This primarily I think applies to ACADEMIC science.
The funding game in academic science is kind of miserable. Researchers eager to maintain positions for their post docs and grad students etc pay high levels of attention to which way the funding story is going -> ie, telling funders what they want to hear is the key skill. This is not always focused on new ideas. That's because it is pretty horrible not to get funded, so getting funding is a top priority?
Adding to this there is a major push now on DEI and other types of policy work which are not always directly scientific idea focused. Then there are compliance costs (you need to train your researches on project costing / job codes for payroll, procurement processes with federal funds etc) and ideally get them the NIH training (see below for a reading list).
me and white supremacy: Combat Racism, Change the World, and Become a Good Ancestor, Layla F. Saad
The New Jim Crow: Mass Incarceration in the Age of Colorblindness, Michelle Alexander
United States and Racism Systemic: Explicate the systemic nature of institutionalized racism, Steven Turam
How We Fight White Supremacy: A Field Guide to Black Resistance, Akiba Solomon and Kenrya Rankin
`The funding game in academic science is kind of miserable. Researchers eager to maintain positions for their post docs and grad students etc pay high levels of attention to which way the funding story is going -> ie, telling funders what they want to hear is the key skill. This is not always focused on new ideas. That's because it is pretty horrible not to get funded, so getting funding is a top priority?`
I think this is oft, but not always, overstated (note, not the bit about the funding game being miserable - it is). I've had a relatively successful track record as new faculty, and my best scored grants are also my most daring. Significance and Innovation is one of the criteria the NIH reviews on, and funding is tight enough that a "meh" score there can torpedo a grant. Getting to know what your funder (and most importantly, your particular program officer) wants is critical, but what they want is not always "safe" science.
The advice I give my trainees is "Learn how to tell your story" and "Stop blowing off your Specific Aims page, it's the most important."
`Then there are compliance costs (you need to train your researches on project costing / job codes for payroll, procurement processes with federal funds etc)`
Almost all of this is handled by departmental staff or a sponsored programs office at every institution I've ever been at, using the indirect costs that Hacker News is always so fond of talking about.
Idk. There's a sweet spot when it comes to novelty and funding, and I'm not sure it's always where it should be. I also think there's a certain relativism about novelty, in that what is novel in a subfield might look pretty conservative to an outsider.
All these studies of grants etc are overshadowed by this problem, which is that they typically use citations etc as some kind of metric of quality. The problem with that, in turn, is that over a reasonable study span, variation in those citations is going to be driven by self-seeking behavior. That is, what's popular is what's funded, but also what's cited. There's a certain bias in it, in that you don't learn about the novel studies that never were studied due to being too novel, and the truly paradigm shifting papers, which are cited at high rates, are kinda washed out by the hundreds or thousands of papers that just kinda creep along.
It's difficult for me to put into words what's on my mind. But when I think of colleagues who are well funded, even those I consider friends and people I respect, I don't think of their work as being innovative. It's very much in the status quo. Very technically well done, but basically data generating machines within a status quo paradigm.
The things that shake things up tend to come from elsewhere, from industry or accidents or secondary reanalysis of old data, or things that get funded off of miscellaneous sources scrounged together. It's as if true innovation happens regardless of grants, or in spite of it, and after everyone agrees it's the accepted thing, then it gets funded, after the fact.
There's definitely a sweet spot, and I don't think we're near the optimum. For a lot of people, I think grants actually aren't "Fund me thinking up an innovative idea", but are taking an innovative idea that's emerged from pilot data, a side project, etc. and spending X years formalizing and solidifying it.
All good points. My own sense is that if your carry isn't too big (you are not feeling a ton of pressure to maintain a pretty big funding line) life is better all around?
My own indirect experience is not NIH, but gov lab related work. This is I think more bureaucratic because the labs have funding streams, and the key goal can be not to f it up. That might move things to a somewhat heavier compliance model.
I'm not against indirect costs rates, they are a HUGE efficiency winner to avoid needing to push paper at the individual level. That said, the system it funds is not itself that efficient.
UC Berkeley I think is going to be 60%+ indirect rate for 22-23 as a local point of reference - I don't work there though.
So if you get $400K in the door you get to "keep" $160K of it.
