"Within the sciences, there are increasing calls for incorporating intersectionality as a theoretical framework in the development of research questions and in methodological approaches. When we consider our recent research experiences, the primary question that arises is not whether quantitative fields can effectively incorporate intersectionality methodologically. Rather, it is whether these disciplines are prepared to expand their definitions of ways of knowing so as to create space for intersectional analysis in the STEM fields."
Forthcoming in the Routledge Companion to Intersectinality, edited by Jennifer Nash and Samantha Pinto.  Contact srichard@fas.harvard.edu for advance manuscript.

The interplay between legal and bioscientific understandings of sex is prolific and complex. Biological evidence and reasoning circulate in lawmaking and policy-making across an array of politically contested issues, including health care, education, and LGBTQI+ rights and protections. There is often a substantial disjoint, however, between how scientists define and operationalize sex differences in their research and how lawmakers and policy-makers make sense of these definitions and concepts as they strategically seek to bolster or challenge legal governance. Medical and life scientists who routinely incorporate sex-related variables in their research cannot eliminate superficial or malicious misuse of research by lawmakers and policy-makers, but awareness of the legal and policy landscape can clarify the possible downstream consequences of researchers’ choices about how to operationalize sex-related variables in their studies.

Policies that require male-female sex comparisons in all areas of biomedical research conflict with the goal of improving health outcomes through context-sensitive individualization of medical care. Sex, like race, requires a rigorous, contextual approach in precision medicine. A “sex contextualist” approach to gender-inclusive medicine better aligns with this aim.

This article shows that in NY the magnitude of sex disparities in COVID-19 mortality was not stable across time. While the initial surge in COVID-19 mortality was characterized by stark sex disparities, these were greatly attenuated after the introduction of public health controls. As of August 28, 2021, 19 227 (44.2%) women and 24 295 (55.8%) men died from COVID-19 in NY. 72.7% of the cumulative difference in the number of COVID-19 deaths between women and men was accrued between March 14 and May 4, 2020. During this period, the COVID-19 mortality rate ratio for men compared to women was 1.56 (95% CI: 1.52-1.61). In subsequent time periods, the corresponding ratio ranged between 1.08 (0.98-1.18) and 1.24 (1.15-1.34). While the cumulative mortality rate ratio of men compared to women was 1.34 (1.31-1.37), the ratio equals 1.19 (1.16-1.22) if deaths during the initial COVID-19 surge are excluded from the analysis.

This paper presents the first longitudinal study of sex disparities in COVID-19 cases and mortalities across U.S. states, derived from the unique 13-month dataset of the U.S. Gender/Sex COVID-19 Data Tracker. To analyze sex disparities, weekly case and mortality rates by sex and mortality rate ratios and rate differences were computed for each U.S. state, and a multilevel crossed-effects conditional logistic binomial regression model was fitted to estimate the variation of the sex disparity in mortality over time and across states. Results demonstrate considerable variation in the sex disparity in COVID-19 cases and mortalities over time and between states. These data suggest that the sex disparity, when present, is modest, and likely varies in relation to context-sensitive variables, which may include health behaviors, preexisting health status, occupation, race/ethnicity, and other markers of social experience.

This paper develops the conceptual framework of “sex contextualism” for the study of sex-related variables in biomedical research. Sex contextualism offers an alternative to binary sex essentialist approaches to the study of sex as a biological variable. Specifically, sex contextualism recognizes the pluralism and context-specificity of operationalizations of ‘sex’ across experimental laboratory research. In light of recent policy mandates to consider sex as a biological variable, sex contextualism offers constructive guidance to biomedical researchers for attending to sex-related biological variation. As an alternative to and critique of biological binary sex essentialism, sex contextualism contributes to current debates in philosophy of biology, feminist science studies, and social ontology on the construction of categories of gender/sex differences in scientific research.

Gender/sex comparisons of COVID-19 case fatality rates are subject to systematic bias owing to differential testing rates. Nonrandom COVID-19 testing in the population means that there is considerable uncertainty around CFR estimates in men and women. Specifically, widespread lower testing among men compared with women likely artificially inflates the CFR among men, as demonstrated by a predictive, inverse relationship between testing skew and CFR ratio. The more disparate testing becomes between men and women, the greater the observed sex disparity in CFR; when testing becomes more similar, observed CFRs become more similar. The case study of COVID-19 offers an important teachable and generalizable example for women's health scholars of the caution that is needed in interpreting sex disparities in CFRs.

