The article claims the solution is "every government grant should stipulate that the research it supports can’t be published in a for-profit journal. That’s it! If the public paid for it, it shouldn’t be paywalled." That's an equivocation fallacy. Whether a for-profit journal publishes the work at some point is orthogonal to whether it is available un-paywalled, which it now must be.

You say that publishers replaced subscription fees with APC charges, but I haven't seen this happening when I've submitted papers recently. Journals need new submissions or they lose mindshare. Authors are price-sensitive and will shop around. Starting a new journal isn't that hard (it can been done as a side project) so high margins will likely be undercut. I have no idea why the author chose to pay a $12k APC; they probably didn't need to. Finally, closed-access journals will have residual subscription income from their closed-access archives for many decades; if the author wants to kill that income stream off, their proposed solution will not do it. So while I agree with the article's condemnation of the publishers, who are certainly no friends of science, I think it's wildly off-base on pretty much every other point.

Author-pays APCs are even potentially a good thing as long as they aren't much higher than the cost of publication. Universal APCs would provide some pressure against publishing many low-value papers that aren't really worth the time it takes to read them. The paper spam is kind of getting out of control.

Edit: OA advocates have won pretty much everything we wanted, there's not much left to be outraged over.

It's just that when the function is implemented on the computer, evaluating so many points takes a long time, and using a more sophisticated optimization algorithm that exploits information like the gradient is almost always faster. In physical reality all the points already exist, so if they can be observed cheaply the brute force approach works well.

Edit: Your question was good. Asking superficially-naive questions like that is often a fruitful starting point for coming up with new tricks to solve seemingly-intractable problems.

> Discussions with different stakeholders suggest that many currently perceive systematic fraudulent science as something that occurs only in the periphery of the “real” scientific enterprise, that is, outside OECD countries. Accumulating evidence shows that systematic production of low quality and fraudulent science can occur anywhere.

From supplement (section about the output of the "ARDA" paper mill):

> We obtained 20,638 documents and were able to impute country of authorship for 13,288 documents (64.4%). Of these documents, more than half were solely from India (26.4%), Iraq (19.3%), or Indonesia (12.2%).

The identity and reputation of the authors, and the publication venue, is (for now) still a strong signal when evaluating the credibility of an article.

The article is spot-on though in that there is a real risk of paper mills infecting formerly reliable journals, and this is not helped by the publishers' commercialism. For example, it used to be easy to ignore Hindawi journals (they are characteristically low quality); then Wiley started publishing them under its own brand. The good is now mixed with the bad under the same label. Practicing scientists can fall back on whether they know the authors personally but that doesn't really help non-practicing professionals or the general public.

It seems messy. Just one example that I remember because it was on HN before: https://www.hillelwayne.com/post/this-is-how-science-happens...

https://par.nsf.gov/

https://pmc.ncbi.nlm.nih.gov/

https://ospo.gwu.edu/overview-us-policy-open-access-and-open...

https://www.nih.gov/about-nih/who-we-are/nih-director/statem...

https://www.coalition-s.org/plan_s_principles/

The intent of the Bayh-Dole Act was to deal with a perceived problem of government-owned patents being investor-unfriendly. At the time the government would only grant non-exclusive licenses, and investors generally want exclusivity. That may have been the actual problem, moreso than who owned the patent. On the other hand, giving the actual inventors an incentive to commercialize their work should increase their productivity and the chance that the inventions actually get used.

The provided examples do not clearly support the idea that industry can compensate for a decrease in government-funded basic research. Bell Labs was the product of government action (antitrust enforcement), not a voluntary creation. The others are R&D (product development) organizations, not research organizations. Of those listed, Xerox PARC is the most significant, but from the profit-seeking perspective it's more of a cautionary tale since it primarily benefited Xerox's competitors. And Hinton seems to have received government support; his backpropagation paper at least credits ONR. As I understand it, the overall deep learning story is that basic research, including government-funded research, laid theoretical groundwork that capital investment was later able to scale commercially once video games drove development of the necessary hardware.

Edit: There's no guarantee this will work out positively—nothing is guaranteed—but it's worth considering if the alternative is giving up / changing careers.

As someone who has tried something similar, institutional bureaucracy expands to fill all available time. People engaging in bureaucratic empire-building will still happily consume your personal unpaid time. And splitting attention between multiple lines of work creates some legitimate additional overhead, which doesn't help.

I'm not sure what the winning strategy is. I think it is necessary to either get out entirely or play the bureaucrats' "system-game" to some degree, but not on their terms and not fairly. When the bureaucracy demands useless work, maximize their costs and minimize yours. Many academics constitutively cannot make themselves do a lazy, poor job, but is a useful skill to deploy defensively so that you can fulfill your education and research responsibilities. Often you'll find that the bureaucracy only cares about the superficial appearance of compliance; the actual actions performed are irrelevant to them. Shift responsibility to some other part of the bureaucracy and use LLMs to generate boilerplate. If the bureaucracy never attempts to punish you in any way, that may indicate you're being more compliant than necessary. This approach is safest if your retirement plan is fully funded and you don't truly need to keep the job. It is also helpful if at some part of what you do is visibly important to someone who does have power; this helps deflect consequences when you accidentally step a over a line. Everything depends on context and execution though; I hope the part-time approach works out for you.

MDPI also spams anyone it thinks might be willing to submit a paper or serve as an editor, and does not seem to care much about the quality of the submissions it receives.

The most important thing from the perspective of replication of a DNA strand is the number of copies of DNA passed to the next generation, and future generations, right? Which would be 0.75 * (mean marginal increase in next-generation sisters) + 0.5 * (mean # offspring). The probability that these next-generation individuals actually get to reproduce in turn would also factor in somewhere.

What's also interesting is that if we take the point of view of the queen (through whom the altruistic genes must pass), the queen's reproductive strategy is relatively few children + hordes of sterile helpers + killing her own sisters. So are we talking about a fitness advantage of altruistic traits (maximizing # sisters), or a fitness advantage from selfish traits [maximizing P(fertile child survival) I guess, since # children is small] that produce hordes of sterile helpers?

Edit: Circling back to the organism perspective, in the sense of "I would gladly give up my life for two brothers or eight cousins.", how many bees is it worth giving up one's own life for in that specific sense? We do have a common ancestor after all and thus a non-zero R-factor.