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4,528 result(s) for "biology of race"
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Reproducing race
Reproducing Race, an ethnography of pregnancy and birth at a large New York City public hospital, explores the role of race in the medical setting. Khiara M. Bridges investigates how race--commonly seen as biological in the medical world--is socially constructed among women dependent on the public healthcare system for prenatal care and childbirth. Bridges argues that race carries powerful material consequences for these women even when it is not explicitly named, showing how they are marginalized by the practices and assumptions of the clinic staff. Deftly weaving ethnographic evidence into broader discussions of Medicaid and racial disparities in infant and maternal mortality, Bridges shines new light on the politics of healthcare for the poor, demonstrating how the \"medicalization\" of social problems reproduces racial stereotypes and governs the bodies of poor women of color.
Has social constructionism about race outlived its usefulness? Perspectives from a race skeptic
The phrase ‘social constructionism about race’ is so ambiguous that it is unable to convey anything very meaningful. I argue that the various versions of social constructionism about race are either false, overly broad, or better described as anti-realism about biological race. One of the central rhetorical purposes of social constructionism about race has been to serve as an alternative to biological racial realism. However, most versions of social constructionism about race are compatible with biological racial realism, and there are some race scholars who endorse both positions. Going a step further, David Reich has recently defended both social constructionism about race and racial hereditarianism. While Reich’s defense of racial hereditarianism is unconvincing, I show that most versions of social constructionism about race are indeed compatible with racial hereditarianism. I argue that we ought to replace the social constructionist “consensus” about race with the view that there are no races, only racialized groups.
Putting races on the ontological map: a close look at Spencer’s ‘new biologism’ of race
In a large and impressive body of published work, Quayshawn Spencer has meticulously articulated and defended a metaphysical project aimed at resuscitating a biological conception of race—one free from many of the pitfalls of biological essentialism. If successful, such a project would be highly rewarding, since it would provide a compelling response to philosophers who have denied the genuine existence of race while avoiding the very dangers that they sought to avoid. The aim of this paper is to subject those moves to careful scrutiny and thereby appraise the prospects for a new biologism about race.
How Real Is Race? Using Anthropology to Make Sense of Human Diversity
Drawing on work of contemporary biological anthropologists and other scientists, argues that biologically based racial differences are not scientifically valid, but are instead socially constructed categories. Draws implications for teachers, students, and society. Provides suggestions and resources for teachers and students to learn more about human biological variation. (Contains 24 references.) (PKP)
Yellow Bodies, Black Sweat
This chapter focuses on the relationship between Asian and Black athletes, global multiculturalism, and capitalism. Ichiro Suzuki and Yao Ming represent in clear ways the figuration of the Asian male body as both cultural phenomena and transnational commodity. This chapter describes the marked turn from the Asian male body as an unattractive representative for marketing commodity exchanges to an imported spectacle reproducing multicultural capitalism in global sport. However, it does not simply offer a conventional study of the political economy involved in the global expansion of popular sports. Rather, it attempts to illustrate how Asian men in U.S. sports presuppose and indeed attempt to produce Asian masculinity through inverting the bodily emasculation of Asian American men. This chapter details the ways in which popular sports have been racialized as a “Black” space of colonial fantasy and fears and how Asian male athletes break down the fixity of biological discourses that hinge upon visual common sense.
History of Biological Anthropology
This chapter contains sections titled: The Eighteenth and Nineteenth‐Century Origins of Physical Anthropology Twentieth Century Beginnings and the Rise of Professionalism The Science Matures: Post‐World War II New Journals and Professional Societies Into the Twenty‐First Century: Contemporary Trends and Approaches Archival and Published Sources Conclusions References
The world the game theorists made
In recent decades game theory—the mathematics of rational decision-making by interacting individuals—has assumed a central place in our understanding of capitalist markets, the evolution of social behavior in animals, and even the ethics of altruism and fairness in human beings. With game theory's ubiquity, however, has come a great deal of misunderstanding. Critics of the contemporary social sciences view it as part of an unwelcome trend toward the marginalization of historicist and interpretive styles of inquiry, and many accuse its proponents of presenting a thin and empirically dubious view of human choice. The World the Game Theorists Made seeks to explain the ascendency of game theory, focusing on the poorly understood period between the publication of John von Neumann and Oscar Morgenstern's seminal Theory of Games and Economic Behavior in 1944 and the theory's revival in economics in the 1980s. Drawing on a diverse collection of institutional archives, personal correspondence and papers, and interviews, Paul Erickson shows how game theory offered social scientists, biologists, military strategists, and others a common, flexible language that could facilitate wide-ranging thought and debate on some of the most critical issues of the day.