A collaboration between scholars in history and social studies of science and leading DOHaD scientists, this article argues that in a world of extreme inequalities, we need a science of DOHaD that attends to how factors that influence the development of health and disease are socially patterned, shifting the focus from individual-level characteristics of the mother–child dyad in early development (independent of fathers, partners and other caregivers), to complex social processes that stratify society over the life-course.  

We explain and contextualize our new study out in Human Fertility in this essay for Slate.

The sex disparity in COVID-19 mortality varies widely and is of uncertain origin. In their recent Nature paper “Sex differences in immune responses that underlie COVID-19 disease outcomes,” Takahashi et al. assess immune phenotype in a sample of COVID-19 patients and conclude that the “immune landscape in COVID-19 patients is considerably different between the sexes,” warranting different vaccine and therapeutic regimes for men and women -- a claim widely disseminated following the publication. Here, we argue that these inferences are not supported by their findings: this study does not demonstrate that biological sex explains COVID-19 outcomes among patients. This study is diagnostic of an ongoing pattern in sex difference research of overstatement of findings and superficial treatment of factors beyond innate sex in analyzing the causes of gender/sex disparities in health outcomes.

The past 50 years have seen heated debate in the reproductive sciences about global trends in human sperm count. In 2017, Levine and colleagues published the most methodologically rigorous and largest meta-regression analysis to date and reported that average total sperm concentration among men from “Western” countries has decreased by 59.3% since 1973, with no sign of halting. These results reverberated in the scientific community and in public discussions about men and masculinity in the modern world, in part because of scientists’ public-facing claims about the societal implications of the decline of male fertility. We find that existing research follows a set of implicit and explicit assumptions about how to measure and interpret sperm counts, which collectively form what we term the Sperm Count Decline hypothesis (SCD). Using the study by Levine and colleagues, we identify weaknesses and inconsistencies in the SCD, and propose an alternative framework to guide research on sperm count trends, the Sperm Count Biovariability hypothesis (SCB). SCB asserts that sperm count varies within a wide range, much of which can be considered non-pathological and species-typical. Knowledge about the relationship between individual and population sperm count and life-historical and ecological factors is critical to interpreting trends in average sperm counts and their relationships to health and fertility.

This study shows that Black women are dying of COVID-19 at rates higher than men in other racial/ethnic groups. The study is the first to quantify the inequities in COVID-19 mortality looking at both race and sex group and analyzing the sex-disparity in COVID-19 mortality across racial groups. It shows that Black women are dying at significantly higher rates than white men, and that disparities in mortality rates among women of all races are greater than those between white women and white men, complicating the simple narrative that men are dying at greater rates of COVID-19 than women.

Results show that the common belief that men with COVID-19 fare more poorly than women varies in magnitude across social groups defined by race/ethnicity. Key findings of the study include:

• Black women have COVID-19 mortality rates that are almost 4 times higher than that of white men and 3 times higher than that of Asian men, as well as higher than white and Asian women.
• Black men have far higher mortality rates than any other sex and racial group, including over 6 times higher than the rate among white men.
• The disparity in mortality rates between Black women and white women is over 3 times the disparity between white men and white women.
• The disparity between Black men and Black women is larger than the disparity between white men and white women.

Study methods: This study used census data and publicly available data from Michigan and Georgia, the only two states reporting data disaggregated by age, race, and sex, to calculate and compare COVID-19 mortality rates.

Headlines like “Battle of the Sexes Against COVID-19” frame sex disparities in COVID-19 outcomes as a matter of essential biological differences between the sexes. Our findings support a contrary view, that biological factors at best play a small role. Rather, social factors influenced by structural gendered racism are key to the patterns of sex disparities revealed by the COVID-19 pandemic. These findings caution against public health messaging emphasizing a higher COVID-19 risk among men that does not also include social context.

The Maternal Imprint charts the history of the idea that a woman’s health and behavior during pregnancy can have long-term effects on her descendants’ health and welfare.

The idea that a woman may leave a biological trace on her gestating offspring has long been a commonplace folk intuition and a matter of scientific intrigue, but the form of that idea—and its staggering implications for maternal well-being and reproductive autonomy—has changed dramatically over time. Beginning with the advent of modern genetics at the turn of the twentieth century, biomedical scientists dismissed any notion that a mother—except in cases of extreme deprivation or injury—could alter her offspring’s traits. Consensus asserted that a child’s fate was set by a combination of its genes and post-birth upbringing.  

