Preparing our gunsights: What types of investigators exist in the NIH system?
January 30, 2013
This figure was posted by Sally Rockey, head of the Office of extramural research on her blog Rock Talking. We have discussed these data in the past but given my recent Fixing the NIH series of posts, I thought it worth bringing up.This depicts the number of investigators funded by the NIH who hold a given number of Research Project Grants as Principal Investigator. This includes a range of R-mechs, U-mechs, DPs, Program Projects, etc. As Dr. Rockey noted:
If you crunch the numbers, you will see that in each of the four years presented more than 90 percent of our investigators hold one or two research project grants.
And, if as I do, you spy a slight trend for increasing numbers of grants per investigator over time, I refer you to my analysis of the real purchasing power of the full modular ($250K in direct cost per year) R01. The short version is that the full-modular of FY 2011 had 69% of the purchasing power of the same award in FY 2001. A PI needs about $350K per year to have the same grant. Also note that the chances of suffering budget reductions upon funding and even on non-competing renewal, due to ongoing Continuing Resolution problems with Congress, has increased relative to the early noughties. So a little aggregate creep in the number of grants per PI should be expected.
The reason for Dr. Rockey presenting these data in the first place coincides with my reason for posting the graph today. Because one of the very popular “fixes” for the NIH incorporates some version of the assertion that there are some PIs who enjoy a huge amount of funding and that by preventing them from doing so, we’ll be able to give a lot more people a basic level of support. “Blood from a stone” is not precisely the right aphorism here but suffice it to say, there aren’t enough of these hugely funded labs to make a difference. Yes, of course, one R01 subtracted from Professor MoneyBags could go to Asst. Professor J.R. Mint and thereby make a HUGE difference in her life. But on the order of systematic fixes…..this does little.
This is the now famous cartoon by Dent which describes “types” of Principal Investigators. Obviously it is drawn from the perspective of trainees (no?) but it resonates with a timeless truthiness. To me anyway. And it is somewhat useful in our considerations for how to fix the NIH. We have to reduce the number of mouths at the trough, this is obvious. I’ve proposed that we need a prospective approach for the medium to long term future. I here renew my assertion that we need to get specific about which type of PI is to be put in the gunsights for reduction.
Obviously, the answer is “That guy! over there….yeah, HIM. Not me, nuh-uh, I need to be preserved at all costs, dude!”
Sigh.
This is precisely why we need to have this conversation and precisely why the NIH needs to get more serious about making this hard call for themselves. Otherwise the culling will continue in an uncontrolled, random bolt-of-lightning fashion. Rockey called this “Darwinian” in (I think) a quote in a Science news bit AAAS bit. I don’t think that is quite the right term….laissez-faire maybe? At any rate. They are going to have to make the culling intentional if they have any interest whatsoever in 1) quality differences between funded investigators and 2) ensuring that the pool that remain after this great culling occurs is as high in quality* as possible.
One possible axis for pursuing this more-rational culling of the herd should involve thinking about types of operations. Small town grocer? Glamour Hound? Dreamer? Slave driver? Are any of these PI phenotypes associated with better value received for dollar spent by the NIH? Or is PI quality entirely uncorrelated with “type” of operation?
Raise your eyes back to the first graph. NIH has a lot of information on PI “type” based on the number of grants / dollars awarded. Some additional relevant information from University or Institute “type”. Does the size of the total NIH extramural portfolio (dollars, numbers of PIs, etc) at local institution influence success? They can, if they choose, do a bunch of retrospective peeking along a given PIs career track to see if a certain funding threshold at various points in the career are associated with success / failure. They need these data to evaluate Michael Eisen’s thresholds, btw.
I plead with you. As you engage in this discussion around and about…on blogs and in real life conversations….try to focus on the data we have. And the analyses that the NIH could conduct in the future. For these latter, demand them over at Rock Talk. Try to temper your knee-jerk “do it to that guy over there, my type of investigator is the BESTEVAH!!!” with some consideration of a larger picture. It is HARD. Believe me I know. Like I said elsewhere, I have no desire to be culled. None whatsoever. So obviously I’m looking very hard for arguments for why my type of scientist, my type of science, my type of job category and my type of institution are providing the best value. Given this, we should all double down on understanding and integrating data if it is available.
Recognizing that some 90 percent of PIs in the NIH system have only one or two RPGs is an example of what I mean.
Additional Reading on Fixing the NIH:
The NIH must dismantle the corrosive competitive culture of science
Shut off the PhD tap
We are going to fix the NIH
__
*yes there are many qualia that could be of interest here.
DrugMonkey 
January 30, 2013 at 9:39 am
Don’t we need a variety of investigators types? Isn’t the issue about the proportions of those types?
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January 30, 2013 at 9:46 am
Well, it was kind of the point to ask if we need variety and what proportion we should target.
Me, I think we should be going after the small town grocer category. The first graph shows that if there are gains to be made, the one-granters are the place to go looking. Two, inefficiency of insufficient scale- can’t hire 1.5 techs on one grant but you can hire three on two grants. That sort of thing. Also, the question of projects which end up being dry wells.
