Through what methods would we know whether COVID-19 deadlier for men than for women? In a new commentary just out in Women’s Health Issues, the GenderSci Lab examines the limitations of case fatality rate (CFR) as a metric for studying sex disparities in COVID-19 outcomes.

In a collaboration with the Harvard SOGIE Health Equity Research Collaborative, today the Harvard GenderSci Lab has a new post up on the Health Affairs blog about gaps in COVID-19 public health data collection on trans, non-binary, and gender-expansive people.

In this blog post, I’m going to walk through how sperm statistics are made by analyzing the 2017 paper by Levine et al., wherein the authors argue that sperm counts around the globe are dropping–but most particularly in “Western” countries and not “Other” countries. I highlight some key methodological choices that Levine et al. and others made while trying to gain insight into the state of global sperm counts.

Counting is usually assumed to be a pretty simple activity; it is, after all, one of the very first things that we learn at school . . . . In this blog post, I examine the ways in which sperm count is less straightforward than it might appear, and consider what this means for scientific research on global sperm count decline.

This piece takes a more in-depth look at the current reporting of individuals who identify as non-binary or who are unclassified by sex. The take-home, summarized in Tables 1 and 2 below, is that there are few states explictly collecting data on trans and nonbinary people, and that the ways in which states report “unknown” gender/sex lack transparency and are highly discordant across states.

According to the Gender Equality Paradox, the more gender equal a country, the fewer women in that country participate in STEM. But how is a country's gender equality measured? In this post, we show how looking carefully at measurement choices might lead us to re-think scientific claims about the so-called Gender Equality Paradox.