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> Evaluating the quality of studies/experiments That's part of the problem. Publications are seen as achievements. If you got accepted to a prestigious journal

> Evaluating the quality of studies/experiments That's part of the problem. Publications are seen as achievements. If you got accepted to a prestigious journal or conference, you can list this on your CV as an impressive "award"-like thing. A publication list is not just a list of "Look, this is the kind of stuff I've been working on, have a great read at it", but "Look, my research is so great it got accepted to all these fancy places!". Publications are therefore unfortunately not merely about sharing new info with the research community but an award show. Ideally a publication would be the start of the conversation: "this is what we found, this is the method we propose, what do you think of it, community? Will you pick it up?" The test is then whether the ideas get adopted. But that's harder to measure. Citations try to approximate it, but it's a very crude approximation. A citation, as such, may mean tons of different things: e.g. a) a deep critique (Negative impact) b) being cited as part of a long block of "these other works exist, too" (Low impact) c) another work substantially based on the deep ideas of the original paper (High impact), d) being listed in a table for comparison, ala "we beat this other method", but no other discussion of the original paper (Low impact), etc. If a publication was nothing more than a "hey, look, this is interesting", then I'd say, publishing mostly novel sexy results would be fine! After all, the surprising cases are those that teach us the most. However, as I said earlier, a paper is not only about "hey, this is interesting", but a "hey I want to advance my career", too. And in a twisted way of logic, I can agree that therefore we could put a band-aid over some of the problem by publishing (rewarding) systematic work with negative or boring results. But ultimately, this goes against the original purpose of papers, that is alerting the scientific community to potentially new information that we haven't known about before. ---- Ideally, to assess someone's scientific career, there would be at least one smart, attentive, impartial expert taking their time reading through the publications, taking notes, pondering, digesting it all, consulting other experts etc. However, this is too subjective. Quantitative metrics seem superficially more objective and therefore egalitarian. The original idea is probably that if we just based everything on subjective judgement of scientific importance instead of publication count, there would be even more networking and friendship-based quid-pro-quo back scratching. But everyone is overworked, and those who aren't, want to keep it that way. So nobody wants to put in the effort to actually interact with the deep content of research. It's too complicated and too opaque. ---- The problem is, flashy results are by their nature more attention-grabbing on all levels. It's not just some small perverse incentive. This is how all of us work, this is how history works, how everything works. The winner takes all, the rich get richer etc. We remember the Einsteins of history, those who just worked systematically and didn't find much aren't heroes. And if that's our bar, then people will do everything to look like they clear it. In any system, scientists would have to hype up their impact, it doesn't matter who makes the decisions. Currently, universities want to employ researchers who will make a visible impact. Because that means attracting funding, but also attracting bright people from all around. Career-conscious researchers want to go to universities that help them market themselves well (good PR departments etc). PR is not only for laypeople as the audience, there is such a flood of research nowadays that even the experts of a small niche cannot keep up with everything happening. ---- The root of it is human nature, competition, deception, cliques, hierarchies. But the new about it is the scale of it, and the accompanying mechanization of it all. The idea that you can mass-manufacture innovation. That you can expect thousands upon thousands of researchers to make regular breakthroughs and, to say my field as an example, publish tens of thousands of novel AI-related ideas every year. It's related to credential inflation, and fake signaling: people with good academic track records got the good jobs and the respect, so people try to emulate that. Everyone tries to become the 1%, the rock star. And everyone wants to hire the 1%. So just like an evolutionary pressure, people try to appear like the successful. Soon enough the old signal doesn't work anymore. It used to be a high mark of educational level to have passed high school. Today that's a bare minimum. College used to be a meaningful differentiator. Now more than half of young people are "college educated" in developed countries. The next step is about becoming "researchers". Nowadays, having some publications is not a big differentiator. We see this also in title inflation like monkeying around in Excel is "data science" and "AI". It's not just a monkey's paw. There is no central figure orchestrating it, asking the monkey's paw for more papers. It's a distributed system of agents acting in their self-interest. Nobody wants papers for papers' sake, they want to make defensible, justifiable decisions that will not get them fired and will pass satisfaction up opposite the path where the money is flowing, all the way to the CEOs, politicians and taxpayers.