My problem with Eisen’s tiered funding is related…next to no-funding the surest killer of a launch is insufficient funding to actually do much. Then you have the double whammy of having had “an award” and poor productivity to show for it. Contrast this with the people who happened to launch with good fortune, spooled up to two grant labs within 4-5 years. The are typically in good shape.
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January 30, 2013 at 9:47 am
I don’t understand the point of NIH putting this up. We all knew this anyway and I’m just waiting for more details about what they ARE going to do if/when sequestration hits and for the next few years vs. what they are NOT going to do (mandate one grant/PI rules etc, which is the purpose of this figure). The military has come out and said how they will deal with it, what about the NIH?
What will happen is they will preserve the R01 “success rates” at all costs because that’s what everyone sees. It’s not rocket science. They will cull all over mechanisms to do it.
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January 30, 2013 at 9:47 am
I don’t think number of grants is all the data we need, unless all grants are more-or-less the same size. I’d like to see that same graph with “total funding” along the x-axis.
The Eate-the-Riche argument might still be valid: the 10% of investigators with >1 grant might still control, I dunno, >50% of the available funds. Or is that not possible, given the distribution of actual cash values among grants?
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January 30, 2013 at 9:56 am
Disclaimer: I’m at a fly-over state, small medical school.
Whenever I hear terms like ‘culling’, I just assume that they are coming after me…not me, per say, but folks like me at my institution. We do great science. We have maybe one person who has multiple R01’s, the rest of us are trying, but it’s tough. We are eligible for R15, but the stability you get from an R01 is unmatched. My point is when the culling starts-will institutions like mine automatically get the axe because we aren’t an tier 1 or even tier 2 place?? Honestly, I hope not. I hope quality of science is preserved, regardless of their tiered or geographic location.
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January 30, 2013 at 10:07 am
Whenever I hear terms like ‘culling’, I just assume that they are coming after me…not me, per say, but folks like me at my institution.
Not at all. First, there is the bulwark of the Congressional district to protect you. Very stalwart stuff this is indeed. Second, as I mentioned in a prior post, while the NIH has muttered about people with too much aggregate funding, too many awards (yes bill, you can find what you are looking for with a little poking), too high of an indirect rate…I have yet to hear any serious proposals that small time Universities should be targeted. Some people (PP) may suspect that this is what the NIH is up to with their allegedly hands-off approach but at least they are not bringing it up explicitly for consideration.
We do great science.
everybody does. the question is rather about efficiency in these times and, to some extent, solving the too-many-mouths problem long term. I am at the point where (selfishly, selfishly) I am advocating (cautiously) that targeting small-to-medium institutions may be one place to get bang for the buck. It is based on my contention (awaiting Rock Talk datamining) that one significant part of the swelling of mouths came from previously non-NIH-focused smaller University deans catching on to the NIH indirect cost “solution” to their local problems.
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January 30, 2013 at 10:09 am
The problem with culling smaller groups is that basic research relies on a plant-a-thousand-seeds philosophy to produce truly innovative discoveries (as opposed to focused health-related research). I think the more scientists you can fund the better. Most labs are wasteful because the curtain system encourages buying the same thing that’s used once a week 10 times. Grants should in general be smaller and labs should have to share resources/equipment more. (Please don’t tell me this can be difficult. No shit.) This is anathema to the prevailing BSD culture, however.
In terms of output, I agree that the “most” knowledge is probably produced by mid-seized, 2-3 R01 equiv labs. Not sure if “most” (as opposed to most creative, most innovative, most useful, most efficient) is the right measure, however, as it seems like the current system makes it easy for a certain type of successful scientist to coast very productively while perhaps not adding much in terms of technical advance or increased understanding.
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January 30, 2013 at 10:10 am
I just realized how obnoxious and off base the first sentence of my last post is. Not what I intended.
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January 30, 2013 at 10:13 am
I think the more scientists you can fund the better.
So everyone gets $50K then miko?
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January 30, 2013 at 10:21 am
No, but I think R01s could be maybe 25%-35% smaller and you can’t have more than 2. Luckily, in my world, you’re not allowed to spend it on trainee salaries/tuition, so you have savings there. Plus, now that you aren’t desperately trying to get more grants (because you can’t have them), your best chance of renewal comes from getting your own ass in the lab and doing science instead of being an administrator.
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January 30, 2013 at 10:22 am
What if the answer is that scientific insights and productivity come collectively from all the different types of PI/lab operations? Although there is no question that some labs are more successful in the long term than others, I think there are many factors that can be quite unpredictable feeding into productivity and key discoveries, e.g., ease/expense of model system, good luck in getting a fantastic first postdoc or student, working on a system that happens be “hot” at the right time putting you in a good funding position, etc. It has been pointed out many times that people awarded Nobel Prizes often say that at the time, their work was ridiculed, rejected from many journals and generally languished until everyone else caught up. Some of these folks might have been considered “small town grocers” until their work was recognized and funding belatedly followed.
