Why do we need “publish or perish”?

June 23 JDN 2458658

This question may seem a bit self-serving, coming from a grad student who is struggling to get his first paper published in a peer-reviewed journal. But given the deep structural flaws in the academic publishing system, I think it’s worth taking a step back to ask just what peer-reviewed journals are supposed to be accomplishing.

The argument is often made that research journals are a way of sharing knowledge. If this is their goal, they have utterly and totally failed. Most papers are read by only a handful of people. When scientists want to learn about the research their colleagues are doing, they don’t read papers; they go to conferences to listen to presentations and look at posters. The way papers are written, they are often all but incomprehensible to anyone outside a very narrow subfield. When published by proprietary journals, papers are often hidden behind paywalls and accessible only through universities. As a knowledge-sharing mechanism, the peer-reviewed journal is a complete failure.

But academic publishing serves another function, which in practice is its only real function: Peer-reviewed publications are a method of evaluation. They are a way of deciding which researchers are good enough to be hired, get tenure, and receive grants. Having peer-reviewed publications—particularly in “top journals”, however that is defined within a given field—is a key metric that universities and grant agencies use to decide which researchers are worth spending on. Indeed, in some cases it seems to be utterly decisive.

We should be honest about this: This is an absolutely necessary function. It is uncomfortable to think about the fact that we must exclude a large proportion of competent, qualified people from being hired or getting tenure in academia, but given the large number of candidates and the small amounts of funding available, this is inevitable. We can’t hire everyone who would probably be good enough. We can only hire a few, and it makes sense to want those few to be the best. (Also, don’t fret too much: Even if you don’t make it into academia, getting a PhD is still a profitable investment. Economists and natural scientists do the best, unsurprisingly; but even humanities PhDs are still generally worth it. Median annual earnings of $77,000 is nothing to sneeze at: US median household income is only about $60,000. Humanities graduates only seem poor in relation to STEM or professional graduates; they’re still rich compared to everyone else.)

But I think it’s worth asking whether the peer review system is actually selecting the best researchers, or even the best research. Note that these are not the same question: The best research done in graduate school might not necessarily reflect the best long-run career trajectory for a researcher. A lot of very important, very difficult questions in science are just not the sort of thing you can get a convincing answer to in a couple of years, and so someone who wants to work on the really big problems may actually have a harder time getting published in graduate school or as a junior faculty member, even though ultimately work on the big problems is what’s most important for society. But I’m sure there’s a positive correlation overall: The kind of person who is going to do better research later is probably, other things equal, going to do better research right now.

Yet even accepting the fact that all we have to go on in assessing what you’ll eventually do is what you have already done, it’s not clear that the process of publishing in a peer-reviewed journal is a particularly good method of assessing the quality of research. Some really terrible research has gotten published in journals—I’m gonna pick on Daryl Bem, because he’s the worst—and a lot of really good research never made it into journals and is languishing on old computer hard drives. (The term “file drawer problem” is about 40 years obsolete; though to be fair, it was in fact coined about 40 years ago.)

That by itself doesn’t actually prove that journals are a bad mechanism. Even a good mechanism, applied to a difficult problem, is going to make some errors. But there are a lot of things about academic publishing, at least as currently constituted, that obviously don’t seem like a good mechanism, such as for-profit publishers, unpaid reviewiers, lack of double-blinded review, and above all, the obsession with “statistical significance” that leads to p-hacking.

Each of these problems I’ve listed has a simple fix (though whether the powers that be actually are willing to implement it is a different question: Questions of policy are often much easier to solve than problems of politics). But maybe we should ask whether the system is even worth fixing, or if it should simply be replaced entirely.

While we’re at it, let’s talk about the academic tenure system, because the peer-review system is largely an evaluation mechanism for the academic tenure system. Publishing in top journals is what decides whether you get tenure. The problem with “Publish or perish” isn’t the “publish”; it’s the perish”. Do we even need an academic tenure system?

The usual argument for academic tenure concerns academic freedom: Tenured professors have job security, so they can afford to say things that may be controversial or embarrassing to the university. But the way the tenure system works is that you only have this job security after going through a long and painful gauntlet of job insecurity. You have to spend several years prostrating yourself to the elders of your field before you can get inducted into their ranks and finally be secure.

