American anthropology has focused on issues related to race from the start of the discipline. From past work designed to categorize humans into phenotype-based categories to current work to undo those categorizations, many anthropologists consider race to be one of the most important topics for students to learn. In this dissertation, I use in-depth ethnographic case studies consisting of interviews, observations, and focus groups, to learn about the way in which anthropologists at four institutions of higher education teach the topic to students in their introductory, four-field general anthropology class. I found that anthropologists are committed to sharing anthropological perspectives with the public through teaching, while their students look for engaging and interesting teaching. I discuss the general acceptance by instructors of introductory courses of the idea that race does not have a biological basis in humans but is in fact a social construction; that in general, professors find this topic to be a critical one for students to learn; that there are a variety of successful strategies that can be employed to teach race to students; and that while students grasp the basic message, they remain confused about the social context of race and racism. Additionally, I conducted interviews with experts on the topic of race to provide context for the current anthropological perspective. I conclude that there is more research to be done on the teaching of anthropology, that the anthropological message about race must be stated in a more nuanced way, that the four-field introductory course is valuable and should be preserved, and that anthropology needs to further incorporate racism (the systematic mistreatment of minorities that is built into the social structure of the United States) into the discussion on race. Future research directions include scaling the research up to observe teaching practices across the country, conducting survey research to understand teaching practices and attitudes, further exploring the generalizability of these findings, and testing the effectiveness of teaching methods described herein using pre- and post- tests. Two potential study limitations include the majority White sample and that the study was confined to the American South.

Ecogeographic patterns of modern human craniofacial diversity suggest external nasal structures reflect climatic adaptations for respiratory and thermoregulatory functions. Regarding internal structures, the maxillary sinus supposedly varies as a function of the nasal cavity while not contributing in respiratory function. Owing to conflicting results, this study reinvestigates that claim by evaluating maxillary sinus variation in a larger sample (n=200) spanning 11 ecogeographic regions. The surface-area-to-volume (SA:V) ratio (i.e., relative mucosal area) was collected in addition to sinus volume and linear dimensions. Pearson correlations show nasal cavity breadth and maxillary sinus volume are not significantly correlated, and individuals from cold, versus hot, climates exhibit larger volumes with lower surface-area-to-volume (SA:V) ratios. Individuals from high altitudes display a unique configuration with high SA:V ratios and large maxillary sinus volumes. Analyses of variance largely fail to find significant differences among the 11 samples. However, a canonical variate analysis of nasal and sinus dimensions indicates clear separations between the heat- and cold-adapted populations, as well as among the cold-adapted populations. Specifically, Arctic populations display smaller sinus volumes and lower SA:V ratios. Mantel tests indicate certain sinus dimensions depart from isolation-by-distance models. Results indicate that maxillary sinus form does not simply follow isolation-by-distance models and cannot simply be explained in terms of nasal cavity breadth or craniofacial architecture— suggesting that environmental pressures are directly acting on the sinus. Functional possibilities for the sinus include thermoregulatory functions among Arctic populations and/or nitric oxide production for high-altitude populations. Additional considerations and future lines of research are presented.

The primary role of a physical anthropologist is to provide sufficient information to assist in the individualisation of unknown skeletal remains. This is often achieved in establishing a biological profile of the deceased, of which ancestry is an essential aspect. Several successful osteometric and morphological approaches have been developed to facilitate the estimation of ancestry from the cranium. However, the cranium is not always available for analysis, emphasising a need for postcranial alternatives. The postcranial skeleton is frequently labelled as too variable and unreliable to provide an accurate assessment of ancestry. Yet, numerous studies utilise the postcrania for sex and stature estimation, where the a priori knowledge of ancestry results in higher accuracy. Thus, the presence of postcranial differences among populations when investigating other biological parameters inherently demonstrates the potential for the estimation of ancestry. The purpose of this study was to quantify postcranial variation among modern, peer-reported black, white and coloured South Africans. A series of 39 standard measurements were taken from 11 postcranial bones, namely the clavicle, scapula, humerus, radius, ulna, sacrum, pelvis, femur, tibia, fibula and calcaneus. The sample consisted of 360 modern South African individuals (120 black, 120 white, 120 coloured) from the Pretoria Bone and Kirsten Collections housed at the University of Pretoria and the University of Stellenbosch, respectively. Group differences were explored with ANOVA and Tukey’s honestly significant difference test (HSD). Group means were used to create univariate sectioning points for each variable indicated as significant with ANOVA. Where two of the three groups had similar mean values, the groups were pooled for the creation of the sectioning points. Multivariate classification models were employed using linear and flexible discriminant analysis (LDA and FDA, respectively). Classification accuracies were compared to evaluate which model yielded the best results. The results demonstrated variable patterns of group overlap. Black and coloured South Africans displayed similar means for breadth measurements, and black and white South Africans showed similar means for the maximum length of distal limb elements. The majority of group variation is attributed to differences in size and robusticity, where white South Africans are overall larger and more robust than black and coloured South Africans. Accuracies for the univariate sectioning points ranged from 43% to 87%, with iliac breadth performing the best. However, the majority of the univariate sectioning points can only classify individuals into two groups rather than three because of similar group means. Multivariate bone models created using all measurements per bone resulted in accuracies ranging from 46% to 62% (LDA) and 41% to 66% (FDA). Multivariate subsets consisting of numerous different measurement combinations from several skeletal elements achieved accuracies as high as 85% (LDA) and 87% (FDA). Ultimately the best results were achieved using combinations of different variables from several skeletal elements. Overall, the multivariate models yielded better results than the univariate approach, as the inclusion of more variables is generally better for maximising group differences. Furthermore, FDA achieved higher accuracies than the more traditional approach of LDA. Despite the significant overlap among the groups, the postcranial skeleton has proven to be proficient in distinguishing the three groups. Thus, even in a heterogeneous population, a multivariate postcraniometric approach can be used to estimate ancestry with high accuracy. / Dissertation (MSc)--University of Pretoria, 2015. / Anatomy / Unrestricted