The avocado genome informs deep angiosperm phylogeny, highlights introgressive hybridization, and reveals pathogen-influenced gene space adaptation
The avocado, Persea americana, is a fruit crop of immense importance to Mexican agriculture with an increasing demand worldwide. Avocado lies in the anciently diverged magnoliid clade of angiosperms, which has a controversial phylogenetic position relative to eudicots and monocots. We sequenced the nuclear genomes of the Mexican avocado race, P. americana var. drymifolia, and the most commercially popular hybrid cultivar, Hass, and anchored the latter to chromosomes using a genetic map. Resequencing of Guatemalan and West Indian varieties revealed that ∼39% of the Hass genome represents Guatemalan source regions introgressed into a Mexican race background. Some introgressed blocks are extremely large, consistent with the recent origin of the cultivar. The avocado lineage experienced 2 lineage-specific polyploidy events during its evolutionary history. Although gene-tree/species-tree phylogenomic results are inconclusive, syntenic ortholog distances to other species place avocado as sister to the enormous monocot and eudicot lineages combined. Duplicate genes descending from polyploidy augmented the transcription factor diversity of avocado, while tandem duplicates enhanced the secondary metabolism of the species. Phenylpropanoid biosynthesis, known to be elicited by Colletotrichum (anthracnose) pathogen infection in avocado, is one enriched function among tandems. Furthermore, transcriptome data show that tandem duplicates are significantly up- and down-regulated in response to anthracnose infection, whereas polyploid duplicates are not, supporting the general view that collections of tandem duplicates contribute evolutionarily recent “tuning knobs” in the genome adaptive landscapes of given species.
Race, color, identity
Advances in genetics are renewing controversies over inherited characteristics, and the discourse around science and technological innovations has taken on racial overtones, such as attributing inherited physiological traits to certain ethnic groups or using DNA testing to determine biological links with ethnic ancestry. This book contributes to the discussion by opening up previously locked concepts of the relation between the terms color, race, and \"Jews\", and by engaging with globalism, multiculturalism, hybridity, and diaspora. The contributors-leading scholars in anthropology, sociology, history, literature, and cultural studies-discuss how it is not merely a question of whether Jews are acknowledged to be interracial, but how to address academic and social discourses that continue to place Jews and others in a race/color category.
An algorithmic approach to reducing unexplained pain disparities in underserved populations
Underserved populations experience higher levels of pain. These disparities persist even after controlling for the objective severity of diseases like osteoarthritis, as graded by human physicians using medical images, raising the possibility that underserved patients’ pain stems from factors external to the knee, such as stress. Here we use a deep learning approach to measure the severity of osteoarthritis, by using knee X-rays to predict patients’ experienced pain. We show that this approach dramatically reduces unexplained racial disparities in pain. Relative to standard measures of severity graded by radiologists, which accounted for only 9% (95% confidence interval (CI), 3–16%) of racial disparities in pain, algorithmic predictions accounted for 43% of disparities, or 4.7× more (95% CI, 3.2–11.8×), with similar results for lower-income and less-educated patients. This suggests that much of underserved patients’ pain stems from factors within the knee not reflected in standard radiographic measures of severity. We show that the algorithm’s ability to reduce unexplained disparities is rooted in the racial and socioeconomic diversity of the training set. Because algorithmic severity measures better capture underserved patients’ pain, and severity measures influence treatment decisions, algorithmic predictions could potentially redress disparities in access to treatments like arthroplasty. An algorithmic, machine-learning approach to measuring severe pain from osteoarthritis applied to X-ray images of knees suggests that reported disparities in knee pain in underserved populations can be reduced by comparison with use of standard radiographic measures of disease severity.