Culling is needed and it’s unrealistic to think there is going to be one answer to this mess. In any effective solution, everybody will have to suffer at every stage of the pipeline: support for fewer Ph.D. students, restrictions on how students or postdocs can be supported on RPG, more support by institutions for their investigators, some limits on total dollars awarded, perhaps at some level, a mandatory age for retirement (70?), fewer RPG awards to institutions that really don’t have a substantial research presence. Unfortunately, everyone will want to protest changes that affects them personally and that presents a huge barrier to any change being made (even if NIH were actually willing to make real changes, which I’m not convinced they are – see raising postdoc salary recommendation post at Rock Talk as a good description of a “change” that will not actually fix anything).
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January 30, 2013 at 10:29 am
right miko. so what you mean is that all PIs should be constrained to doing the science that you do in the way you do it. what you envision as “sufficient” barely gets some labs off the ground….see: human subjects research.
med chem vs flies/worms vs mouse vs rat vs monkey vs human is an (approximately) increasing linear function of cost to paper in the substance abuse fields that I follow.
So fine, I’m happy if you are saying we should reduce down to the common denominator of cookie-cutter labs/science… but you have to stand up for that.
Obviously I think that would be a massive failing because I think everybody doing the same thing is actually an inefficiency in the overall advance of knowledge. It contributes to the competitive cycle as well.
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January 30, 2013 at 10:52 am
I’m not gonna go find the data, DM (sorry to be an asshole but I just don’t have time right now) — but I think you should if you want to support your contention that eate-the-riche won’t work. Without knowing more about the variation in grant sizes (which may be considerable, given your comment above about cost:paper ratios), I think the graph you started with is misleading.
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January 30, 2013 at 11:23 am
I think I’m confused by why start with the presumption that some other system of culling is going to be better than grant review. I agree whole-heartedly with the idea that meaningful differences cannot be made between the 10% and the 9% or even the 10% and the 15% (roughly, I think grant applications can be divided into quarters). But why would some other targeted method have a different probability of producing the best science (rather than producing less risky careers for scientists)?
I’ve suggested culling based on soft money (i.e. leveraging the support of scientists by their universities, rather than creating incentives to universities to over-hire in the hopes that their investment is going to return NIH dividends). I also hope (without much evidence) that this will diversify the way that successful candidates are chosen (that universities will hire based on track history and future guesses, rather than the quality of a grant proposal, while NIH will still judge the grant proposal).
I’d really like to see the graph that shows the proportion of PI costs on NIH grants over the years, to talk about the effect of my soft-money culling.
But, I suspect I’d not be at all confident in arguing that culling along these lines would have a positive effect on the quality/quantity of science compared to culling with study sections.
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January 30, 2013 at 11:29 am
I see at least two points to the data you’re saying we need to look at and ask for — 1) will culling along the lines have a significant financial impact? and 2) what will the effect on quality/quantitiy of science be?
#1 is important, and a lot of suggestions for culling are small change, unlikely to have significant impact (kind of like reducing “waste”).
#2 is the trillion dollar question, no? you say that Miko is arguing for science done like Miko’s, but the difficulty of judging overall scientific impact is the same problem faced in study section. It doesn’t become easier when you try to judge an entire category of research (done at small institutions or by soft money PIs, or whatever category we’re choosing).
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January 30, 2013 at 11:44 am
DM, I have no problem with grants being scaled to what the research costs to some degree, just that there needs to be across-the-board scaling back as well. In the zero sum (or negative sum) game between funding fewer scientists the same and funding more scientists less I lean toward the latter, in large part because I perceive a lot of waste and redundancy within institutions and opportunities to do the same with less with some reorganization. The fact that you can do less with $X in monkeys vs. Drosophila is true no matter what funding system you’re talking about. However, it would be pointless to scale back invertebrate funding to the point we can only expect the kind of experiments done in mammals, because this is, of course, a big part of the reason we study different kinds of animals.
One could just as easily argue (as Florian Engert just did) that you can do many things easier in C. elegans but what you learn is less interesting. So for him, larval fish are the cost/interesting sweet spot. Others could argue that you can do things in flies for a fraction of the cost as in mice and learn many of the same things. I don’t think its controversial that a diversity of systems and approaches is probably best and has historically been successful, that model organisms chauvinism is stupid, or that different systems have different inherent costs and benefits.
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January 30, 2013 at 11:50 am
“(…) that one significant part of the swelling of mouths came from previously non-NIH-focused smaller University deans catching on to the NIH indirect cost “solution” to their local problems (…)”
I might be saying something really naive since I’m still a n00b postdoc but isn’t the indirect cost a really strong inefficiency bottleneck? What if the NIH imposed the following restriction/requirements:
1) Salary for soft money PI comes from indirect cost, no PI-specific F&A adjustment allowed. That way you remove the really perverse side of soft money positions. I’m OK with soft money being used to increase competition or make tenure a sham, but soft money can’t be used by universities to get cheap labor subsidized by government.
2) Request university matching from indirect cost when using direct cost to hire grad student. This is a way to close the PhD tap without producing a shock in the system. You want to increase the student population to assist the growing research portfolio? Fine. But you won’t see a lot more money. This would generate a pressure against increasing the number student. Still, RA and TA work needs to be done, bright kids will always want to go to school, so there would be a steady-state number of grad students >0. Again it is about removing incentives. I think matching is more appropriate because student must cost something for PI to prevent lazy student/negligent professor dynamics.