Of course, job insecurity is the norm, particularly in the United States: Most employment in the US is “at-will”, meaning essentially that your employer can fire you for any reason at any time. There are specifically illegal reasons for firing (like gender, race, and religion); but it’s extremely hard to prove wrongful termination when all the employer needs to say is, “They didn’t do a good job” or “They weren’t a team player”. So I can understand how it must feel strange for a private-sector worker who could be fired at any time to see academics complain about the rigors of the tenure system.

But there are some important differences here: The academic job market is not nearly as competitive as the private sector job market. There simply aren’t that many prestigious universities, and within each university there are only a small number of positions to fill. As a result, universities have an enormous amount of power over their faculty, which is why they can get away with paying adjuncts salaries that amount to less than minimum wage. (People with graduate degrees! Making less than minimum wage!) At least in most private-sector labor markets in the US, the market is competitive enough that if you get fired, you can probably get hired again somewhere else. In academia that’s not so clear.

I think what bothers me the most about the tenure system is the hierarchical structure: There is a very sharp divide between those who have tenure, those who don’t have it but can get it (“tenure-track”), and those who can’t get it. The lines between professor, associate professor, assistant professor, lecturer, and adjunct are quite sharp. The higher up you are, the more job security you have, the more money you make, and generally the better your working conditions are overall. Much like what makes graduate school so stressful, there are a series of high-stakes checkpoints you need to get through in order to rise in the ranks. And several of those checkpoints are based largely, if not entirely, on publication in peer-reviewed journals.

In fact, we are probably stressing ourselves out more than we need to. I certainly did for my advancement to candidacy; I spent two weeks at such a high stress level I was getting migraines every single day (clearly on the wrong side of the Yerkes-Dodson curve), only to completely breeze through the exam.

I think I might need to put this up on a wall somewhere to remind myself:

Most grad students complete their degrees, and most assistant professors get tenure.

The real filters are admissions and hiring: Most applications to grad school are rejected (though probably most graduate students are ultimately accepted somewhere—I couldn’t find any good data on that in a quick search), and most PhD graduates do not get hired on the tenure track. But if you can make it through those two gauntlets, you can probably make it through the rest.

In our current system, publications are a way to filter people, because the number of people who want to become professors is much higher than the number of professor positions available. But as an economist, this raises a very big question: Why aren’t salaries falling?

You see, that’s how markets are supposed to work: When supply exceeds demand, the price is supposed to fall until the market clears. Lower salaries would both open up more slots at universities (you can hire more faculty with the same level of funding) and shift some candidates into other careers (if you can get paid a lot better elsewhere, academia may not seem so attractive). Eventually there should be a salary point at which demand equals supply. So why aren’t we reaching it?

Well, it comes back to that tenure system. We can’t lower the salaries of tenured faculty, not without a total upheaval of the current system. So instead what actually happens is that universities switch to using adjuncts, who have very low salaries indeed. If there were no tenure, would all faculty get paid like adjuncts? No, they wouldn’tbecause universities would have all that money they’re currently paying to tenured faculty, and all the talent currently locked up in tenured positions would be on the market, driving up the prevailing salary. What would happen if we eliminated tenure is not that all salaries would fall to adjunct level; rather, salaries would all adjust to some intermediate level between what adjuncts currently make and what tenured professors currently make.

What would the new salary be, exactly? That would require a detailed model of the supply and demand elasticities, so I can’t tell you without starting a whole new research paper. But a back-of-the-envelope calculation would suggest something like the overall current median faculty salary. This suggests a median salary somewhere around $75,000. This is a lot less than some professors make, but it’s also a lot more than what adjuncts make, and it’s a pretty good living overall.

If the salary for professors fell, the pool of candidates would decrease, and we wouldn’t need such harsh filtering mechanisms. We might decide we don’t need a strict evaluation system at all, and since the knowledge-sharing function of journals is much better served by other means, we could probably get rid of them altogether.

Of course, who am I kidding? That’s not going to happen. The people who make these rules succeeded in the current system. They are the ones who stand to lose high salaries and job security under a reform policy. They like things just the way they are.

The replication crisis, and the future of science

Aug 27, JDN 2457628 [Sat]

After settling in a little bit in Irvine, I’m now ready to resume blogging, but for now it will be on a reduced schedule. I’ll release a new post every Saturday, at least for the time being.

