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Why the binary distinction? Clearly, there exists a hierarchy between targets and non-targets. But among the targets, individual ability trumps school affiliation.
School A has undergrad population of 100 and grad population of 10. Assume for the sake of simplicity that under and phd last one year.
All undergrads at school A decide to go to grad school, so 0% are "pre-professional." But, because the grad school has a max population of 10, we get 10/100*1000=100 = Score A. The other students have to go to another school for grad school.
Now let's look at school B. It looks exactly the same as School A (# under at A= # under at B and # phd at A=# phd at B) with the excpetion that people at B hate phd and just want to work/go to law/medicine/etc.
Because of this, 0% of undergrads at B are going to get a PHD and 100% are "pre-professional" Size of Phd program stays the same and just recruits from other undergrad colleges for Phd class. Score B = 10/100*1000=100= Score of A.
So two scenarios:
School A in which 100% of undergrads are "pre-professional" and school A gets score of 100.
School B in which 0 % of undergrads are "pre-professional" and school B gets score of 100.
Your score on this list tells us little to nothing about the percentage of undergrads at the school that are "pre-professional". What affects the scores are the sizes of the under and grad programs.
columbia probably has more folks than other ivies that enter into education, non-profit and in general social justice work - i will offer anecdotally.
I am fairly certain that the study tracks whether or not undergraduate alumni/ae receive PhDs, not where they received them. But if you want to look at the (NSF) list which shows the "percentage of undergrads [that] go on to [successfully] pursue PHDs," here you go:
nsf.gov - SRS Baccalaureate Origins of S&E Doctorate Recipients - US National Science Foundation (NSF)