Over the last fifty years, however, this consensus was dismantled, and today, research on the intrauterine environment and its effects on the fetus is emerging as a robust program of study in medicine, public health, psychology, evolutionary biology, and genomics. Collectively, these sciences argue that a woman’s experiences, behaviors, and physiology can have life-altering effects on offspring development. Tracing a genealogy of ideas about heredity and maternal-fetal effects, The Maternal Imprint offers a critical analysis of conceptual and ethical issues provoked by the striking rise of epigenetics and fetal origins science in postgenomic biology today.

The Harvard GenderSci Lab developed a scoring scheme and Report Card to evaluate the comprehensiveness of socially relevant, intersectional data publicly reported by each state.  We scored each state on their reporting of selected socially relevant variables (age, sex/gender, race/ethnicity, and comorbidity status), and on reporting of interactions between these variables.  The results document the paucity of comprehensive disaggregated COVID-19 surveillance reporting among states. Only three states received an “A”, while 30 states received a “D” grade or lower.

Although gender parity has been reached at the graduate level in the geosciences, women remain a minority in faculty positions. First authorship of peer‐reviewed scholarship is a measure of academic success and is often used to project potential in the hiring process. Given the importance of first author publications for hiring and advancement, we sought to quantify whether women are underrepresented as first authors relative to their representation in the field of geoscience. We compiled first author names across 13 leading geoscience journals from January 2013 to April 2019 (n 1⁄4 35,183). Using a database of 216,286 names from 79 countries, across 89 languages, we classified the likely gender associated with each author's given (first) name. We also estimated the gender distribution of authors who publish using only initials, which may itself be a strategy employed by some women to preempt perceived (and actual) gender bias in the publication process. Female names represent 13–30% of all first authors in our database and are substantially underrepresented relative to the proportion of women in early career positions (30–50%). The proportion of female‐name first authors varies substantially by subfield, reflecting variation in representation of women across geoscience subdisciplines. In geoscience, the quantification of this first authorship gender gap supports the hypothesis that the publication process—namely, achievement or allocation of first authorship—is biased by social factors, which may modulate career success of women in the sciences.

The increasing influence of private equity in a range of health care delivery settings such as physician staffing, nursing homes, and hospitals is not new. But our research reveals a precipitous rise of private equity activity in women’s health. The recent rise of private equity in this area marks a novel form of investor attention with unknown implications. To determine how the incentives of private equity firms interact with clinicians’ mission of caring for women, policymakers, researchers, and the general public need to stay vigilant. Deals between private equity firms and health care providers should be transparent, and ethical standards should be put in place to ensure that profits don’t get in the way of people, and that patients are able to access comprehensive, equitable, and affordable care.

We document formerly non–private equity women’s health care companies, including physician networks, practices, and fertility clinics, that gained a private equity affiliation between 2010 and 2019. This analysis shows a substantial increase in private equity affiliations in women’s health care since 2017. Private equity–affiliated OB/GYN offices are located in urban locations, with an average 2017 median household income 24% higher than the 2017 national average. How the incentives of private equity firms interact with the clinical mission of women’s health is a critical area of inquiry. Future debate about private equity in women’s health will likely be shaped by the associations between economic incentives and quality of care, elective or cosmetic procedures, and access to reproductive health services, especially among low-income, LGBTQIA, and other disadvantaged populations.

Commentary: Private Equity, Women’s Health, and the Corporate Transformation of American Medicine

Since March 2020, our group at the Harvard GenderSci Lab has been critiquing sex essentialist explanations of COVID-19 outcome disparities. Using interdisciplinary tools from feminist philosophy, science studies, and critical public health, we work collaboratively to critically examine COVID-19 sex-difference research and to explore and elevate the role of social variables in driving biological disparities. We argue that, in public health research and messaging, data on sex disparities must be contextualized to avoid reinforcing harmful sex essentialist assumptions and to help the public understand how social factors influence these patterns. In the case of COVID-19, doing so can clarify risks and save lives. Here, we describe our methods and share some of our findings.

A few months into the first wave of the Covid-19 epidemic, men in aggregate appear to have higher fatality rates. But ascribing this outcome to biological sex-related variables, as some have rushed to do, is unlikely to lead to effective interventions. In past epidemics, what at first appeared to be a sex difference turned out to be largely a result of the difference in life experiences between women and men. Occupations, behaviors and pre-existing conditions mattered more than whether one was a woman or a man.