`All good points. My own sense is that if your carry isn't too big (you are not feeling a ton of pressure to maintain a pretty big funding line) life is better all around?`
Absolutely. The standard in my field is somewhere between a 50% and 100% soft money position. Mine is only 25%, and while I could probably fish around for a position at a more prestigious university, it's a big boost to my ability to go "Yeah, that seems neat, lets do it" and thus a major quality of life boost.
`UC Berkeley I think is going to be 60%+ indirect rate for 22-23 as a local point of reference - I don't work there though.`
This is not how you calculate indirect rates.
Indirect rates are a percentage of your direct rates. If X is the money you get for your lab (i.e. direct costs) and the indirect rate is 60%, then the actual calculation is 1.6X = 400,000, so X = $250,000.
If you want to point a finger at the thing that's probably the most harmful to the funding of science, it's not indirect rates. IMO, it's that the NIH budget cap for a modular R01 was set at $250,000 in direct costs in *1999* and has never moved from that.
25% sounds awesome - that's in cool and interesting projects range! Do you have responsibility for other positions. Not sure how it works where you are, I know someone who was very stressed because their proposals "carried" a fairly large group of folks.
Good point on indirect rates - I was being too quick there. Salary costs can be lower because you have to layer on fringe as well (which can be a separate pool or just a direct calc). So salary * 1.X (fringe) * 1.Y (indirect) = total award?
`Good point on indirect rates - I was being too quick there. Salary costs can be lower because you have to layer on fringe as well (which can be a separate pool or just a direct calc). So salary * 1.X (fringe) * 1.Y (indirect) = total award?`
Yeah, this is how that math works, at least at my institution, with some rare exceptions.
`25% sounds awesome - that's in cool and interesting projects range! Do you have responsibility for other positions. Not sure how it works where you are, I know someone who was very stressed because their proposals "carried" a fairly large group of folks.`
It really is awesome, and I'm tremendously privileged to be in that position. It's especially nice in my field (infectious disease epidemiology) because in basically all outbreaks, the work we do is uncompensated for ~ 6 months or so and then you sort of hope for grants to back fill it (I had, for example, done my best work on the pandemic prior to getting any funding for it).
You have however nailed the primary source of my stress - keeping "my" people funded. Graduate students (the downside of my position is its in a place where TA lines are functionally non-existent), postdocs, etc. are my responsibility, and keeping them funded is most of the reason I write grants.
We're experimenting for some staff positions (because 100% funding a staff scientist on grant money is daunting and terrifying for a single PI) with using a pool of funding, to address that while four of us may be able to pay 25% of a data analyst, none of us can pay 100%, with gaps in that backfilled by some institutional resources.
I'd encourage you to engage substantively in the conversation. You know almost nothing about me, and are claiming that I'm pretending. This is not substantive.
I can absolutely tell you have no point to make, and so are stuck resorting to assuming bad faith which breaks this sites guidelines and/or race baiting.
Something can be both a good thing and require work. The fact that you don't understand that is what is surprising. If you are in the intersection of academia and govt this is heightened. It's not only DEI work (which has a lot of attention now). And agreement is not universal on steps to take. The NIH has been struggling on things like going to or away from double blind methods for eval. Some have argued to reduce racism double blind is positive, others have been saying that double blind results in a racist result etc.
Work is happening in pipeline areas (dismantling racism in math instruction etc). A reminder that these govt / academic areas have all the other requirements still there, everything from guidelines on federal funding with respect to reproductive health (where the right has put in lots of restrictions and compliance efforts), funding models that complicate the process of carrying positions in various complicated ways, sweatshop compliance steps, virgin redwood compliance steps, northern ireland accord requirements and many many more.
I would really encourage you and your colleagues in this space to get a grip and fast. The arguments I'm seeing above are extremely weak. They are not even arguments, just assertions of bad faith. If you believe industry has to comply with the same rules as folks in academia receiving federal funds, fine, lay it out. I believe you are totally and completely wrong.
The biggest issue in academia is the push for the number of papers you publish. You see it especially in Machine Learning, where garbage papers are continuously released with very biased tuning to "show how we beat a superior model" along with not releasing any code to ensure that no one could refute their paper, meanwhile those junk papers are securing your tenure and giving you prestige in the industry. It's one big joke.
