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In a paper forthcoming at Nature Human Behaviour, we track school closures during each month of the pandemic for nearly every school in the U.S. (100k+). Our results show large racial and socio-economic disparities in exposure to school closures. Short 
. https://osf.io/cr6gq
. https://osf.io/cr6gq
1/ First, the obvious: school closures may be necessary to slow spread of COVID. This paper takes no position on whether schools should close (we are not epis). But school closures do carry other consequences (edu performance, etc.). Our goal: identify who is exposed to closures.
2/ Using anonymized, aggregated mobile phone data, we track closures at 100k+ schools throughout 2020. The peak in closures was, of course, in April. But even in December, we estimate more than half of schools in the U.S. were closed or engaged in distance learning.
3/ Which students face greatest exposure to school closures? Let’s start with trends by race/ethnicity. From August through November in particular, Asian, Black, and Latino students far more likely than White students to be exposed to closures or distance learning.
4/ Another way to view the disparities: binned scatterplot of closure rates (Y-axis) by share of students with the labeled characteristics (X-axis). Lower-left, for example, shows: schools with lower 3rd grade math scores = higher closure rates.
5/ What about geographic disparities? Darker colors in the map here = larger year-over-year decline in in-person visits to the schools in the given county. The Midwest, perhaps unsurprisingly, looks very different from the coasts.
6/ In the paper, you’ll also find plenty of validation tests, more on our methods, and a link to download our School Closure Database for yourself at either the school district, census tract, county, or state level for each month in 2020 (and soon Jan 2021).
7/ Or, for a short summary of the paper, you can read this coverage in The New York Times, also featuring results from @pengzell, @RichardvReeves, and one low-income family’s harrowing experience with distance learning. https://www.nytimes.com/2020/12/24/us/remote-learning-student-income.html
8/8: Finally, a shout-out to my talented co-author, Emma K. Lee, who is working as an undergraduate RA at Columbia. This paper would not have been possible without her brilliant data collection work. First of her many publications to come, I anticipate!
