And morality and their conscientiousness (what a word).
If you look at the map of Europe, lay it over with that fiscal discipline and above, there is no mystery how things like income are spread out across the map, it all makes sense. Also a good confirmation that well regulated but proper capitalism is the easiest path for any country to long term prosperity.
Nowadays high citation numbers don't mean anymore what they used to. I've seen too many highly cited papers with issues that keep getting referenced, probably because people don't really read the sources anymore and just copy-paste the citations.
On my side-project todo list, I have an idea for a scientific service that overlays a "trust" network over the citation graph. Papers that uncritically cite other work that contains well-known issues should get tagged as "potentially tainted". Authors and institutions that accumulate too many of such sketchy works should be labeled equally. Over time this would provide an additional useful signal vs. just raw citation numbers. You could also look for citation rings and tag them. I think that could be quite useful but requires a bit of work.
I explored this question a bit a few years ago when GPT-3 was brand new. It's tempting to look for technological solutions to social problems. It was COVID so public health papers were the focus.
The idea failed a simple sanity check: just going to Google Scholar, doing a generic search and reading randomly selected papers from within the past 15 years or so. It turned out most of them were bogus in some obvious way. A lot of ideas for science reform take as axiomatic that the bad stuff is rare and just needs to be filtered out. Once you engage with some field's literatures in a systematic way, it becomes clear that it's more like searching for diamonds in the rough than filtering out occasional corruption.
But at that point you wonder, why bother? There is no alchemical algorithm that can convert intellectual lead into gold. If a field is 90% bogus then it just shouldn't be engaged with at all.
There is in fact a method, and it got us quite far until we abandoned it for the peer review plus publish or perish death spiral in the mid 1900s. It's quite simple:
1) Anyone publishes anything they want, whenever they want, as much or as little as the want. Publishing does not say anything about your quality as a researcher, since anyone can do it.
2) Being published doesn't mean it's right, or even credible. No one is filtering the stream, so there's no cachet to being published.
We then let memetic evolution run its course. This is the system that got us Newton, Einstein, Darwin, Mendeleev, Euler, etc. It works, but it's slow, sometimes ugly to watch, and hard to game so some people would much rather use the "Approved by A Council of Peers" nonsense we're presently mired in.
Yeah, the gatekeepers just want their political power, and that's it. Also, education/academia is a big industry nowadays; it feeds many people who have a big incentive to perpetuate the broken system.
We are just back to the universities under the religious control system that we had before the Enlightenment. Any change would require separating academia from political government power.
Academia is just the propaganda machine for the government, just like the church was the tool for justifying god-gifted powers to kings.
Interesting idea. How do you distinguish between critical and uncritical citation? It’s also a little thorny—if your related work section is just describing published work (which is a common form of reviewer-proofing), is that a critical or uncritical citation? It seems a little harsh to ding a paper for that.
That's one of the issues that causes a bit of work.
Citations would need to be judged with context. Let's say paper X is nowadays known to be tainted. If a tainted work is cited just for completeness, it's not an issue, e.g. "the method has been used in [a,b,c,d,x]"
If the tainted work is cited critically, even better: e.g. "X claimed to show that..., but y and z could not replicate the results".
But if it is just taken for granted at face value, then the taint-label should propagate: e.g. ".. has been previously proved by x and thus our results are very important...".
Going to conferences seeing researchers who've built a career doing subpar (sometimes blatantly 'fake') work has made me grow increasingly wary of experts. Worst is lots of people just seem to go along with it.
Still I'm skeptical about any sort of system trying to figure out 'trust'. There's too much on the line for researchers/students/... to the point where anything will eventually be gamed. Just too many people trying to get into the system (and getting in is the most important part).
The worse system is already getting gamed. There's already too much on the line for researchers/students, so they don't admit any wrong doing or retract anything. What's the worse that could happen by adding a layer of trust in the h-index ?
I think it could end up helping a bit in the short term. But in the end an even more complicated system (even if in principle better) will reward those spending time gaming it even more.
The system ends up promoting an even more conservative culture. What might start great will end up with groups and institutions being even more protective of 'their truths' to avoid getting tainted.
Don't think there's any system which can avoid these sort of things, people were talking about this before WW1, globalisation just put it in overdrive.
>people don't really read the sources anymore and just copy-paste the citations.
