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.
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.