I just stumbled on this summary in Slate of a study by Borjas and Doran (2012, FULL TEXT PDF).

To quote the summary:

According to a new study by Harvard's George Borjas and Notre Dame's Kirk Doran of recipients of the Fields Medal, the most prestigious prize in mathematics, winning big actually kills productivity.

Mathematicians who win it publish far less in the years afterwards than similarly brilliant "contenders"—highly cited mathematicians who won other prestigious awards before the age of 40 (the cutoff for the Fields), but not the prize itself. The prize is awarded every four years to two, three, or four mathematicians. It goes to show that major awards and recognition can have unintended consequences

papers before and after Fields medal

I have not yet read the paper. But my first thought would be that a lot would depend on how you define contenders. I also imagine that the criterion of interest is research achievement, and that number of papers is an imperfect index of this.


  • Does winning the Fields medal actually decrease the research productivity of winners below what it would have been had they not won the medal?
  • How strong is the evidence presented by Borjas and Doran (2012)? What, if any, limitations does the study have?


  • Borjas, G. J., & Doran, K. B. (2012). The Collapse of the Soviet Union and the Productivity of American Mathematicians*. The Quarterly Journal of Economics, 127(3), 1143-1203. PDF
  • $\begingroup$ This is probably because the units on the plot make this difference seem far larger than it actually is. This could be an issue of statistical vs. practical significance. To learn more about statistics, please check out the statistics stackexchange. Best $\endgroup$ – Homeland Sep 12 '13 at 2:49
  • $\begingroup$ @homeland I think that 3 versus 5 widgets of anything per year would be practically important. I.e., almost double the productivity. I agree that the question has statistical elements (and I'm quite active on Stats.SE), but that also, much theoretical judgement would be required to determine whether the comparison group is meaningful. The importance of theory is what motivates me to ask the question here. $\endgroup$ – Jeromy Anglim Sep 12 '13 at 3:13
  • $\begingroup$ You're only getting a ratio of 3/5 near the tail end of the plot (around the 20 year point on the x-axis). Assuming the dataset only includes people who are still active in the field (unretired, etc.) I'd guess there's substantially less data in the far right tail than in the earlier part of the plot. So, it could be sampling variation that is the explanation. Also, a 67% increase isn't always practically significant, e.g. .00000003% vs. .00000005% chance of winning the lottery. $\endgroup$ – Homeland Sep 12 '13 at 3:18
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    $\begingroup$ yep good point. That said, if there was no sampling error, I think the difference observed at five years is practically important. $\endgroup$ – Jeromy Anglim Sep 12 '13 at 4:01
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    $\begingroup$ My first thought upon reading the title was “beware of age/career stage” but it would precisely seem to be a good reason to select “contenders” as a control group. Interesting stuff in any case… $\endgroup$ – Gala Sep 13 '13 at 8:16

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