Today’s post was chosen by Patreon vote, though only one person voted (this whole Patreon voting thing has not been as successful as I’d hoped). It’s about something we scientists really don’t like to talk about, but definitely need to: We are in the middle of a major crisis of scientific replication.

Whenever large studies are conducted attempting to replicate published scientific results, their ability to do so is almost always dismal.

Psychology is the one everyone likes to pick on, because their record is particularly bad. Only 39% of studies were really replicated with the published effect size, though a further 36% were at least qualitatively but not quantitatively similar. Yet economics has its own replication problem, and even medical research is not immune to replication failure.

It’s important not to overstate the crisis; the majority of scientific studies do at least qualitatively replicate. We are doing better than flipping a coin, which is better than one can say of financial forecasters.
There are three kinds of replication, and only one of them should be expected to give near-100% results. That kind is reanalysiswhen you take the same data and use the same methods, you absolutely should get the exact same results. I favor making reanalysis a routine requirement of publication; if we can’t get your results by applying your statistical methods to your data, then your paper needs revision before we can entrust it to publication. A number of papers have failed on reanalysis, which is absurd and embarrassing; the worst offender was probably Rogart-Reinhoff, which was used in public policy decisions around the world despite having spreadsheet errors.

The second kind is direct replication—when you do the exact same experiment again and see if you get the same result within error bounds. This kind of replication should work something like 90% of the time, but in fact works more like 60% of the time.

The third kind is conceptual replication—when you do a similar experiment designed to test the same phenomenon from a different perspective. This kind of replication should work something like 60% of the time, but actually only works about 20% of the time.

Economists are well equipped to understand and solve this crisis, because it’s not actually about science. It’s about incentives. I facepalm every time I see another article by an aggrieved statistician about the “misunderstanding” of p-values; no, scientist aren’t misunderstanding anything. They know damn well how p-values are supposed to work. So why do they keep using them wrong? Because their jobs depend on doing so.

The first key point to understand here is “publish or perish”; academics in an increasingly competitive system are required to publish their research in order to get tenure, and frequently required to get tenure in order to keep their jobs at all. (Or they could become adjuncts, who are paid one-fifth as much.)

The second is the fundamentally defective way our research journals are run (as I have discussed in a previous post). As private for-profit corporations whose primary interest is in raising more revenue, our research journals aren’t trying to publish what will genuinely advance scientific knowledge. They are trying to publish what will draw attention to themselves. It’s a similar flaw to what has arisen in our news media; they aren’t trying to convey the truth, they are trying to get ratings to draw advertisers. This is how you get hours of meaningless fluff about a missing airliner and then a single chyron scroll about a war in Congo or a flood in Indonesia. Research journals haven’t fallen quite so far because they have reputations to uphold in order to attract scientists to read them and publish in them; but still, their fundamental goal is and has always been to raise attention in order to raise revenue.

The best way to do that is to publish things that are interesting. But if a scientific finding is interesting, that means it is surprising. It has to be unexpected or unusual in some way. And above all, it has to be positive; you have to have actually found an effect. Except in very rare circumstances, the null result is never considered interesting. This adds up to making journals publish what is improbable.

In particular, it creates a perfect storm for the abuse of p-values. A p-value, roughly speaking, is the probability you would get the observed result if there were no effect at all—for instance, the probability that you’d observe this wage gap between men and women in your sample if in the real world men and women were paid the exact same wages. The standard heuristic is a p-value of 0.05; indeed, it has become so enshrined that it is almost an explicit condition of publication now. Your result must be less than 5% likely to happen if there is no real difference. But if you will only publish results that show a p-value of 0.05, then the papers that get published and read will only be the ones that found such p-values—which renders the p-values meaningless.

It was never particularly meaningful anyway; as we Bayesians have been trying to explain since time immemorial, it matters how likely your hypothesis was in the first place. For something like wage gaps where we’re reasonably sure, but maybe could be wrong, the p-value is not too unreasonable. But if the theory is almost certainly true (“does gravity fall off as the inverse square of distance?”), even a high p-value like 0.35 is still supportive, while if the theory is almost certainly false (“are human beings capable of precognition?”—actual study), even a tiny p-value like 0.001 is still basically irrelevant. We really should be using much more sophisticated inference techniques, but those are harder to do, and don’t provide the nice simple threshold of “Is it below 0.05?”

