Comment by moduspol
3 hours ago
The number seems arbitrary. Maybe we should be subsidizing until we have 100,000 more.
I'm always skeptical when something is presumed to be a universal good in a way that's unfalsifiable. What metrics would you expect to see if we had too many STEM PhDs? What metrics can we expect to improve if we had more of them?
I think your comment is more a refutation of the top level than the person you're responding to. I think people are right to assume there is already a serious throughput issue with scientific research, especially so-called "basic" research in the US and seeing a mass exodus from the government is troubling because public funding is what, historically, generates the big breakthroughs.
What the person you're replying to was likely trying to say is that once you get into this size of layoffs its no longer about the individuals and their performances and a claim that all 10k of them are on one side of a theoretical "bell curve" (which btw i havent seen evidence can actually be measured) is big and needs evidence.
> public funding is what, historically, generates the big breakthroughs
Without an opinion on the rest of this, public funding in the US doesn't produce big breakthroughs from scientists employed by the government, but rather by funding university research.
It appears that, after the administration canceling a significant proportion of grants in 2025, that science funding has largely been maintained or increased from pre-2025 levels for 2026, although how the 2026 funding gets spent, and whether it is all spent, is an open question.
It’s a separate question not arbitrary. How many PHD’s the government should employ is debatable, but saying we should have fewer such people says nothing about who was let go.
It’s always tempting to say ‘This was a good decision therefore all the consequences are good’ but in the real world good and bad decisions will have both positive and negative consequences. Understanding individual consequences is therefore largely separated from the overall question of should we do X. However in politics nobody wants to admit any issues with what they did so they try and smokescreen secondary effects as universally beneficial/harmful.
One metric you could use is how often publications are mentioned by patents, and how often those patents lead to economic value. By this metric, it is valuable.
The number of PhDs we have is currently too many given the amount of money we have for project grants. But there is no evidence that the money we allocate to research is too large. If anything, you could argue the opposite.
I would be delighted if the private market funded basic research - the seed ideas that lead to patents.
You’re confusing two different questions. ‘Should we have more STEM PhDs in government?’ is a reasonable policy debate. ‘Is losing 10,000 STEM PhDs in weeks a problem?’ has a clearer answer… yes, because institutional knowledge doesn’t rebuild quickly. Also, there’s no evidence this was performance-based attrition. Lastly, recruitment becomes harder after mass departures signal instability.
The burden isn’t on critics to prove some theoretical optimal number. The burden is on defenders of this exodus to show it improved government technical capacity rather than hurt it.
I disagree--we're all paying for it, so it should be justified regardless.
And I don't need an optimal number. But the common refrain is essentially that more is always better, and fewer means we're losing our standing in the world. Always.
Maybe keeping a lot of them but shedding some percentage is actually more optimal. But I'm open to being wrong. That's why I'm asking for metrics.
The US government operates with such a huge debt that we aren’t paying for these things. Instead we are paying for the long term effects of such spending.
Cutting 10k scientists could therefore result in increased taxes without anyone ever seeing any savings. Or it could result in net gain from 1$ all the way up to what their cost * interest in the debt.
Therefore there’s no obvious side who takes the default win here. Instead you need actual well supported arguments.
If this was intentional workforce reduction, then the agencies affected should show improved efficiency or output with fewer people. We should see faster regulatory reviews, better grant decisions, stronger technical evaluations, just with leaner teams.
Instead, what we’re likely to see is degraded capacity, slower timelines, and reduced technical oversight. If that happens, will you acknowledge this was a mistake? Or will any negative outcome just get blamed on the remaining employees?