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Este documento apresenta um estudo em nível de mestrado na área de Geração de Língua Natural (GLN), enfocando a questão da variação humana na tarefa de Geração de Expressões de Referência (GER). O trabalho apresenta um levantamento bibliográfico sobre o tema, a criação de dois algoritmos de GER e a construção de um novo córpus de expressões de referência. Modelos computacionais de GER baseados nos algoritmos criados foram implementados em versões que incorporam e não incorporam a variação humana e empregados em uma série de experimentos de GER em sete córpus de expressões de referência. Resultados comprovam a hipótese inicial de que algoritmos de GER que levam em conta a variação humana podem gerar expressões de referência mais próximas a descrições de seres humanos do que algoritmos que não levam esta questão em conta. Além disso, confirmou-se que algoritmos de GER baseados em técnicas de aprendizado de máquina mostram-se superiores a algoritmos de GER consagrados e amplamente utilizados na literatura, como o algoritmo Incremental. / This work concerns a MSc Project in the field of Natural Language Generation (NLG), focusing on the issue of human variation in the Referring Expression Generation task (REG). The study presents a literature review on the topic, the proposal of two REG algorithms and the construction of a new corpus of referring expressions. Based on these algorithms, two REG models are implemented: with and without taking human variation. These models are employed in a series of REG experiments using seven referring expression corpora. Results confirm the initial hypothesis that REG algorithms that take speaker variation into account outperform existing algorithms that generate speaker-independent descriptions. Moreover, the present study confirms that algorithms based on machine learning techniques overperform existing algorithms, as the Dale and Reiter\'s Incremental algorithm.

Este documento apresenta um estudo em nível de mestrado na área de Geração de Língua Natural (GLN), enfocando a questão da variação humana na tarefa de Geração de Expressões de Referência (GER). O trabalho apresenta um levantamento bibliográfico sobre o tema, a criação de dois algoritmos de GER e a construção de um novo córpus de expressões de referência. Modelos computacionais de GER baseados nos algoritmos criados foram implementados em versões que incorporam e não incorporam a variação humana e empregados em uma série de experimentos de GER em sete córpus de expressões de referência. Resultados comprovam a hipótese inicial de que algoritmos de GER que levam em conta a variação humana podem gerar expressões de referência mais próximas a descrições de seres humanos do que algoritmos que não levam esta questão em conta. Além disso, confirmou-se que algoritmos de GER baseados em técnicas de aprendizado de máquina mostram-se superiores a algoritmos de GER consagrados e amplamente utilizados na literatura, como o algoritmo Incremental. / This work concerns a MSc Project in the field of Natural Language Generation (NLG), focusing on the issue of human variation in the Referring Expression Generation task (REG). The study presents a literature review on the topic, the proposal of two REG algorithms and the construction of a new corpus of referring expressions. Based on these algorithms, two REG models are implemented: with and without taking human variation. These models are employed in a series of REG experiments using seven referring expression corpora. Results confirm the initial hypothesis that REG algorithms that take speaker variation into account outperform existing algorithms that generate speaker-independent descriptions. Moreover, the present study confirms that algorithms based on machine learning techniques overperform existing algorithms, as the Dale and Reiter\'s Incremental algorithm.

<p>The completion of the Human Genome Project, a remarkable feat by any measure, has provided over three billion bases of reference nucleotides for comparative studies. The next, and perhaps more challenging step is to analyse sequence variation and relate this information to important phenotypes. Most human sequence variations are characterized by structural complexity and, are hence, associated with abnormal functional dynamics. This thesis covers the assembly of a computational platform for verifying these variations, based on accurate, published, experimental data.</p>

