There is nothing like a round of study section to make you wish you were the Boss of ALL the Science.
There is just soooo much incredible science being proposed. From noob to grey beard the PIs are coming up with really interesting and highly significant proposals. We'd learn a lot from all of them.
Obviously, it is the stuff that interests me that should fund. That stuff those other reviewers liked we can do without!
Sometimes I just want to blast the good ones with the NGA gun and be done.
Notice of Grant Award
Do not EVER spend so much time geeking away about the amazingly swell trees that you will be characterizing that you forget to convince the reviewer that the forest itself holds any interest. And I mean ANY interest.....Seriously dudes, I'm trying to help you out here but you are giving me absolutely nothing to work with. There is barely any point in me even reading your experimental manipulations....I can tell already there is no overall justification for doing them in the first place!
Everyone is going to hate you, pretty much.
Think about it. You have 7-10 grants assigned in your pile on a typical study section these days. Odds are good that at best one or two of these is going to be good enough to be in the hunt for funding. The rest of the panel is in the same boat, so it really doesn't matter that the applicants don't know precisely which of you* on the panel reviewed his or her proposal.
80-90 % of the applicants are going to be mad at you.
Since you have been selected for expertise in the relevant field...these are people who you know. You know their work and you probably like and cite it. They know you. They know your work.
And for at least a while after they see their disappointing score, and for another while after the pink sheets are posted, they cannot help but hate you a little.
Maybe even a lot.
*If you were triaged you do know for absolute sure that every member listed on that panel roster stood by and refused to pull your application up for discussion.
Thanks to an exchange with PhysioProf after this comment, I dug up the summary statement for the first R01 proposal I ever submitted to the NIH as a PI. I was trying to remember how badly I got hammered on the "investigator" criterion.
They were pretty nice about it but it boiled down to a pronounced skepticism that some noob-ass not-yet-assistant-professor upjumped postdoc was going to be able to pull off an R01 sized, collaborative study.
Of course, within a 12 month interval from that review I was heading up at least 2X that amount of work and the eventual publication record was, I would argue, adequate at the least.
This is not to brag and I don't think this is unusual at all. This comment is to further reinforce my assertions that questioning the ability of a newly minted Assistant Professor of the current usual type in biomedical researchdom to handle a $250K direct cost R01 project is absurd.
I mean sure, if there are unusual circumstance yes, you can raise an eyebrow. But for someone of the usual training duration (3+ years of postdoc after 5+ years of grad training), with at least some first and middle author publications who is now in their mid 30s or later and has competed successfully for a job.... I mean come. on.
They can handle this. The only thing between them and producing is the grant award.
sorry, the "hilarity" part is my reaction to reading such an old dusty pink sheet. man, I was but a wee grantwriting tot back then.
If you had to put an explicit weighting on the relative influence of Investigator/Environment/TrackRecord versus Idea/Plan/Significance/Innovation in evaluating grant proposals, what would it be?
-feel free to elaborate on your career stage as you stake your flag.
The hardest thing about grant review is giving good scores to proposals that clearly suck compared with your own proposals that have been scoring* outside of the fundable range in recent rounds.
*because of rat bastige biased and incompetent reviewers that make eRroRZ of FaCT!, of course.
Yes, I realize that this is a competing continuation and that you have many published papers. But you use the figures, published or not, to help tell the story of your proposal.
Wall to wall text is still a huge Grant FAIL.
You know when you are faced with using somebody's crappy bit of code but you could just write the whole thing from scratch? But then you'd have to 'splain to the boss man why you spent all that effort doing by a totally different way? And the client will be pissed....and the coding team will be pissed...and basically it all just sucks ass. But you can't bear to let the cluster borkage mess exist and still call yourself a professional?
Reviewing a revised NIH grant that you didn't review for the original submission is a little bit like that.
If I do not have any idea, within about three sentences into your Specific Aims page, what model systems, subjects and broad experimental approaches are going to be in your proposal you are seriously screwing up your grantsmithing.
As I previously noted (somewhat critically) that the NIAID had posted sample R01 grants and the corresponding summary statements. Well, they've added some R21 applications to the page.
Again, I wonder how useful this really is for most applicants. First thing you notice is that it takes a perfect score to get funded. Three of the four received 10s and the fourth limped home with an 11. Remember, the study section score range starts at 1, which is then multiplied by 10 after the voting of the entire panel is averaged.
Then there's this (emphasis added):
From the Dow summary statement's resume of discussion: "Strengths of the application include the accomplished investigator and research team, strong preliminary data, the direct doable and logical set of experiments, and the likelihood of paradigm shifting insights into meliodosis"
From the resume on the Starnbach app: "Strengths of the application include the innovative use of the novel GPS strategy, compelling preliminary data, an investigator with a strong bacterial pathogenesis research track record, an excellent and appropriate set of collaborators, and a high degree of confidence that import results will emerge from these studies."
Weis, individual critique #2: "Strong and compelling preliminary data is presented that indicate a high likelihood of success"
Well, at least NIAID is telling it like it is with these examples.....