marcus_holmes 6y ago
Would open publishing on the web solve this? After all, the journal system was invented to solve distribution of papers. We have the internet now, so is there any need for the journal system any more? Independent reviewers would/could easily step up to pick up the interesting papers and present a "feed" of the good stuff.
- bonoboTP 6y ago
  First we need to understand what we want to solve. The attention economy and PR war goes on just as much on the open internet. E.g. people only reading papers from big shots, MIT, Stanford, Harvard labs etc. The problem is way deeper than just academia. Such as, is there fairness in the world deep down, is mass-produced excellence possible? Does individual greatness actually exist or is it all just a power play? Overall, the quality of science is extremely difficult to measure, precisely because it operates on the border of the unknown and because people try their best to appear the best possible. Science is difficult to understand and is often far removed from the here and now, and may only bear fruit decades down the line. It's hard to judge for the same reason that antelopes are hard to catch for cheetahs: competition (mainly the antelope vs antelope type). In the end, science has only been this mass product for a few decades. Before that it was mostly a pastime of weird nerdy aristocrats or people paid by aristocrats for showoff purposes. Or church people with too much time on their hands. In reality, from the top down view it's a huge gamble. You try to get good people to do their honest best and then see what happens. Then at the end there will be some breakthroughs. But only a few every few years in each field. However, this does not satisfy the participants. I toiled away as well, but the reward is only paid to the lucky one. So everyone tries to be the lucky one, which perversely pushes everyone to take fewer risks, making the collective likelihood of a breakthrough lower, but their own expected reward better. ----- My grandfather used to recite the story of a farmer who had three pigs. Every morning he'd throw two apples in their confinement. He'd then grab a big stick and beat the one that didn't get any apple: why didn't it try harder? ----- My prediction is that as with all signaling spirals and treadmill effects, there will be something new to aspire to, to tell the wheat from the chaff, a signal that's harder to fake. It's a constant race. You demonstrate your fitness by being adaptive to how the system changes. Overall the "quality" of people obviously doesn't change over time, it's just that the competent/powerful drive the criteria to their benefit. As academia/publishing etc. is now flooded with "the plebs", "the elite" will move on and will perhaps use other criteria. ---- Now, going back to assuming this is about the object-level science itself. Where to find the best science? You cannot do this in general. You have to educate yourself and dive in yourself. You try to learn how to judge people's character and try to listen to and digest the assessment of those you trust. There's no other way, gather experience and become "better" yourself. Use the cognitive resources of your brain to try and outsmart your opponent: the writer of the piece of text you are reading. This cannot be standardized/metrificated in a simple way (outside human-level AGI). If your organization does not put in the cognitive power of extensively processing the content of a particular research and critically examining the motivations behind it etc., there is no way to judge it. Then you're back to credentials. Did it come from a highly cited person? Is this person endorsed by other big shots, where the "seed big shots" are the researchers at the historically most prestigious institutions. ---- Currently, to find interesting research I personally use Github recommendations, Google Scholar alerts watching for citations of landmark papers (good indicators for progress in niches) and authors. A well-curated Twitter-feed is also useful, as is arxiv-sanity. In the end, I have to make up my mind if it's good work or not, and as everyone I don't have infinite cognitive resources. So I make snap judgements based on paper gestalt, affiliations, plausibility, result tables, etc. If it clears this bar, I dive in more. Over time, you learn to trust some smart people and can follow them online and see what they say and recommend. And continuously learn and grind your brain. Cognitive work cannot be spared, just like you cannot spare physical exhaustion in sport competitions.

marcus_holmes 6y ago

Would open publishing on the web solve this? After all, the journal system was invented to solve distribution of papers. We have the internet now, so is there any need for the journal system any more? Independent reviewers would/could easily step up to pick up the interesting papers and present a "feed" of the good stuff.

bonoboTP 6y ago
First we need to understand what we want to solve. The attention economy and PR war goes on just as much on the open internet. E.g. people only reading papers from big shots, MIT, Stanford, Harvard labs etc. The problem is way deeper than just academia. Such as, is there fairness in the world deep down, is mass-produced excellence possible? Does individual greatness actually exist or is it all just a power play? Overall, the quality of science is extremely difficult to measure, precisely because it operates on the border of the unknown and because people try their best to appear the best possible. Science is difficult to understand and is often far removed from the here and now, and may only bear fruit decades down the line. It's hard to judge for the same reason that antelopes are hard to catch for cheetahs: competition (mainly the antelope vs antelope type). In the end, science has only been this mass product for a few decades. Before that it was mostly a pastime of weird nerdy aristocrats or people paid by aristocrats for showoff purposes. Or church people with too much time on their hands. In reality, from the top down view it's a huge gamble. You try to get good people to do their honest best and then see what happens. Then at the end there will be some breakthroughs. But only a few every few years in each field. However, this does not satisfy the participants. I toiled away as well, but the reward is only paid to the lucky one. So everyone tries to be the lucky one, which perversely pushes everyone to take fewer risks, making the collective likelihood of a breakthrough lower, but their own expected reward better. ----- My grandfather used to recite the story of a farmer who had three pigs. Every morning he'd throw two apples in their confinement. He'd then grab a big stick and beat the one that didn't get any apple: why didn't it try harder? ----- My prediction is that as with all signaling spirals and treadmill effects, there will be something new to aspire to, to tell the wheat from the chaff, a signal that's harder to fake. It's a constant race. You demonstrate your fitness by being adaptive to how the system changes. Overall the "quality" of people obviously doesn't change over time, it's just that the competent/powerful drive the criteria to their benefit. As academia/publishing etc. is now flooded with "the plebs", "the elite" will move on and will perhaps use other criteria. ---- Now, going back to assuming this is about the object-level science itself. Where to find the best science? You cannot do this in general. You have to educate yourself and dive in yourself. You try to learn how to judge people's character and try to listen to and digest the assessment of those you trust. There's no other way, gather experience and become "better" yourself. Use the cognitive resources of your brain to try and outsmart your opponent: the writer of the piece of text you are reading. This cannot be standardized/metrificated in a simple way (outside human-level AGI). If your organization does not put in the cognitive power of extensively processing the content of a particular research and critically examining the motivations behind it etc., there is no way to judge it. Then you're back to credentials. Did it come from a highly cited person? Is this person endorsed by other big shots, where the "seed big shots" are the researchers at the historically most prestigious institutions. ---- Currently, to find interesting research I personally use Github recommendations, Google Scholar alerts watching for citations of landmark papers (good indicators for progress in niches) and authors. A well-curated Twitter-feed is also useful, as is arxiv-sanity. In the end, I have to make up my mind if it's good work or not, and as everyone I don't have infinite cognitive resources. So I make snap judgements based on paper gestalt, affiliations, plausibility, result tables, etc. If it clears this bar, I dive in more. Over time, you learn to trust some smart people and can follow them online and see what they say and recommend. And continuously learn and grind your brain. Cognitive work cannot be spared, just like you cannot spare physical exhaustion in sport competitions.