@albertcardona I think the part "it was pretty much a given if you were doing good work." is the most important in that.

Don’t constantly stress people about their employment future while they are working for you. That stress steals focus from the work they are doing that actually benefits society.

@bitbraindev @alexh

@foaylward There’s some background from concept discussed in the book Thinking Fast and Slow:

Since you often only know years (decades) later whether some research was important, building intuition can’t work and creating metrics that quantify that is a fools errant.

But people try anyway. It looks a lot like superstition caused by a need to have certainty.

Either an emotional need or as a cover-my-ass method in case something doesn’t work out.

@bitbraindev @albertcardona @alexh

@ArneBab @foaylward @bitbraindev @albertcardona Does it really take decades to know though? This feels like one of those things people say, like “protein has to be the genetic material because nucleic acid is too simple” or “bacteria don’t have genes”.

Where is the systematic evidence (not anecdata) that this is true?

@kristine_willis If you want to check that, the easiest sanity check could be to investigate when the science that led to Nobel prizes later on was recognized as groundbreaking.

The next step could be to check which requirements these had to be possible and how long it took for those requirements to be recognized as important (time after publication).

@foaylward @bitbraindev @albertcardona @alexh

@ArneBab could not agree more, this is an obvious test. But, we have to define "recognition".

I suspect that the immediate field recognizes breakthroughs much more rapidly than the broader scientific community, and I would hypothesize that perhaps the lag time between recognition by practitioners of a sub-specialty and recognition by the scientific community in general is what give the appearance of a long delay.

@foaylward @bitbraindev @albertcardona @alexh

@ArneBab The sleeping beauty phenomenon you're describing in comp sci fits a different pattern where neighboring practitioners don't recognize the immediate utility (and maybe they never do, it's some other community that finds the utility). But this just means, I think, there can be delays, not that the delay in recognition is obligatory.

@foaylward @bitbraindev @albertcardona @alexh

@ArneBab We may be violently agreeing here. But I seem to hear the "you can never know" line rolled out as a kind of bromide to provide cover to funding work that, as a subject matter expert, I'm pretty sure is a dead letter.

Of course I could be wrong. Sure. Absolutely. The problem is, our resources are finite, and I wonder to what extent this paradigm is undermining progress by contributing to problematic hyper competition. @foaylward @bitbraindev @albertcardona @alexh

@kristine_willis @ArneBab @foaylward @bitbraindev
A key point here is that in scientific research competition is counterproductive. That no scientist in their right mind would want to compete with anyone. And if a work is so obvious that multiple labs are on it, collaboration beats competition any day. There's no point in being a month faster and scooping someone; even the concept of scooping is absurd: if anything, that'd be confirmation, validation – and very valuable. Most, though, would rather work on questions whose answers push the horizon of knowledge.

Resources are indeed finite, hence let's stop competition for papers, for grants, for positions. There is no point in that. Define what size of scientific research sector can the country support and go with that, with properly funded labs.

#academia #ScientificPublishing

@albertcardona I see two different aspects:

One is that funding is provided by people outside the field, and they want proof of value. But they don’t want to trust the people within the field ("they all know each other, so how can they be objective?"). So they request something impossible.

The second is that abuse of funds absolutely does happen, and bad theories often only die with their generation. So there *is* need for funding of outsiders.

@kristine_willis @foaylward @bitbraindev @alexh

@albertcardona The current solution is to make the most accomplished scientists waste at least a third of their time writing grants just so people they know are doing good work have a chance to continue their work.

And the missing job security kills a lot of good work because people are on the edge instead of focusing on their passion.

So the current situation is just bad.

The only ones who benefit are administrations who can point to metrics.

@kristine_willis @foaylward @bitbraindev @alexh

@albertcardona "We did not choose wrong: here are the numbers to prove that our selection is the only correct one, so if it does not work out, we are not responsible."

@kristine_willis @foaylward @bitbraindev @alexh

@kristine_willis @ArneBab @foaylward @bitbraindev
Indeed, the evaluation problem is a tough one. Two points.

1. Outsider perspectives are always needed. Hence I'd value most an evaluation committee composed on 1/3 internal, 1/3 national, 1/3 international. The result should be biased towards not squashing potentially great people or projects, at the cost of letting some less good ones continue. While the cost of an error in the latter is small, the cost on the former is gigantic.

2. Since it's impossible to be perfect, I'd use, again the Ross Cagan proposal of funding levels: go up, go down, and so on, depending on past performance, not future perspectives. In other words, no grants: the evaluation is done on past work only.

#academia

@druedin @kristine_willis @ArneBab @foaylward @bitbraindev
Same as now: who is interested, who did a sensible internship or rotation, who do you happen to know, who has sensible grades on relevant subjects, who can come up with a project proposal that reads sensible. Plus the equivalent of a visitor project for juniors: short-term positions of 3 months to a year where they can prove themselves. Actual work in a lab is the best recruitment basis there is.

Frankly, my problem is finding people who want to work in academic scientific research. There aren't enough. And the issue isn't entirely salaries, which is a major one. It's also that not everybody is comfortably being wrong all day long, all year wrong, not knowing exactly how to do something, not knowing what the outcome may be. Perhaps this can be learned, but at the PhD/postdoc level it may be too late.

#academia