[One alternative that accomplishes the same goal is removing PI and grad student salaries from the F&A multiplier. My point is to remove overhead gains to the university coming from increase in number of people. Overhead tax on PI salary is bizarre, overhead tax on grad student salary (who is already paying tuition) is surreal. I’m ok with overhead tax on postdocs because they are positions generated by the grant, and additional postdoc hiring increases admin demands on university.]
3) Diminishing indirect costs per PI/institution. A lab with two grants don’t use twice as much resources. And a building with two labs don’t use twice as much resources. If a university wants to increase size to generate a diverse research portfolio and attract bright students and faculty, that is great. But there should be some diminishing incentives so that their bottom line isn’t purely the number of grants. I would be OK with waving this system from non-university institutes, since their bottom line tends to be the number of grants, and the overhead money there is used to improve research-related facilities not to hire more deans or subsidize the rowing team.
I think these measures can adjust the incentives in a way that a PI would have a strong incentive to get the first grant, but not a lot of institutional pressure to get more than one at a time. Still, it allows him/her to get that second grant if the science needs it, or if there is a desire to be a superstar, but university doesn’t get a lot more than a bump in its image by having said superstar. It also adjusts incentives in a way that a non-research university has money if it wants to get in the NIH game, but it doesn’t allow university to solve all their financial woes using NIH money.
*All these suggestions would likely hurt me. (1) is going to reduce the available faculty positions when I enter the job market in a few years. And (2) reduces the available grad school seats so I’m not sure I would’ve gotten in this.
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January 30, 2013 at 12:06 pm
The thing about IDC suggestions is that you have to figure out where the money is to come from. ditto hard-money faculty.
all very well to blame “deanlets and the rowing team” but that is fantasy. NIH can’t really reach into this. What they can do is to concentrate the research dollars into fewer institutions which has a better chance of improving the output to DC+IDC ratio. (obviously this assumes *some* degree of sensible relationship of IDC to actual costs. The Dean of Extramural Grabbing salaries at places that have 5 fold difference in NIH grant earning probably have less than a 5-fold difference, for example.
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January 30, 2013 at 12:22 pm
Add in a section on a grant application for efficiency that takes into account your institutions overhead costs, what sort of money they will put up for personnel/materials, and what sort of facilities they offer. This gives the institution an incentive to become more efficient, keeps more money in the “actually for science pot,” and might allow for more funding (either in total number of average amount). However, comparing Middle America Small Research University vs Large Coastal BSD Factory becomes problematic.
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January 30, 2013 at 12:37 pm
For the money part, the idea is to renegotiate the F&A ratio after setting the policy. Total money remains the same, no extra money needed. For hard money, salary comes from uni coffers, uni gets all IDC to “pay electricity”. For soft money, uni has to pay part of the “electricity” for the grant out of its pocket, but it’s basically money they saved when hiring soft position.
If universities don’t have the cash to pay their current soft money staff, they are essentially an over leveraged investor that has too many stakes in a bad investment. I guess, if you are in an over leveraged university, than you would be culled. But with dying NIH funding, your prospects weren’t really high to begin with.
Also, I’m not expecting NIH to mess with internal school policy. No NCAA style “athletics can’t give money to rest of university”. I just think that a diminishing allowable indirect policy prevents school from engaging in “lifestyle inflation” coming from increase in the number of grants. What I’m saying is that if a school has 5x increase in NIH direct cost earning, then the IDC would increase 2x, instead of 5x. That way you only double the salary of the DExGrab, instead of doubling his salary and hiring two extra assistants.
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January 30, 2013 at 12:44 pm
Agree with one thing though: if NIH wants strictly to maximize efficacy of their money, they should get out of universities and fund only few giant labs and grad-only institutes distributed geographically. That way they keep diversity and grad student labor but decrease dean shenanigans increase concentration for better DC:IDC ratio.
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January 30, 2013 at 12:45 pm
What isn’t in these numbers are the PIs with contracts, U19s, PO1s etc. Those grants are essentially multi-PI RO1s that should factor into these. I am certain that I know atleast 10 PIs with 1 RO1 but also 1 large contact and 1 U19. And I do know that several of these PIs are double funded for very similar projects. Fold all of those types of grants into the mix and then divide out the number per PI. This chart will look much more skewed to the right.
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January 30, 2013 at 12:55 pm
Everybody needs to remember that IDC is based in absolutely no way on actual costs. It’s based on how well your university/institution negotiated with NHS (NIH’s parent). There are very very large IDC differences between universities.
More importantly, however, one needs to remember that IDC is not actually something NIH has control over. From discussions earlier on this blog and elsewhere, it seems that NIH could limit soft-money positions, but doesn’t want to.
Hypothetical for someone to disprove(*): Having a population of very eager, very hungry, young, naive minds trying their damndest to make major scientific breakthroughs produces the best science. (Call it the HungerGames theory.)