Due to the strong genetic component of dental development, research has shown that mineralization patterns of the human dentition are relatively buffered against environmental influences that normally affect bone growth and development. It is because of this resistance to environmental factors and the continuous growth of the permanent dentition throughout childhood and adolescence that the evaluation of dental development patterns has become the preferred method of age estimation in living and deceased children. Researchers (Harris and Mckee 1990; Tompkins 1996; Blankenship et al. 2007; Kasper et al. 2009) have suggested that the timing of dental development varies by ancestral descent and geographic populations. However, further evaluations of these perceived differences in the timing of dental development among populations are necessary as classical statistical methods result in age estimations that are biased toward the age structure of the reference population. However, the Bayesian approach is beneficial since it incorporates relevant prior knowledge into the analysis and formalizes the relationship between assumptions and conclusions (Buck et al. 1996). Therefore, the purpose of this research is to incorporate methods in Bayesian analysis to compare the timing of dental development between two contemporary populations of the Southeastern United States, as well as test the accuracy of dental development age parameters devised by Moorrees et al. (1963) on a contemporary Florida Population. For this study, 51 panoramic radiographs of individuals from a contemporary Florida population ranging in age from 7.7-20.4 years were reviewed. Statistical analyses incorporated a Bayesian approach to compare the timing of dental development for individuals comprising the contemporary Florida sample with the timing of dental development for a contemporary Middle Tennessee population by utilizing the age structure of the Middle Tennessee population as informed prior knowledge, otherwise referred to as an informed prior. Transition distributions for age, given stage of dental development, were also modeled for individuals comprising the contemporary Florida sample. The accurate observation and comparison of probability density distributions for age can serve as a noninvasive method for evaluating the probability of whether or not an unknown individual is a particular age, given the stage of dental development. Results of this research indicate that there is a consistent underestimation of age for individuals comprising the contemporary Florida population when the age structure of the Middle Tennessee population is utilized as an informed prior. Additionally, the results of this thesis indicate that there is a consistent underestimation of age when utilizing age parameters of Moorrees et al. (1963) for the estimation of age for individuals from a contemporary Florida population. By incorporating a Bayesian approach to compare two contemporary populations of the Southeastern United States, a comprehensive analysis of the relationship between age and stage of dental development can be achieved. Therefore, the results of this thesis support Bayesian analysis as an appropriate method of evaluating perceived differences in the timing of dental development between contemporary populations. Furthermore, the results of this research are beneficial to the field of forensic anthropology as the observation of advanced stages of molar development utilizing panoramic radiographs serves as a noninvasive method in estimating age for unknown juveniles and young adults, and can also assist courts within the United States in determining whether or not an individual is legally considered a minor or an adult.

The analysis of craniometric data collected from skeletal remains, combined with archaeological data, can provide very valuable information pertaining to biological distance and gene flow among prehistoric populations through space and time. The goal of this study was to examine microevolutionary change among prehistoric populations in south Florida based on the degree of cranial variation among populations at seven prehistoric sites. It was expected that as time progressed, microevolutionary forces caused significant changes in the crania of the various populations based on the relative geographic proximity of the sites and the temporal distance between sites. A Microscribe 3-DX digitizer was used to collect coordinate data using the full protocol of cranial landmarks. Twenty-three interlandmark distances for n=223 skulls from seven sites, ranging in age from 8120 B.P. to 260 B.P., were analyzed using Cluster Analysis, an Analysis of Variance (ANOVA), a Tukey’s Pairwise Comparison (post-hoc test), a Multiple Analysis of Variance (MANOVA), and Principal Components Analysis (PCA) in SPSS 18.0. The seven sites were Windover (8Br246), Perico Island (8Ma6), Captiva Island (8Ll57), Belle Glade (8Pb40), Horr’s Island (8Cr41), Safety Harbor (8Pi2), and Fuller Mound A (8Br90). Of the 223 crania used, zero (0) skulls were 100% complete. Results of univariate and multivariate statistical analyses indicate that there are significant differences among the seven groups. The agglomerative cluster analysis did not provide significant results. When using Maximum Cranial Length (GOL), the ANOVA (F=5.190, p ≤ 0.000) and post-hoc tests indicated that there was a significant amount of variation among the seven populations. In a series of 12 MANOVA tests, it was determined that significant variation existed between Windover and each of the remaining six sites (F > 5, p ≤ 0.000). Additionally, the MANOVA tests indicated that significant variation existed between Horr’s Island and Safety Harbor (F = 8.151, p ≤ 0.000) and between Safety Harbor and Fuller Mound A (F = 5.549, p ≤ 0.000). Last, a Principal Components Analysis demonstrated that measurements consistent with length or breadth accounted for the largest percentage of variation among the populations. In conclusion, the data strongly demonstrate a significant amount of variation among prehistoric populations as time progressed from 8120 B.P. to 260 B.P. Specifically, changes in gene flow which can be attributed to significant differences among populations based on craniometric data parallel major time gaps and historical events in Florida. More generally, these results can be applied to other past populations to investigate similar patterns of gene flow and changes that may have occurred due to various social, political, and environmental stressors.

<p>The completion of the Human Genome Project, a remarkable feat by any measure, has provided over three billion bases of reference nucleotides for comparative studies. The next, and perhaps more challenging step is to analyse sequence variation and relate this information to important phenotypes. Most human sequence variations are characterized by structural complexity and, are hence, associated with abnormal functional dynamics. This thesis covers the assembly of a computational platform for verifying these variations, based on accurate, published, experimental data.</p>