The point on elite universities is distinctly about how these epicenters have shifted over time, not a snapshot in time today. Germany was home to the world leading higher education institutions in the 19th century. One example, from mathematics—over the years the University of Göttingen was home to Gauss, Riemann, Hilbert, von Neumann, and others. The book cited, “Empires of Ideas”,gets into this evolution and global movement of modern universities.
On the point of talent being equally distributed, I think this is both self-evident and substantiated by many examples and the data. One example that is quite familiar is the proliferation of Indian immigrants now running the global technology companies. A empirical point is the paper we cite on IMO scores, which highlights the existence of talent and the subsequent limitations of opportunity: “an equally talented teenager with the same IMO score born in a low-income country produces 30% fewer publications and receives 50% fewer citations than a participant from a high-income country.”
On the point of talent being equally distributed, I think this is both self-evident and substantiated by many examples and the data. One example that is quite familiar is the proliferation of Indian immigrants now running the global technology companies. A empirical point is the paper we cite on IMO scores, which highlights the existence of talent and the subsequent limitations of opportunity: “an equally talented teenager with the same IMO score born in a low-income country produces 30% fewer publications and receives 50% fewer citations than a participant from a high-income country.”
IMO scores don’t help either, they sample people from the edge of the distribution and may be more representative of “talent” (which PISA and PIRLS are not designed to show), and even still we see similar variation. Your quote of an “an equally talented teenager...” assumes the conclusion (comparing people of equal measured ability), as there are countries with 230m people which always get outscored by a large amount than countries with 5m people. An economic model again doesn’t predict UAE, or North Korea (which does very, very well, scoring one place behind South Korea in 2019 and 2015). Again pointing against an equal distribution.
It’s easy to disprove an equal distribution; however, it’s also very easy to disprove a distribution that closely fits opportunities (say, measured by economic development).
I’d also like to note that IMO performance is a strong but quite noisy signal of top talent distribution, due to some countries’ educational and career systems not particularly caring about it (France comes to mind); some countries kneecapping their performance on purpose (China doesn’t let anyone participate twice), and the cultural importance of high-school competitions varying between countries.
We see Asian American’s overrepresented in some metrics such SAT scores and see them overrepresented in tech employment. There overrepresentation is not a sign of equal distribution.
It could just be that Asian parents encourage their children to study in a way that builds specific talents that are useful for success at global technology companies.
The claim that talent is equally distributed means that talent is both independent from cultural upbringing and of genetics and not supported by finding a single demographic that does well at something.
When it comes to innovation it’s worth noting as well that having different talents as other people is useful for innovation.
Hi Christian—thanks for reading!
The point on elite universities is distinctly about how these epicenters have shifted over time, not a snapshot in time today. Germany was home to the world leading higher education institutions in the 19th century. One example, from mathematics—over the years the University of Göttingen was home to Gauss, Riemann, Hilbert, von Neumann, and others. The book cited, “Empires of Ideas”, gets into this evolution and global movement of modern universities.
On the point of talent being equally distributed, I think this is both self-evident and substantiated by many examples and the data. One example that is quite familiar is the proliferation of Indian immigrants now running the global technology companies. A empirical point is the paper we cite on IMO scores, which highlights the existence of talent and the subsequent limitations of opportunity: “an equally talented teenager with the same IMO score born in a low-income country produces 30% fewer publications and receives 50% fewer citations than a participant from a high-income country.”
Cross-national, large sample PISA tests, the most recent of which had >600,000 students, show considerable variation in mathematics, science, and reading scores. See these charts, https://en.wikipedia.org/wiki/File:PISA_average_Mathematics_scores_2018.png, https://en.wikipedia.org/wiki/File:PISA_average_Science_scores_2018.png, https://en.wikipedia.org/wiki/File:PISA_average_Reading_scores_2018.png. A recent Progress in International Reading Literacy Study report shows similar variation, with 400,000 students. A simple GDP per capita model fails to predict scores in Qatar, UAE, or China. This and other such international tests all point against an equal distribution.
IMO scores don’t help either, they sample people from the edge of the distribution and may be more representative of “talent” (which PISA and PIRLS are not designed to show), and even still we see similar variation. Your quote of an “an equally talented teenager...” assumes the conclusion (comparing people of equal measured ability), as there are countries with 230m people which always get outscored by a large amount than countries with 5m people. An economic model again doesn’t predict UAE, or North Korea (which does very, very well, scoring one place behind South Korea in 2019 and 2015). Again pointing against an equal distribution.
It’s easy to disprove an equal distribution; however, it’s also very easy to disprove a distribution that closely fits opportunities (say, measured by economic development).
I’d also like to note that IMO performance is a strong but quite noisy signal of top talent distribution, due to some countries’ educational and career systems not particularly caring about it (France comes to mind); some countries kneecapping their performance on purpose (China doesn’t let anyone participate twice), and the cultural importance of high-school competitions varying between countries.
We see Asian American’s overrepresented in some metrics such SAT scores and see them overrepresented in tech employment. There overrepresentation is not a sign of equal distribution.
It could just be that Asian parents encourage their children to study in a way that builds specific talents that are useful for success at global technology companies.
The claim that talent is equally distributed means that talent is both independent from cultural upbringing and of genetics and not supported by finding a single demographic that does well at something.
When it comes to innovation it’s worth noting as well that having different talents as other people is useful for innovation.