Scientists use big data to understand what separates winners from losers

Regarding counter-terrorism, that would suggest that rather than more surveillance we instead need better reporting of and responding to failed terrorist incidents/attacks.

My sense is that a grant, like an academic paper, is often basically well-received or not. So prior to going into it, if you're familiar with the details of the particular grant, you can get some sense of interest or not. The grant may have even been solicited in a certain sense by a program officer or something, so it's quasi-invited.

Those grants that are quasi-invited, or well-received, will basically involve polishing on subsequent revisions. Those that are totally unsolicited and not well-received it doesn't matter how much polishing you do often, it will not go anywhere.

I think where this becomes relevant to the paper is that this often has very little to do with the process of the grant revisions. It says little about "how someone responds to failure", and everything about connections with the grant agency, program officers, and luck. All that stuff that happens before the grant is even submitted plays into it, and this paper kind of ignores that.

You could say that it does speak to learning, in that you could ask "why doesn't the other scientist adjust their strategy?" To which I'd say, there are enormous pressures to submit anyway, and for someone who doesn't get good mentoring about what to target, or what agency to target, or whose research doesn't jive with the priorities of the division head at that time, or whatever, they might just not get it, and it might easily be over the 5 year period of the study.

Basically, at least with NIH grants I think this study is really misleading and potentially harmful, because it kind of suggests failed applicants just aren't learning, when I think what's really happening is that you have a mixture of two groups, one of which can learn something, and the other of whom it just doesn't matter if they learn or not, because the outcome has kind of been preordained.

That is, the process they predict from is an indicator of which mixture class the applicant belongs in, not the cause of the outcome.

This is confounded by the fact that the closer one is to success the more frequent their attempts tend to be. The article doesn't indicate the research took this into consideration.

e.g. Golfers takes shots more frequently the closer they are to a hole. But telling a golfer from the start to take a series of frequent short shots is bad advice.