But okay, p-values can be useful in many cases—if they are used correctly and you see all the results. If you have effect X with p-values 0.03, 0.07, 0.01, 0.06, and 0.09, effect X is probably a real thing. If you have effect Y with p-values 0.04, 0.02, 0.29, 0.35, and 0.74, effect Y is probably not a real thing. But I’ve just set it up so that these would be published exactly the same. They each have two published papers with “statistically significant” results. The other papers never get published and therefore never get seen, so we throw away vital information. This is called the file drawer problem.

Researchers often have a lot of flexibility in designing their experiments. If their only goal were to find truth, they would use this flexibility to test a variety of scenarios and publish all the results, so they can be compared holistically. But that isn’t their only goal; they also care about keeping their jobs so they can pay rent and feed their families. And under our current system, the only way to ensure that you can do that is by publishing things, which basically means only including the parts that showed up as statistically significant—otherwise, journals aren’t interested. And so we get huge numbers of papers published that tell us basically nothing, because we set up such strong incentives for researchers to give misleading results.

The saddest part is that this could be easily fixed.

First, reduce the incentives to publish by finding other ways to evaluate the skill of academics—like teaching for goodness’ sake. Working papers are another good approach. Journals already get far more submissions than they know what to do with, and most of these papers will never be read by more than a handful of people. We don’t need more published findings, we need better published findings—so stop incentivizing mere publication and start finding ways to incentivize research quality.

Second, eliminate private for-profit research journals. Science should be done by government agencies and nonprofits, not for-profit corporations. (And yes, I would apply this to pharmaceutical companies as well, which should really be pharmaceutical manufacturers who make cheap drugs based off of academic research and carry small profit margins.) Why? Again, it’s all about incentives. Corporations have no reason to want to find truth and every reason to want to tilt it in their favor.

Third, increase the number of tenured faculty positions. Instead of building so many new grand edifices to please your plutocratic donors, use your (skyrocketing) tuition money to hire more professors so that you can teach more students better. You can find even more funds if you cut the salaries of your administrators and football coaches. Come on, universities; you are the one industry in the world where labor demand and labor supply are the same people a few years later. You have no excuse for not having the smoothest market clearing in the world. You should never have gluts or shortages.

Fourth, require pre-registration of research studies (as some branches of medicine already do). If the study is sound, an optimal rational agent shouldn’t care in the slightest whether it had a positive or negative result, and if our ape brains won’t let us think that way, we need to establish institutions to force it to happen. They shouldn’t even see the effect size and p-value before they make the decision to publish it; all they should care about is that the experiment makes sense and the proper procedure was conducted.
If we did all that, the replication crisis could be almost completely resolved, as the incentives would be realigned to more closely match the genuine search for truth.

Alas, I don’t see universities or governments or research journals having the political will to actually make such changes, which is very sad indeed.

What’s wrong with academic publishing?

JDN 2457257 EDT 14:23.

I just finished expanding my master’s thesis into a research paper that is, I hope, suitable for publication in an economics journal. As part of this process I’ve been looking into the process of submitting articles for publication in academic journals… and I’ve found has been disgusting and horrifying. It is astonishingly bad, and my biggest question is why researchers put up with it.

Thus, the subject of this post is what’s wrong with the system—and what we might do instead.

Before I get into it, let me say that I don’t actually disagree with “publish or perish” in principle—as SMBC points out, it’s a lot like “do your job or get fired”. Researchers should publish in peer-reviewed journals; that’s a big part of what doing research means. The problem is how most peer-reviewed journals are currently operated.

First of all, in case you didn’t know, most scientific journals are owned by for-profit corporations. The largest corporation Elsevier, owns The Lancet and all of ScienceDirect, and has net income of over 1 billion Euros a year. Then there’s Springer and Wiley-Blackwell; between the three of them, these publishers account for over 40% of all scientific publications. These for-profit publishers retain the full copyright to most of the papers they publish, and tightly control access with paywalls; the cost to get through these paywalls is generally thousands of dollars a year for individuals and millions of dollars a year for universities. Their monopoly power is so great it “makes Rupert Murdoch look like a socialist.”

