there are still limitations with current methodologies for the skull as well as inadequate classification accuracies. Therefore, the purpose of this research is to improve osteological sex classification accuracies for the skull by combining morphological and metric variables into multiple models using decision trees and random forest (RF) modeling. The sample was derived from four U.S.-based skeletal collections and consisted of 403 individuals of European American and African American population affinities. Twenty-one morphological traits and 21 metric variables of the skull were selected for analysis, and intraobserver error was assessed to determine which variables should be incorporated into the models. Additionally, two-way ANOVAs and aligned rank transformation were utilized to examine the effects of sex, age, population affinity, and secular change on the variables. To generate the trees and RF models, 80% of the sample was used for model training and 20% of the sample was used for holdout validation testing. Multiple decision trees and RF models were generated that incorporated morphological, metric, and combined variables. Models were generated for the African American and European American samples, as well as for the pooled populations. The predictive accuracy of the models was assessed utilizing the holdout validation sample and the out-of-bag error. Overall, the majority of the combined data decision trees and RF models achieved higher classification accuracies compared to the separate morphological and metric models. Additionally, the pooled and European American models frequently achieved higher accuracies compared to the African American models. The combined data models also resulted in higher accuracies compared to popular osteological sex estimation methods for the skull. Therefore, the combined data models have great potential for use by forensic anthropologists and bioarchaeologists for estimating osteological sex from the skull.

This thesis uses the metric evaluation of 3D models created from CT images. The study is based on an examination of 51 males and 55 females CT scans from recent European population and also based on a metric data (10 linear measurements) of the same geographical provenance of the mid-20th century (n=113). The purpose of our research project is to determine the degree of sexual dimorphism in current population and compare the degree of sexual dimorphism in this geographic area in the middle of the last century. Intraobserver variabilities of linear measurements were less than 2%. Both groups were statistically tested. An index of sexual dimorphism (ISD) was used to assess the level of sexual dimorphism within each sample (Paris ISD = 8,28, Marseille ISD = 6,50). The two-sided t-test indicates that the degree of sexual dimorphism is not significantly different between population from the mid-20th century and recent population (p = 0,680). The secular trend was expressed by the z-score. The results showed that changes in the pelvic bone between the two groups are not significant, since neither one of the measurements does not exceed ±2 SD. Finally, we verified the reliability of method DSP ("Diagnose Sexuelle Probabiliste") for measurements deducted from CT-derived models. The results showed the...

The main goal of a forensic anthropological analysis of unidentified human remains is to establish an accurate biological profile. The largest obstacle in the creation or validation of techniques specific for subadults is the lack of large, modern samples. Techniques created for subadults were mainly derived from antiquated North American or European samples and thus inapplicable to a modern South African population as the techniques lack diversity and ignore the secular trends in modern children. This research provides accurate and reliable methods to estimate age and sex of South African subadults aged birth to 12 years from long bone lengths and breadths, as no appropriate techniques exist. Standard postcraniometric variables (n = 18) were collected from six long bones on 1380 (males = 804, females = 506) Lodox Statscan-generated radiographic images housed at the Forensic Pathology Service, Salt River and the Red Cross War Memorial Children’s Hospital in Cape Town, South Africa. Measurement definitions were derived from and/or follow studies in fetal and subadult osteology and longitudinal growth studies. Radiographic images were generated between 2007 and 2012, thus the majority of children (70%) were born after 2000 and thus reflect the modern population. Because basis splines and multivariate adaptive regression splines (MARS) are nonparametric the 95% prediction intervals associated with each age at death model were calculated with cross-validation. Numerous classification methods were employed namely linear, quadratic, and flexible discriminant analysis, logistic regression, naïve Bayes, and random forests to identify the method that consistently yielded the lowest error rates. Because some of the multivariate subsets demonstrated small sample sizes, the classification accuracies were bootstrapped to validate results. Both univariate and multivariate models were employed in the age and sex estimation analyses. Standard errors for the age estimation models were smaller in most of the multivariate models with the exception of the univariate humerus, femur, and tibia diaphyseal lengths. Univariate models provide narrower age estimates at the younger ages but the multivariate models provide narrower age estimates at the older ages. Diaphyseal lengths did not demonstrate any significant sex differences at any age, but diaphyseal breadths demonstrated significant sex differences throughout the majority of the ages. Classification methods utilizing multivariate subsets achieved the highest accuracies, which offer practical applicability in forensic anthropology (81% to 90%). Whereas logistic regression yielded the highest classification accuracies for univariate models, FDA yielded the highest classification accuracies for multivariate models. This study is the first to successfully estimate subadult age and sex using an extensive number of measurements, univariate and multivariate models, and robust statistical analyses. The success of the current study is directly related to the large, modern sample size, which ultimately captured a wider range of human variation than previously collected for subadult diaphyseal dimensions. / Thesis (PhD)--University of Pretoria, 2013. / gm2014 / Anatomy / unrestricted