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Exploring Mutual and Exclusive Biological Information in Cranial Metric and Morphological Variables
No full textEvidence 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 affinit
Using Multivariate Analysis within the Vertebral Column to Identify Individual Vertebrae
No full textThis 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
We Think There’s Been a Glitch: Artificial Intelligence and Machine Learning in Forensic Anthropology
No full textForensic 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 promisesenhanced 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
Constructing Chronicity and Clouding Kairos: The Fragmentation of Temporal Dialectics in Descriptions of Chronic Depression
No full textExtending Sarah Singer and Jordynn Jack’s (2020) definition of illness chronicity as a complex rhetorical process of identification, this essay suggests that the development of specific temporal vocabularies (ways of defining and describing time) is an important part of this process, one that precedes and enables identification. Drawing from underemphasized temporal themes in Kenneth Burke’s work, this essay analyzes a collection of public descriptions of chronic depression to identify implicit patterns of temporal vocabulary development and to consider how these patterns relate to identification. The analysis shows that descriptions of chronic depression consistently utilize what Burke termed “directional” strategies of definition, which center permanence as the essence of the illness experience, obscuring recognition of change. While this definitional strategy enables two potentially ameliorative disidentifications, it comes at the expense of precluding kairos, which requires a dialectically-intact temporal vocabulary featuring terms of both permanence and change.
The Corporate Rhetoric of Care and Nurse Identity in Times of COVID-19: A Study of a Johnson & Johnson Nursing Video Through the Lens of Althusserian Theory
No full textThis article draws on Louis Althusser’s theory of interpellation to examine the ideology behind the language and images of a web-based video Johnson & Johnson created in 2020. The video promoted the company’s annual “Nurses Innovate QuickFire Challenge”—a grant competition for nurses’ innovations. In our analysis, we found that the video created four main discourses of care: nurses as innovators, technologies as care, nurses as heroic, ministering angels, and Johnson & Johnson as an empowerer of nurses. Building on the positive, but contested, identity of nurses as heroes during the pandemic, Johnson & Johnson’s video connected heroism with technological innovation, enacting a problematic vision of care and nursing identity that figures technological innovation as not only a responsibility but a moral obligation of nurses. Through their sponsorship of research and design work with these nurse heroes and innovators, Johnson & Johnson also bolstered its own corporate identity as a caring supporter and empowerer of nurses
Introduction to Queer and Trans Health Justice: A Special Issue of RHM
Get PDFIntroduction to Queer and Trans Health Justice: A Special Issue of RHM 
Food Tax Substitution Effects
No full textDiet-related illness in the U.S. has risen to crisis levels, with today’s parents projected—for the first time—to enjoy longer lives than their children. Policymakers have responded with a range of novel proposals, many revolving around the assumption that increasing the relative price of unhealthful foods via taxes on soda, fat, sugar or caloric density will encourage more healthful eating. Yet there is little evidence that diet-targeted price interventions have had a meaningful impact on health outcomes. The reason for this, I argue, is both expected and largely overlooked in the academic and policy literatures: consumers have been motivated by price interventions to eat differently, but differently isn’t necessarily better. Price interventions created and crafted solely on the basis of the nutritional value of the targeted dietary item(s) are vulnerable to health-neutral substitution effects, wherein a price intervention motivates consumers to substitute items of similar dietary value—candy or beer for soda, for example—leading to little net change in overall dietary quality.
This Article proposes a novel food tax strategy, one that focuses on substitution effects. Instead of targeting foods with the least or most nutritional value, legislators and other policymakers should direct taxes to foods with the least or most relatively healthful substitutes.
As proof of concept, this Article introduces a specific substitution-based food tax proposal, supported with empirical results from an original randomized controlled trial: food taxes should seek to motivate substitution between grocery food and the relatively less healthful option of restaurant food. The health impact of such a shift will likely exceed that of a direct tax on soda, fat, sugar or calories given the high cross-elasticity of demand for restaurant food and its significant health inferiority. And because this shift may be accomplished by subsidizing groceries, by lowering taxes on groceries or by increasing taxes on restaurants, it presents a more politically flexible intervention than traditional consumer-side food taxes. 
The Paradox of Taxing the Rich
No full textAmerica does not tax its richest citizens, such as Elon Musk or Jeff Bezos, at all. This Article argues that part of the reason is the paradox that under current income tax law and theory, taxing the rich would cost resources that could be made available to benefit the not-rich. The Article explores the paradox in theory and practice, then points to ways to move beyond it. Taxing the rich will mean accepting compelling justifications for doing so other than providing resources to the not-rich. We must either pay the price or reset the terms of the debate to move society forward by breaking up large concentrations of private wealth
Book Review: The Evolving Tax State: A Review Essay
No full textReview of: Tax and Government in the Twenty-First Century, Miranda Stewart, Cambridge University Press, 2022, pp. 407
Guaranteed Wealth? A New Way of Thinking About the Gift Tax Treatment of Loan Guarantees
No full textWealthy parents have found an ingenious way to magnify their children’s assets without paying gift tax. Rather than transfer assets to the children directly, a parent may encourage her children (or trusts for the children’s benefit) to borrow funds as needed to make investments. The parent stands behind that debt by making a personal guarantee, assuring the lender of repayment and thereby allowing the children to borrow and invest far more than they otherwise could. The Internal Revenue Service clearly believes that such guarantees should be treated as gifts but has hesitated to press that position or develop a framework for doing so. This Article provides that framework, drawing on analogous corporate tax cases to show the way.
For gift tax purposes, when a person guarantees a loan to a related party, the loan would be recharacterized as a loan from the lender to the guarantor, followed by a second loan on the same terms from the guarantor to the ultimate borrower. Each loan would then be tested under existing doctrines to see whether it should be respected as debt. In most cases, the second deemed loan (from the guarantor to the ultimate borrower) would not be respected as debt, because the ultimate borrower lacks the income or resources to justify the extension of credit. As a result, the second deemed loan would be recharacterized as a gift to the ultimate borrower rather than a loan. This framework would severely curtail the use of guarantees to grow dynastic wealth.