For-profit journals do often offer an “open-access” option in which you basically buy back your own copyright, but the price is high—the most common I’ve seen are $1800 or $3000 per paper—and very few researchers do this, for obvious financial reasons. In fact I think for a full-time tenured faculty researcher it’s probably worth it, given the alternatives. (Then again, full-time tenured faculty are becoming an endangered species lately; what might be worth it in the long run can still be very difficult for a cash-strapped adjunct to afford.) Open-access means people can actually read your paper and potentially cite your paper. Closed-access means it may languish in obscurity.

And of course it isn’t just about the benefits for the individual researcher. The scientific community as a whole depends upon the free flow of information; the reason we publish in the first place is that we want people to read papers, discuss them, replicate them, challenge them. Publication isn’t the finish line; it’s at best a checkpoint. Actually one thing that does seem to be wrong with “publish or perish” is that there is so much pressure for publication that we publish too many pointless papers and nobody has time to read the genuinely important ones.

These prices might be justifiable if the for-profit corporations actually did anything. But in fact they are basically just aggregators. They don’t do the peer-review, they farm it out to other academic researchers. They don’t even pay those other researchers; they just expect them to do it. (And they do! Like I said, why do they put up with this?) They don’t pay the authors who have their work published (on the contrary, they often charge submission fees—about $100 seems to be typical—simply to look at them). It’s been called “the world’s worst restaurant”, where you pay to get in, bring your own ingredients and recipes, cook your own food, serve other people’s food while they serve yours, and then have to pay again if you actually want to be allowed to eat.

They pay for the printing of paper copies of the journal, which basically no one reads; and they pay for the electronic servers that host the digital copies that everyone actually reads. They also provide some basic copyediting services (copyediting APA style is a job people advertise on Craigslist—so you can guess how much they must be paying).

And even supposing that they actually provided some valuable and expensive service, the fact would remain that we are making for-profit corporations the gatekeepers of the scientific community. Entities that exist only to make money for their owners are given direct control over the future of human knowledge. If you look at Cracked’s “reasons why we can’t trust science anymore”, all of them have to do with the for-profit publishing system. p-hacking might still happen in a better system, but publishers that really had the best interests of science in mind would be more motivated to fight it than publishers that are simply trying to raise revenue by getting people to buy access to their papers.

Then there’s the fact that most journals do not allow authors to submit to multiple journals at once, yet take 30 to 90 days to respond and only publish a fraction of what is submitted—it’s almost impossible to find good figures on acceptance rates (which is itself a major problem!), but the highest figures I’ve seen are 30% acceptance, a more typical figure seems to be 10%, and some top journals go as low as 3%. In the worst-case scenario you are locked into a journal for 90 days with only a 3% chance of it actually publishing your work. At that rate publishing an article could take years.

Is open-access the solution? Yes… well, part of it, anyway.

There are a large number of open-access journals, some of which do not charge submission fees, but very few of them are prestigious, and many are outright predatory. Predatory journals charge exorbitant fees, often after accepting papers for publication; many do little or no real peer review. There are almost seven hundred known predatory open-access journals; over one hundred have even been caught publishing hoax papers. These predatory journals are corrupting the process of science.

There are a few reputable open-access journals, such as BMC Biology and PLOSOne. Though not actually a journal, ArXiv serves a similar role. These will be part of the solution, most definitely. Yet even legitimate open-access journals often charge each author over $1000 to publish an article. There is a small but significant positive correlation between publication fees and journal impact factor.

We need to found more open-access journals which are funded by either governments or universities, so that neither author nor reader ever pays a cent. Science is a public good and should be funded as such. Even if copyright makes sense for other forms of content (I’m not so sure about that), it most certainly does not make sense for scientific knowledge, which by its very nature is only doing its job if it is shared with the world.

These journals should be specifically structured to be method-sensitive but results-blind. (It’s a very good thing that medical trials are usually registered before they are completed, so that publication is assured even if the results are negative—the same should be done with other sciences. Unfortunately, even in medicine there is significant publication bias.) If you could sum up the scientific method in one phrase, it might just be that: Method-sensitive but results-blind. If you think you know what you’re going to find beforehand, you may not be doing science. If you are certain what you’re going to find beforehand, you’re definitely not doing science.