* I’m not saying this is moral or even correct. Personally, my best and highest-impact work has all come from flexibility and freedom when I haven’t had grant deadlines hanging over my head. But I’m personally very driven by non-monetary rewards, and am willing to do a lot for them.
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January 30, 2013 at 1:05 pm
“Having a population of very eager, very hungry, young, naive minds trying their damndest to make major scientific breakthroughs produces the best science. ”
Or the most fraud, risk-aversion, and eagerness to please old BSDs who control jobs and funding.
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January 30, 2013 at 1:09 pm
The trouble with statements like “one significant part of the swelling of mouths came from previously non-NIH-focused smaller University deans catching on to the NIH indirect cost “solution” to their local problems” is that another way of saying it is “NIH is doing it’s bit to ensure that federal funds get allocated to underserved and minority institutions” or “NIH funding should benefit all of the country and not just CA, MD, MA.”
Not that I’m not sympathetic, just pointing out that, depending on your frame of reference, things can look very different.
BTW, you should hear the howls of outrage when I suggest to colleagues who now work on the university lobbying side of things that indirect costs are out of control and need to be capped. And boy are those people good at lobbying for what they want. Honestly, I don’t see a politically realistic solution to this problem appearing until after the republic falls.
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January 30, 2013 at 1:19 pm
“one significant part of the swelling of mouths came from previously non-NIH-focused smaller University deans catching on to the NIH indirect cost “solution” to their local problems”
It’s admittedly all anecdote, but all (*) of the universities that I know of that tried to use NIH grant funding to “solve their problems” were R1 (or R0?) super-research-oriented universities that decided to metastasize their faculty numbers with soft-money positions. None of the smaller universities that I know of (**) that had not been previously sucking at the NIH trough dared bank on trying to solve funding problems with NIH dollars. With the percentiles so low, those universities figured they still don’t have a chance.
* Say 5-10 places where I have close enough friends on the inside who can complain to me about their “top-secret plans” to hire a hundred new faculty, each of whom would bring in a million dollars….
** Again, about 5-10 places where I have friends on the inside.
I know we’ve seen that the problem was an increase in applicants, not an increase in grants/applicant (an earlier RockTalk post), but has anyone seen if its an increase in institutions vs an increase in applicants/institution?
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January 30, 2013 at 2:01 pm
“What they can do is to concentrate the research dollars into fewer institutions which has a better chance of improving the output to DC+IDC ratio. ”
Why would concentrating funding reduce NIH’s leverage in negotiating the most efficient IDC ratio? Do large institutions with lots of NIH grants have lower percent indirect costs? I think you’re arguing economies of scale, but I’d want to see evidence of the economies before I relied on monopolization to decrease costs.
Yes, I agree that NIH doesn’t want to reduce soft money positions (or remove grad student funding on RO1’s); But, I think those decisions boil down to the fact that NIH nor universities have been convinced that they have a significant interest in creating a stable scientific workforce. They’ve decided the burn and churn model works for their goals. So, ignoring those options ’cause NIH won’t implement them basically means abandoning the premise that is the whole point of this discussion.
Also, do we have data on the expansion of the NIH-funded PI workforce at “marginal” research institutions? Like Qaz, I’d always assumed (and always advised grad students) that those “deanlets” were engaging in fantasies in presuming they would get NIH funds, and that in fact, few faculty at those institutions succeeded in getting NIH funding. (NSF funding seems a bit more available). In the last 20 years, have small institutions (second third tier, in flyover areas, whatever you want to call it) gotten more funding?
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January 30, 2013 at 2:20 pm
Click to access OC09049.pdf
This analysis of indirect costs says there is no correlation with nothing except if the school is public or private. They didn’t look at amount of funding, but they did check the Carnegie status and found no correlation. Caveat lector, I don’t know how reliable is the source and the data is not available, but I feel it passes the smell test. There’s also some lit review which basically says that politics is the only factor of indirect costs.
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January 30, 2013 at 2:39 pm
@Jonathan
Like this one? http://web.mit.edu/fnl/volume/205/canizares.html
“One thing to bear in mind is that, in comparison with peer institutions, MIT’s total revenues from research are a larger fraction of our on-campus annual operating budget, about 40% compared to ~30% for Stanford and UC Berkeley, and ~20% for Harvard (in 2006; excluding hospitals). The F&A recovery represents more than 10% of MIT’s campus operating budget and is nearly equal to the net revenue from undergraduate and graduate tuition combined. ”
I found a few of texts saying that F&A is currently too low in other universities, but something there doesn’t sound right for me. If extramural funded research really causes loss, then why do deans encourage it so much? I think there is some creative accounting going on in these schools. I wonder if they add all utilities and depreciation costs to the extramural research balance sheet, effectively making undergrad teaching a pure profit center.
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January 30, 2013 at 2:58 pm
So for him, larval fish are the cost/interesting sweet spot.
The real total costs of working with fish are not less than working with mice.
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January 30, 2013 at 4:06 pm
I’m at an undergraduate-focused institution that has decided that research grants will help fix our problems. If they just want a bit more slack, sure, a few grants here and then with a bit of IDC will help. If they want to fundamentally plug giant holes, that’s pure fantasy. However, we and our peers are small enough that even if we succeeded we’d still be a rounding error compared to the giant med schools.
