Interesting! Many great threads here. I definitely agree that some component of scientific achievement is predictable, and the IMO example is excellent evidence for this. Didn’t mean to imply any sort of disagreement with the premise that talent matters; I was instead pointing at a component of the variance in outcomes which follows different rules.
Fwiw, my actual bet is that to become a top-of-field academic you need both talent AND to get very lucky with early career buzz. The latter is an instantiation of preferential attachment. I’d guess for each top-of-field academic there are at least 10 similarly talented people who got unlucky in the paper lottery and didn’t have enough prestige to make it to the next stage in the process.
It sounds like I should probably just read Sinatra, but its quite surprising to me that publishing a highly cited paper early in one’s career isn’t correlated with larger total number of citations, at the high-performing tail (did I understand that right? Were they considering the right tail?). Anecdotally I notice that the top profs I know tend to have had a big paper/ discovery early. I.e. Ed Boyden who I have been thinking of because he has interesting takes on metascience, ~invented optogenetics in his PhD in 2005 (at least I think this was the story?) and it remains his most cited paper to this day by a factor of ~3.
On the scientist vs paper preferential attachment story, I could buy that. I was pondering while writing my comment how much is person-prestige driven vs. paper driven. I think for the most-part you’re right that its paper driven but I decided this caches out as effectively the same thing. My reasoning was if number of citations per paper is power law-ish then because citations per scientist is just the sum of these, it will be dominated by the top few papers. Therefore preferential attachment on the level of papers will produce “rich get richer” on the level of scientists, and this is still an example of the things because its not an intrinsic characteristic.
That said, my highly anecdotal experience is that there is actually a per-person effect at the very top. I’ve been lucky to work with George Church, one of the top profs in synthetic biology. Folks in the lab literally talk about “the George Effect” when submitting papers to top journals: the paper is more attractive simply because George’s name is on it.
But my sense is that I should look into some of the refs you provided! (thanks :)
its quite surprising to me that publishing a highly cited paper early in one’s career isn’t correlated with larger total number of citations, at the high-performing tail (did I understand that right? Were they considering the right tail?
No, they considered the full distribution of scientists with long careers and sustained publication activity (which themselves form the tail of the larger population of everyone with a PhD).
That is, their analysis includes the right tail but wasn’t exclusively focused on it. Since by its very nature there will only be few data points in the right tail, it won’t have a lot of weight when fitting their model. So it could in principle be the case that if we looked only at the right tail specifically this would suggest a different model.
It is certainly possible that early successes may play a larger causal role in the extreme right tail—we often find distributions that are mostly log-normal, but with a power-law tail, suggesting that the extreme tail may follow different dynamics.
Interesting! Many great threads here. I definitely agree that some component of scientific achievement is predictable, and the IMO example is excellent evidence for this. Didn’t mean to imply any sort of disagreement with the premise that talent matters; I was instead pointing at a component of the variance in outcomes which follows different rules.
Fwiw, my actual bet is that to become a top-of-field academic you need both talent AND to get very lucky with early career buzz. The latter is an instantiation of preferential attachment. I’d guess for each top-of-field academic there are at least 10 similarly talented people who got unlucky in the paper lottery and didn’t have enough prestige to make it to the next stage in the process.
It sounds like I should probably just read Sinatra, but its quite surprising to me that publishing a highly cited paper early in one’s career isn’t correlated with larger total number of citations, at the high-performing tail (did I understand that right? Were they considering the right tail?). Anecdotally I notice that the top profs I know tend to have had a big paper/ discovery early. I.e. Ed Boyden who I have been thinking of because he has interesting takes on metascience, ~invented optogenetics in his PhD in 2005 (at least I think this was the story?) and it remains his most cited paper to this day by a factor of ~3.
On the scientist vs paper preferential attachment story, I could buy that. I was pondering while writing my comment how much is person-prestige driven vs. paper driven. I think for the most-part you’re right that its paper driven but I decided this caches out as effectively the same thing. My reasoning was if number of citations per paper is power law-ish then because citations per scientist is just the sum of these, it will be dominated by the top few papers. Therefore preferential attachment on the level of papers will produce “rich get richer” on the level of scientists, and this is still an example of the things because its not an intrinsic characteristic.
That said, my highly anecdotal experience is that there is actually a per-person effect at the very top. I’ve been lucky to work with George Church, one of the top profs in synthetic biology. Folks in the lab literally talk about “the George Effect” when submitting papers to top journals: the paper is more attractive simply because George’s name is on it.
But my sense is that I should look into some of the refs you provided! (thanks :)
No, they considered the full distribution of scientists with long careers and sustained publication activity (which themselves form the tail of the larger population of everyone with a PhD).
That is, their analysis includes the right tail but wasn’t exclusively focused on it. Since by its very nature there will only be few data points in the right tail, it won’t have a lot of weight when fitting their model. So it could in principle be the case that if we looked only at the right tail specifically this would suggest a different model.
It is certainly possible that early successes may play a larger causal role in the extreme right tail—we often find distributions that are mostly log-normal, but with a power-law tail, suggesting that the extreme tail may follow different dynamics.
Sorry meant to write “component of scientific achievement is predictable from intrinsic characteristics” in that first line