October Mystery Map Solution

Only one person submitted a guess to our latest Mystery Map competition.  Amazingly enough, this guess was correct for all three variables, so congratulations – again – to Sam Masinter!  Here are the winning answers:


Variable A: number of scientific* Nobel Prizes per country

Variable B: number of universities per country (see this link for the source)

Variable C: number of scientific Nobel Prizes per university for every country in the world

*scientific is defined as Noble prizes in physics, chemistry, physiology/medicine, and economics (which isn’t really a Nobel prize, by the way).  I obtained these data from Wikipedia, the most up to date source on this topic, so I didn’t create this definition of “scientific” myself.


There are plenty of maps about Nobel prizes that show the uneven geographic distribution of these coveted awards. The Global North has amassed almost all of the scientific prizes since the first Nobel was awarded in 1901. Of course, we would expect countries with larger populations, such as Germany or the US, to have more medals. But, the trend still holds when you look at Nobels per capita.

Giving the Nobel system the benefit of the doubt, I decided to normalize the number of Nobels by a different data set – number of universities per country.  The distribution of universities throughout the world is problematic in its own right, since education is so intertwined with imperialism, past and present.  Maybe, I hypothesized, Nobel committees are just picking the best awardees they can given the flawed state of education globally. This claim would be supported if the distribution of Nobel prizes roughly matched the global distribution of universities; in this hypothetical situation, a map of Nobels per university would not show the clear North/South divide that’s apparent in the other maps.

As it turns out, though, the North/South divide becomes (arguably) more apparent in the Nobels per university map.  Notably, China and India fade more into the background on the normalized map (variable C) than on the raw number of Nobels map (variable A). To me, this indicates that there is some sort of systemic bias in the selection of Nobel prizes – perhaps Nobel committees look for nominees in universities of the Global North, or perhaps they perceive research coming out of the Global South as inferior.  Of course, this map doesn’t prove anything (maps rarely do), but it does suggest that this pattern is worth studying more in depth.

With more time, I would have loved to make some variations on this map, such as:

  • considering how the distribution has changed over time, like this article from FiveThirtyEight
  • taking gender into account – in general, do women laureates come from different countries than men?
  • analyzing each award’s geography independently.  This would be hard, since I haven’t found an up-to-date tabulation of Nobels broken down by discipline and country, so I’d have to compile this data from scratch.

The award for most insightful guess goes to June Ahn ’18, whose guess, “number of white people per country,” is sadly much closer to the actual answer than you might think at first glance.