NSF grants and other things that emphasize the educational benefits of undergrad research are bigger parts of our research portfolio than NIH, obviously. What’s interesting, though, is that most of those grants are not single-investigator grants evaluated in part on the science and in part on the likelihood of successful undergraduate involvement. They’re usually large multi-investigator “pipeline” grants, that support students working on projects in several labs. Sounds great, right? Well, the one problem is that a metric shit-tonne of money goes into people administering the program, doing assessment, etc. etc. Very little goes into supporting the people doing the research with the students. It’s very much like the med schools with their armies of deanlets sucking up IDC generated by the people running the labs.
The real money isn’t in doing the science with the students, or doing the research in the labs, it’s in being the person who dresses nice and administers programs. In that respect, undergrad institutions are remarkably similar to med schools.
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January 30, 2013 at 4:10 pm
BTW, you know what the funding agencies (NIH, NSF, and the rest) want from us? They want us to send students to PhD programs. They aren’t just funding undergrad research because they decided it’s a better way to learn science. No, they want more PhDs in the pipeline. Any undergrad who wants funding to do a summer project has to write an essay on how they want to go to a PhD program.
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January 30, 2013 at 7:52 pm
The NIH cannot control negotiated F&A rates but they can (and do) cap F&A on certain budget items as well as certain grant types. The could also cap PI salary support across the salary range (rather than just at the top), thereby requiring institutions to put some skin in the game on soft money positions.
That said, I am puzzled that DM has not addressed the elephant in the room when discussing the NIH portfolio — scientific content. I don’t recall ever discussing the categorical spending data in this forum. Surely there are some content areas that could be selectively reduced?
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January 30, 2013 at 8:54 pm
Care to elaborate?
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January 30, 2013 at 10:19 pm
Categorical spending data opens up endless vistas of easy troll-bait, e.g.:
1) Clinical vs basic
2) Disease A vs Disease B
3) Area X is just bunny-hopping
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January 31, 2013 at 5:09 am
Meh… Seems too specific for much entertainment. The basic/translational might have traction but I’m skeptical I can find anything interesting to say. I’m more or less a believer in balance and have failed to get enraged by the pendulum swinging.
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January 31, 2013 at 5:40 am
I think there is something in this. It seems to me that each ICs budget is a reflection of how many mouths there are to feed rather than the true cost of a disease to the country. One could argue easily that the NCI receives way too much money compared to ICs focusing on metabolic or neuro disorders, for example.
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January 31, 2013 at 5:40 am
Interesting discussion, but I think it’s already been made fairly clear that 1) NIH expects a Malthusian die of of labs over the next ~5 years (Jeremy Berg mentioned this more or less explicitly in an interview a few months ago), and 2) they’re going to just let the low overall paylines do the job, rather than taking a targeted approach.
Maybe a bunch of comments on Sally Rockey’s blog will change that, but I doubt it.
In any case, if it comes to targeted cuts, I think we can all agree that drug abuse research should be the first to get the axe…
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January 31, 2013 at 6:33 am
Your apathy, distressing it is.
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January 31, 2013 at 6:48 am
To be fair I completely agree with AcademicLurker. I really don’t see anything being “done” except lowering the paylines, gutting non-R01 mechanisms and letting everything else fall in to place. The strong will survive, the weak and unfunded will die unless the institutions step-up, which is about as likely as a ban on handguns in the US. The really young may be able to weather out the storm because departments may be willing to float them for a few years, but it is the mid-career Asst and Assoc. Profs who will get it up the arse the most. The middle class taking the hit. Where have I heard that before?
It may be apathy, but it’s also fucking reality DM.
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January 31, 2013 at 6:53 am
I would be careful drawing too many conclusions from the categorical spending data you get from RePORTER. Because of the way that RCDC was designed, you can’t pro-rate anything in there, so grants get double or triple counted (so instead of saying that Bob Chickenshit’s R01 or U54 is 15% translational genomics, 30% postdoc hazing etc, it counts as 100% translational genomics, 100% postdoc hazing and so on). If you were to add up all the of dollars for all of the categories you’d get a number that might be an order of magnitude larger than the actual NIH budget.
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January 31, 2013 at 7:12 am
I don’t mean to sound apathetic, but it just seems like NIH has signaled its intentions pretty clearly.
Also, the real source of the problem is at the level of institutional leadership at universities and medical schools. Various NIH spokespeople have plainly stated that NIH can’t or won’t use its control of the purse strings to force institutions to clean up their acts. Absent that kind of direct action, it seems like “Malthusian die off” becomes the inevitable strategy for dealing with the problem of too many mouths to feed.
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January 31, 2013 at 8:24 am
“At the same time, it is likely that the number of applications will decline somewhat over the five-year period if NIH appropriations do not increase as investigators dependent on extramural funding for their position are laid off or seek other positions.”
Jeremy Berg
Election of President Rubio/Paul in 2016 would also dramatically hasten the decline. I couldn’t imagine who the heads of DHHS and the NIH would be under these folks.
