Racial disparities in health outcomes have recently become a flashpoint in the debate about the value of race as a biological concept. What role, if any, race has in the etiology of disease is a philosophically and scientifically contested topic. In this article, I expand on the insights of the new mechanistic philosophy of science to defend a mechanism discovery approach to investigating epidemiological racial disparities. The mechanism discovery approach has explanatory virtues lacking in the populational approach typically employed in the study of race and biomedicine. The explanatory constraints that form an integral part of the new mechanistic approach enable mechanism discovery to avoid the epistemic and normative shortcomings of the populational approach. The methodology of mechanism discovery can fruitfully be extended to the treatment and reversal of epidemiological racial disparities. Keywords Mechanism. Race. Epigenetics. Explanation. Disease. Epidemiology States, and therefore "race-based studies" are an essential component of research into these disparities (Lorusso and Bacchini 2015).Nevertheless, both advocates and critics of the race-based studies take for granted their principal mode of reasoning and investigation, namely statistical reasoning and the tools of population genetics. Whether it is in biomedical research or social science, it is statistical reasoning, the kind employed in population genetics, that is used to build evidence for hypotheses relating to racial disparities. It is "statistical evidence of associations between variables" that is prized by the statistical reasoning approach (Matthews 2017, 1006). This paper argues that the populational/genetics approach, which remains the preeminent approach to investigating epidemiological racial disparities 1 (ERDs), has a number of epistemic and normative shortcomings. I outline the three main varieties of explanations of ERDs, which I call the racism-based explanations, genetics-based explanations, and embodiment-based explanations, and illustrate each with an example case. I argue that the dominant approach of race-based studies into ERDs, which often fall under genetics-based explanations, violate two explanatory constraints highlighted by what I call the granularity and reification problems. As I show, the granularity and reification problems pose an explanatory challenge to the prominent methodology of race-based studies of epidemiological racial disparities. This challenge stems from an inherent limitation of the populational/genetics approach in determining which variety of explanation, and subsequently what type of mechanism, is adequate.1 By epidemiological racial disparities I mean statistically significant differences in the incidence of disease between racialized groups. Except when discussing the views of others, I use "race" and "racialized group" interchangeably. However, see Hochman (2019) for the argument that since racialization theory is not committed to a racial ontology, "racialized groups" are conceptually distinct f...
Lockdowns were a morally and medically appropriate anti-contagion policy to stop the spread of Covid. However, lockdowns came with considerable costs. Specifically, lockdowns imposed harms and losses upon the young in order to benefit the elderly, who were at the highest risk of severe illness and death from Covid. This represented a shifting of the (epidemiological) burden of Covid for the elderly to a systemic burden of lockdown upon the young. This article argues that even if lockdowns were a morally permissible response to Covid, the harms and losses they imposed on the young ground a claim of compensation. I defend an intergenerational compensation argument that defends a claim for an egalitarian intergenerational transfer to compensate the young for the harms of lockdown.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.