That's reference-stealing, some other paper I read cited this so it should be OK, I'll steal their reference. I always make sure I read the cited paper before citing it myself, it's scary how often it says something rather different to what the citation implies. That's not necessarily bad research, more that the author of the citing paper was looking for effect A in the cited reference and I'm looking for effect B, so their reason for citing differs from mine, and it's a valid reference in their paper but wouldn't be in mine.
> There is going to be a lot of debate over whether this specific operation was legal
There might be a local debate about the legality in the US. But from the outside perspective in terms of international law, there is not much to debate. Unless i missed some UN resolution, the US has no jurisdiction in Venezuela.
I have a hypothesis that we're getting closer to a cultural inflection point (maybe half a decade out). With every year, more important and very high-quality cultural artifacts enter the public domain, while at the same time, many low quality artefacts are produced (... AI slop). It'll be increasingly difficult to choose a good cultural artefict for consumption (e.g., which book to read next or which movie to watch). A very good indicator for quality is time and thus a useful filter.
In some years we could have the following: a netflix-like (legal variant of popcorntime) software system (p2p) that serves high-quality public domain movies, for those who like it, even with AI upscaling or post processing.
The same would also work for books, with this pipeline: Project Gutenberg -> Standard Ebooks. At the inflection point, there would be a steady stream of high-quality formats of high-quality content, enough to satisfy the demand of cultural consumption. You wouldn't need the latest book/movie anymore, except for interest in contemporary stuff.
The incentives are alright. Publishers who now start publishing too much low quality slop will lose readers (who has time to read all those low quality publications). Less readers leads to less citations, which will drag dawn their impact factor resulting in less authors willing to pay a high publication fee.
For those fields with an existing market, meaning there is more than one high quality journal, the market will provide the right incentives for those publishers.
I doubt that this is true except maybe for the top journals. Mid and low tier journals cater to scientists whose main incentive is to publish no matter how while moderately optimizing for impact factor (i.e. readers and citations). This lower quality market is huge. The fact that even top tier publishers have created low-ranking journals that address this market segment using APC-based open-access models shows the alignment between publisher and author interests will not necessarily lead to increasing quality, rather the opposite.
Does anyone actually read articles from those low tier journals? Many of those articles are illegible fluff pieces.
That top tier publishers create new low-tier journals for this market shows that they are very well aware of these incentives and risks. They are not flooding their top journals with low quality OA "pay to publish" articles, which was the argument from OP.
For academia's sake I hope you are correct, but my experience of the system leads me to suspect otherwise, though only time will tell.
One hope might be that it incentivises institutions away from the publish or perish mind set and starts to discourage salami slicing and other such practices, allowing researchers to focus on putting out less work of a higher quality, but I suspect the fees would need to be larger to start seeing this sort of change.
Calling a system that is 90% foss and public domain "owned" by anyone is a bit of a stretch. I can, fully legally, download all the text of Wikipedia for about 130gb and host it myself.
Besides, Jimmy Wales is awesome.
It's an oligarchy in reality and Wikimedia was having a discussion a couple of years ago about implementing the SDGs, which come from the UN and not the public (who are barely aware of them.)
It really depends on what exactly you want to bet on and on what timeframe. More short term bet? Puts on the AI companies or an AI ETF. Do you assume that the rest of tech stays up even if AI pops? Then you could short some AI ETF and hedge with long QQQ. (=betting that the AI subset of Nasdaq will underperform relative to the Nasdaq.
That would be a highly bureaucratic solution with significant overheads.
Would everyone pay extra tax per kWh or just AI computers? Tax it on the producer or consumer side?
How would you verify that a particular data center is "bad computation" and needs a different tax rate on its energy usage.
Should an AI data center from pharmaceuticals or biotech startup be taxed extra per kWh, even if the AI is purely used for medical research?
Just big AI datacenters. If this encourages people to run local AI, all the better.
> Should an AI data center from pharmaceuticals or biotech startup be taxed extra per kWh, even if the AI is purely used for medical research?
That's not a gotcha.. those are all policy choices. My personal preference is, yes, of course - medical research today is taxed just fine. If there's lobbying to specifically grant tax benefits to medical research, I can see an exception being carved.
You think multiple localised heat centres are more efficient than centralised managed heat centres. Why don't we all just have a coal-fired power station in our back garden?
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