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January 31, 2013 at 9:36 am
Alex wrote: BTW, you know what the funding agencies (NIH, NSF, and the rest) want from us? They want us to send students to PhD programs. They aren’t just funding undergrad research because they decided it’s a better way to learn science. No, they want more PhDs in the pipeline. Any undergrad who wants funding to do a summer project has to write an essay on how they want to go to a PhD program.
Certainly in the case of the NSF and its summer undergrad programs, this is complete and utter bullshit.
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January 31, 2013 at 11:00 am
Odyssey, all I can tell you is that when my campus gets a “pipeline” grant of some sort, and says that students wanting to do summer projects can apply for funding, the application always says something about interest in grad school. When the PIs on these grants have asked me to serve on internal review committees to look at the student applications, we’ve always been asked under our evaluation criteria “Does this student want to go to grad school?”
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January 31, 2013 at 11:01 am
Oh, and I know that one guy with a “pipeline” grant that I am admittedly not a part of (i.e. I haven’t reviewed applications) has turned into a massive, massive cheerleader for grad school ever since he got funded.
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January 31, 2013 at 12:13 pm
“Certainly in the case of the NSF and its summer undergrad programs, this is complete and utter bullshit.”
Really? I don’t know NSF, but I do know that when we reviewed summer undergrad programs, we were always trying to weed out the pre-meds who just wanted the summer experience on their CVs. Now, that might have been mostly our unreasonable prejudice against pre-meds and a belief that they weren’t really going to do or learn anything in their summer program. In some cases our bias was the result of wanting more PhD applicants to the program in the future, but in many it was just a strong belief that the students who didn’t have graduate school desires just wouldn’t be as fun in the summer program and our own goals for it.
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January 31, 2013 at 1:07 pm
I’ve been running a NSF summer undergrad program for over 7 years now. The NSF is quite explicit that the purpose of these is to give research experiences to students who otherwise don’t have ready access to such. e.g. Students at 4 year colleges. We do have some bias against med students because there is an impression of CV padding. Do we explicitly look for people who want to go to grad school? No. Are many of the non-med student wannabes thinking about grad school? Yes, of course. The pool of applicants will naturally be weighted towards those thinking about a research career. Nonetheless, based on anonymous surveys taken by each group of participants we’ve had, only about 40% enter wanting to go to grad school. This increases to a staggering ~45% by the end of the summer. i.e. Statistically there is no change in numbers. If this is a way to increase the number of students going to grad school, it’s a pretty poor one. On the other hand, we have past participants who are high school science teachers, med students, pharmacy students, lab techs in industry, and even a science writer wannabe. Personally I’m quite happy to have people in those occupations who have at least some clue about research. For me, and consequently my program, it’s as much, if not more, about those than about getting students into grad school. And based on conversations I’ve had with the PI’s of other NSF summer programs, I am far from unusual.
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January 31, 2013 at 1:09 pm
It sounds like I work in an unusual environment, then, because all of my colleagues with “pipeline” research experience grants (NSF, NIH, private foundation, etc.) want to hear the applicants say that they want to go to grad school. Some of them believe, rightly or wrongly, that their grant renewal depends on it.
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January 31, 2013 at 1:41 pm
Well, looks like we’ve got all the deck chairs in place.
Bon voyage, everyone.
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January 31, 2013 at 3:00 pm
Funny you should mention the deck chairs…Jeremy Berg’s latest should interest you.
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January 31, 2013 at 5:19 pm
I agree with AcademicLurker that NIH is defaulting to a non-targeted shrinking of the workforce based on low paylines + some marginal targeted pickups.
I’m not sure which categories that method will actually end up targeting, but I’m guessing smaller mid-careersh labs with a weighting towards labs where the PI is paid mostly through federal funds. New investigators might get a little bit of a break, but I’d guess those would be the new investigator “haves” (glam pubs, big institutions, pedigrees).
I don’t particularly think explicit targeting would work much better, so am not as distressed by what I think will happen.
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January 31, 2013 at 6:04 pm
My point is that it will be random. Whomever gets caught with their pants down at the wrong time kind of thing. I agree this is what the NIH is banking on. Perhaps from their perspective they really do not care who survives, who doesn’t, who goes meteoric.
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January 31, 2013 at 8:36 pm
Shridhar, this–“One alternative that accomplishes the same goal is removing PI and grad student salaries from the F&A multiplier”–speaks to a lack of understanding of what happens in a university outside the research labs. I’ve been up close and personal in having federal grants to a biotech. That’s like one lab having to handle everything. Just administrating salaries costs a lot more money (people’s time) than keeping on the lights. You don’t want the Chief Scientific Officer of the company writing pay checks and calculating (and paying) withholding, for example. You’re going to hire a bookkeeper to do it. That biotech experience gave me a much better understanding of the nuts and bolts of what even a lean administration has to do.