Yes, industry is maybe a bit more outcome oriented in these areas (outside of the snake oil ML / AI marketing and sales efforts which I find just totally ridiculous 90% of the time).
You should speak with some researchers. Entire categories are off limits because DEI politics. I could cite many examples, but one which comes to mind now is that of Noah Carl, formerly of Edmund's College, Cambridge University in England: https://www.spectator.co.uk/article/how-noah-carl-is-fightin...
He deigned to research politically contentious topics like migration and IQ. He wasn't just defunded. He was fired.
The racist overtones to Noah Carl's work certainly did his case no favours, but he was doing scholarship whose poor quality is easy to see. Before you get tenure (or the watered-down approximation that the UK has), academia offers essentially no job security: only around of 1/4 of researchers starting their first post-doc will succeed in getting a permanent academic position. I wonder what he was thinking?
Science should be immune to "overtones." Overtones are subjective and based in emotion and personal experience. I don't see any racist overtones at all.
Which work was poor quality? His work is published and peer reviewed. It should be easy to point at the work you're referring to.
He has conducted interviews about what he was thinking: he wanted to research migration and IQ, even though he received a lot of political pressure not to. He knew that this was a potential consequence, but believed that scientific and educational institutions would uphold Enlightenment ideals and allow free research. He was wrong. Politics have won in academia, and some subjects are off limits now.
This sounds nice, but given that science is done by humans, it seems entirely unrealistic to me.
If you had said: we should try to minimise the influence of this kind of politics on science, I would agree, but I rather think that is best achieved by keeping think-tank-class ideologues like Carl far away from tenure.
The tide of politics waxes and wanes in academia. Your whitewashing of Carl's record does not help reduce the role of politics in academia.
> Which work was poor quality?
Carl was spending his time publishing in a 'journal' that was published by a friend that had essentially no quality controls, where the content contained provocative racist claims not backed up by argument or evidence instead of doing the hard work of quality scholarship.
His work is published and peer reviewed. Which work was "pseudoscience"? I think you're only making that accusation because it's vague and sounds authoritative, but you don't have any examples.
The funding game is a miserable slog, but people are in academia because they want to do their research. If they wanted to use their expertise to obtain a paycheck, there are typically much better opportunities to do so.
> but people are in academia because they want to do their research
Which is perfectly fine as long as those people don't go asking the NSF or NIH for money to fund students.
I'll never understand why we give egomaniacs funding for phd students, and it's something I actively work to get the panel to select against when evaluating any proposal that includes lines for PhD students or post-docs (ie all of them).
CS profs: if you want employees for your ego trip, start a damn company. Your students are not employees, and if we're all honest, most of the benefit of the grant we're giving you will be the students it produces. So sayth this regular panel member.
While I would agree that DEI isn't directly about science, it certainly helps the end goal of understanding some phenomenon as holistically possible.
I think these sorts of policies are aimed more towards administrators rather than researchers, which for some reason are often the same people.
I think academia could benefit from adopting the music industry's approach to managing talent - i.e. the managing and talent are usually kept separate.
Don't like being made aware of your compliance in racist institutions? Want to just do your "science" as people outside the institutions are subject to mass incarceration?
Yes, my own sense is that it starts in govt / academia and does tend to filter out to industry in some form usually after some of the specifics get worked out a bit more. And don't worry, in places like California where there are still required harassment trainings (every 2 years) there are still complaints! I enforce some of these requirements.
The funding game in academic science is kind of miserable. Researchers eager to maintain positions for their post docs and grad students etc pay high levels of attention to which way the funding story is going -> ie, telling funders what they want to hear is the key skill. This is not always focused on new ideas. That's because it is pretty horrible not to get funded, so getting funding is a top priority?
Adding to this there is a major push now on DEI and other types of policy work which are not always directly scientific idea focused. Then there are compliance costs (you need to train your researches on project costing / job codes for payroll, procurement processes with federal funds etc) and ideally get them the NIH training (see below for a reading list).
https://www.training.nih.gov/2020_inclusion_anti-racism_and_...So you have a lot on your plate - not that this is a bad thing, but just to be aware of it.