The process should still be highly selective, but it should be possible—indeed, expected—to submit to multiple journals at once. If journals want to start paying their authors to entice them to publish in that journal rather than take another offer, that’s fine with me. Researchers are the ones who produce the content; if anyone is getting paid for it, it should be us.

This is not some wild and fanciful idea; it’s already the way that book publishing works. Very few literary agents or book publishers would ever have the audacity to say you can’t submit your work elsewhere; those that try are rapidly outcompeted as authors stop submitting to them. It’s fundamentally unreasonable to expect anyone to hang all their hopes on a particular buyer months in advance—and that is what you are, publishers, you are buyers. You are not sellers, you did not create this content.

But new journals face a fundamental problem: Good researchers will naturally want to publish in journals that are prestigious—that is, journals that are already prestigious. When all of the prestige is in journals that are closed-access and owned by for-profit companies, the best research goes there, and the prestige becomes self-reinforcing. Journals are prestigious because they are prestigious; welcome to tautology club.

Somehow we need to get good researchers to start boycotting for-profit journals and start investing in high-quality open-access journals. If Elsevier and Springer can’t get good researchers to submit to them, they’ll change their ways or wither and die. Research should be funded and published by governments and nonprofit institutions, not by for-profit corporations.

This may in fact highlight a much deeper problem in academia, the very concept of “prestige”. I have no doubt that Harvard is a good university, better university than most; but is it actually the best as it is in most people’s minds? Might Stanford or UC Berkeley be better, or University College London, or even the University of Michigan? How would we tell? Are the students better? Even if they are, might that just be because all the better students went to the schools that had better reputations? Controlling for the quality of the student, more prestigious universities are almost uncorrelated with better outcomes. Those who get accepted to Ivies but attend other schools do just as well in life as those who actually attend Ivies. (Good news for me, getting into Columbia but going to Michigan.) Yet once a university acquires such a high reputation, it can be very difficult for it to lose that reputation, and even more difficult for others to catch up.

Prestige is inherently zero-sum; for me to get more prestige you must lose some. For one university or research journal to rise in rankings, another must fall. Aside from simply feeding on other prestige, the prestige of a university is largely based upon the students it rejects—its “selectivity” score. What does it say about our society that we value educational institutions based upon the number of people they exclude?

Zero-sum ranking is always easier to do than nonzero-sum absolute scoring. Actually that’s a mathematical theorem, and one of the few good arguments against range voting (still not nearly good enough, in my opinion); if you have a list of scores you can always turn them into ranks (potentially with ties); but from a list of ranks there is no way to turn them back into scores.

Yet ultimately it is absolute scores that must drive humanity’s progress. If life were simply a matter of ranking, then progress would be by definition impossible. No matter what we do, there will always be top-ranked and bottom-ranked people.

There is simply no way mathematically for more than 1% of human beings to be in the top 1% of the income distribution. (If you’re curious where exactly that lies today, I highly recommend this interactive chart by the New York Times.) But we could raise the standard of living for the majority of people to a level that only the top 1% once had—and in fact, within the First World we have already done this. We could in fact raise the standard of living for everyone in the First World to a level that only the top 1%—or less—had as recently as the 16th century, by the simple change of implementing a basic income.

There is no way for more than 0.14% of people to have an IQ above 145, because IQ is defined to have a mean of 100 and a standard deviation of 15, regardless of how intelligent people are. People could get dramatically smarter over timeand in fact have—and yet it would still be the case that by definition, only 0.14% can be above 145.

Similarly, there is no way for much more than 1% of people to go to the top 1% of colleges. There is no way for more than 1% of people to be in the highest 1% of their class. But we could increase the number of college degrees (which we have); we could dramatically increase literacy rates (which we have).

We need to find a way to think of science in the same way. I wouldn’t suggest simply using number of papers published or even number of drugs invented; both of those are skyrocketing, but I can’t say that most of the increase is actually meaningful. I don’t have a good idea of what an absolute scale for scientific quality would look like, even at an aggregate level; and it is likely to be much harder still to make one that applies on an individual level.

But I think that ultimately this is the only way, the only escape from the darkness of cutthroat competition. We must stop thinking in terms of zero-sum rankings and start thinking in terms of nonzero-sum absolute scales.