I know it’s popular to trash the assistant deans of stuff, but that’s not where the bulk of overhead goes. A lot of F&A actually goes to the salaries of the people who make sure that OMB Circular A110 (or whatever) is appropriately followed, as well as all federal and state employment law. There is a cost of ownership for any federal grant because of need to fulfill federal requirements, as anyone who has had a grant outside a university can tell you, with horror stories of how their ignorance almost got them in trouble. When we calculated the small business F&A for federal grants for a start-up biotech, a significant portion of our negotiate ~60% overhead covered the personnel time needed to fulfill the federal requirements. Your OSP handles a lot of that for you. Your PI doesn’t have to write your pay check. Finance does that for her. Your PI doesn’t have to create a course in Responsible Conduct of Research, or pay a private company to do it. Your university should have/has one centrally supported. Etc. Etc.
OT to the original post, I know. Sorry DM. Someone was wrong on the internet.
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January 31, 2013 at 9:16 pm
That was pitch perfect iGrrrl. These people screeching about indirects who have never so much as sketched out a back of the envelope estimate of what the total costs of doing research are annoy me too. What they don’t grasp is that the consensus 55% overhead at most public Us is probably under the open market costs of doing research. The states are picking up some of the bill.
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January 31, 2013 at 10:13 pm
Nobody will agree on what targeting will be “fair” so I do think it will just be attrition. I think across the board attrition will probably do more damage to institutions that inflated less with the bubble, presumably because of other constraints in place. They didn’t expand as much but will contract at the same percentage. I do not think this is good for science education infrastructure, which perhaps may be negligible if the practical use for scientific training is reduced by insufficient economic support. I do think that undergraduate research (the beginning of the pipeline) does have value outside of growing Ph.Ds, if for example these students will be able to consider engineering or some other alternative, but what jobs are really available. This is an economy level problem, and really needs more money plus more proactivity with that increased money to keep the system healthy. I don’t have any answers.
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January 31, 2013 at 10:22 pm
Do you not agree that uncontrolled, random-forces attrition is likewise “unfair”, Pinko?
It just seems cowardly to say “well, doing anything would be unfair” when not doing anything leads to an equally unfair outcome…it just has the benefit of deniability.
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January 31, 2013 at 10:43 pm
heh heh, “Whomever gets caught with their grants down…”
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February 1, 2013 at 6:18 am
I wonder if NIH is in sort of the same position as the military. The strategy they pursued to protect themselves politically (dispersing funds in as many congressional districts as possible) is the very thing that makes it difficult to make big targeted cuts.
As long as they can say “Hey, we’re all about funding the best science. We just follow the study section’s lead.” they’re safe. But if they were to announce that they were deliberately cutting funds to this or that type of institution (pick your target: 3rd tier non-research heavy, big soft money based monster, whatever), you can bet that the congress critters with those institutions in their districts would have something to say about it.
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February 1, 2013 at 9:17 am
I interpreted Pinko’s comment differently. It’s not necessarily that we shouldn’t change to more targeted culling because it is unfair, it’s that we will not change to more targeted culling because we will not *agree* that it’s more fair. There’s a activation barrier to changing the method by which the culling will occur which puts a stronger requirement on the change — kind of like the radio report I just heard about the political impact of transported wolves into an environment v letting them wander in. One option requires more justification and its effects are more debated than the other.
Hey, I can go further with that analogy if we call the current culling of low paylines as wolves that wander in, while targeted culling as being wolves we bring to the study section.
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February 1, 2013 at 9:29 am
I think random attrition is unfair. I laid out a fair case that targets the bubble and gave a reason. This is antagonistic to the medical school science of the bloggers here, and more friendly to the Big State U science of someone very close to myself. Therefore I have a conflict of interest for this argument, and don’t wish to advocate for it here. I have laid out the case previously on this blog. It is something that I don’t want to argue about on the internets because I don’t see a distinction between the science that we all do. Any of us with jobs were very lucky (presumably combined with some skill) to get them. If one randomly landed at Gleaming Glass Instituted of Beautiful New NIH Bubble Doubling Presumptive Med School Cash Cow riding the wave of the bubble, it was not their fault for taking that job. Nor do I think we should destroy the functionality of undergraduate campus departments who did not have explosions in their numbers with the doubling of the NIH budget- presumably some expansion, but not unlimited. This is a problem that is unsolvable without money, but not one where money can solve everything.
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February 1, 2013 at 10:50 am
Targeting certain kinds of institutions/programs is unfair because scientists are not normally spoiled for choice about where to work and there is likely no correlation with scientific quality (though maybe there is efficiency).
Targeting certain kinds of scientists is wrong because we either cannot agree what kinds suck, or we agree that all kinds are important.
Natural culling with paylines is wrong because it privileges elite grantsmanship and NIH experience, also not scientific criteria.
We could probably agree that across all categories there is science that should not be funded, but we would never agree which science that is.
I stand by my solution that NIH should make it priority to keep funding close to the same number of scientists, but make cuts to grant sizes. DM claims this privileges research on cheaper animal systems, but I think in almost all labs the highest cost is personnel/trainees, and that’s where the cuts should land, because that’s where we have a massive surplus.
COI statement: The only job I’ve been shortlisted for is outside the NIH system. So in a year it either woudn’t affect me, or still being a trainees paid out of an R01 (something I have argued for banning) it would put me in peril.
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