Helping scientists during the pandemic: lessons from gender disparities


The following article is authored by Kyle R. Myers.


There is no doubt that this pandemic has disrupted the pace of science around the world. But not all scientists have experienced the same level of disruption. In light of these differences, science policy makers should look to some lessons learned from studying long-standing gender disparities in the workforce.
How large are these differences? Our survey work has illustrated that no two scientists have been affected by the pandemic in the same way (Myers et al, 2020a). Looking across disciplines, those in the “bench sciences” (e.g., biologists, chemists) systematically reported larger disruptions to their research, while others in fields such as economics, mathematics, and statistics tended to report much smaller changes. Important socio-demographic differences have also emerged: female scientists and those with young children at home have been able to commit much less time to their research. And the disruptions are not over, as scientists expect them to continue as long as the pandemic persists (Myers et al, 2020b).
It is important to note that these comparisons across disciplines and individuals are averages. A large amount of the variation in responses to our surveys persists even after we control for many important factors surrounding each scientist’s professional and household situation. So, these features should not be used as litmus tests, but rather as guideposts for identifying scientists in need of support.[1]
What are the implications of these unequal effects? What lessons might we apply from our understanding of gender disparities across the economy when devising policies to help scientists now, and in the future?
First, the research of Claudia Goldin has emphasized that the presence of “winner-take-all” contests will tend to disproportionately reward individuals who work long and particular hours (Goldin, 2014). Science is full of these sorts of contests – competition for tenure at universities, races to make discoveries – and the pandemic continues to force some scientists to focus their time in other directions (e.g., home-schooling, health care). Just as Professor Goldin’s work emphasizes the value of flexible work arrangements as a tool for gender convergence economy-wide,[2] so too will flexibility be an important feature of science policies moving forward. The specifics of these policies and procedures are still evolving (e.g., virtual teaching, remote conferences), but beyond this pandemic, embracing a more flexible approach when designing the job of a “scientist” will likely be an important part of increasing and maintaining equity and diversity in the scientific workforce.

Second, science policy is not immune from the unintended consequences of policies. Of the many efforts to address gender disparities at academic institutions, one of the most popular policy changes has been the introduction of gender-neutral “tenure clock stopping” policies for family events such as childbirth or adoptions. These policies were seemingly designed to help academics balance their career and family duties. However, evidence based on the promotions (or lack thereof) of economics professors at U.S. universities indicates that these substantially reduced female tenure rates while substantially increasing male tenure rates (Antecol, et al., 2018). This highlights the challenge of using one-size-fits-all policies to address unequal circumstances. Still, the vast majority of U.S. universities that implemented tenure clock extensions in response to this pandemic did so with blanket policies that applied to all pre-tenure professors (Myers et al, 2020a). Whether this approach will have unintended consequences remains to be seen.
Instead, policy makers should strive to direct support and resources in a more tailored approach to scientists who, because of the style of their research or their socio-demographics, have suffered the largest disruptions in this pandemic. The effects of the pandemic have been unequal, so the response should be too.
Certainly, it is a challenging prospect to develop more flexible work arrangements for scientists, or policies that are tailored to the specifics of a scientist’s home-life or style of research. This would involve more difficult decisions by administrators choosing to help some scientists more than others. However, an optimist might say that the circumstances forced by this pandemic have provided both the desire and the motivation to make changes that will not only help scientists recover from this pandemic, but that could prove helpful well into the future.


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Myers, K.R., Tham, W.Y., Yin, Y., Cohodes, N., Thursby, J.G., Thursby, M.C., Schiffer, P., Walsh, J.T., Lakhani, K.R. and Wang, D., 2020. Unequal effects of the COVID-19 pandemic on scientists. Nature human behaviour, 4(9), pp.880-883.


Myers, K., Lakhani, K.R. and Wang, D., 2020. Towards Recovery: Scientists With Better Ratings of Their Institution’s COVID-19 Response Have More Optimistic Forecasts. Available at SSRN 3712876.


Goldin, C., 2014. A grand gender convergence: Its last chapter. American Economic Review104(4), pp.1091-1119.​


Antecol, H., Bedard, K. and Stearns, J., 2018. Equal but inequitable: who benefits from gender-neutral tenure clock stopping policies?. American Economic Review108(9), pp.2420-41




[1] For instance, our finding that bench scientists have reported (and forecast) the largest disruptions due to the pandemic does not imply that no other field should receive attention. Rather, it suggests that scientists whose style of research resembles that of a “average” bench scientist has likely been struggling more than others. This would include scientists whose work tends to be performed in large, in-person teams, in specific locations (e.g., laboratory, field site, secured data facilities), and who tend to work with very time-sensitive inputs (e.g., living organisms). While our data suggests that the average biologist is facing more challenges than the average economist, it would likely be easy to find, for example, a biologist that specializes in computational analyses of pre-existing data who has had much smaller disruptions to their research compared to an economist who specializes in field experiments in real-world businesses.
[2] In Goldin (2014), “flexibility” is related to both the number of hours to be worked as well as the specifics of those hours (i.e., degree of time pressure, in-person interaction with others, or being available for short-notice demands).

Kyle R. Myers is an economist and assistant professor of business administration in the Technology and Operations Management unit at the Harvard Business School.
The author is responsible for the facts contained in the article and the opinions expressed therein, which are not necessarily those of UNESCO and do not commit the Organization.