Why do we manage academia so badly?
March 22, 2017
The previous post (Every attempt to manage academia makes it worse) has been a surprise hit, and is now by far the most-read post in this blog’s nearly-ten-year history. It evidently struck a chord with a lot of people, and I’ve been surprised — amazed, really — at how nearly unanimously people have agreed with it, both in the comments here and on Twitter.
But I was brought up short by this tweet from Thomas Koenig:
That is the question, isn’t it? Why do we keep doing this?
I don’t know enough about the history of academia to discuss the specific route we took to the place we now find ourselves in. (If others do, I’d be fascinated to hear.) But I think we can fruitfully speculate on the underlying problem.
Let’s start with the famous true story of the Hanoi rat epidemic of 1902. In a town overrun by rats, the authorities tried to reduce the population by offering a bounty on rat tails. Enterprising members of the populace responded by catching live rats, cutting off their tails to collect the bounty, then releasing the rats to breed, so more tails would be available in future. Some people even took to breeding rats for their tails.
Why did this go wrong? For one very simple reason: because the measure optimised for was not the one that mattered. What the authorities wanted to do was reduce the number of rats in Hanoi. For reasons that we will come to shortly, the proxy that they provided an incentive for was the number of rat tails collected. These are not the same thing — optimising for the latter did not help the former.
The badness of the proxy measure applies in two ways.
First, consider those who caught rats, cut their tails off and released them. They stand as counter-examples to the assumption that harvesting a rat-tail is equivalent to killing the rat. The proxy was bad because it assumed a false equivalence. It was possible to satisfy the proxy without advancing the actual goal.
Second, consider those who bred rats for their tails. They stand as counter-examples to the assumption that killing a rat is equivalent to decreasing the total number of live rats. Worse, if the breeders released their de-tailed captive-bred progeny into the city, their harvests of tails not only didn’t represent any decrease in the feral population, they represented an increase. So the proxy was worse than neutral because satisfying it could actively harm the actual goal.
So far, so analogous to the perverse academic incentives we looked at last time. Where this gets really interesting is when we consider why the Hanoi authorities chose such a terribly counter-productive proxy for their real goal. Recall their object was to reduce the feral rat population. There were two problems with that goal.
First, the feral rat population is hard to measure. It’s so much easier to measure the number of tails people hand in. A metric is seductive if it’s easy to measure. In the same way, it’s appealing to look for your dropped car-keys under the street-lamp, where the light is good, rather than over in the darkness where you dropped them. But it’s equally futile.
Second — and this is crucial — it’s hard to properly reward people for reducing the feral rat population because you can’t tell who has done what. If an upstanding citizen leaves poison in the sewers and kills a thousand rats, there’s no way to know what he has achieved, and to reward him for it. The rat-tail proxy is appealing because it’s easy to reward.
The application of all this to academia is pretty obvious.
First the things we really care about are hard to measure. The reason we do science — or, at least, the reason societies fund science — is to achieve breakthroughs that benefit society. That means important new insights, findings that enable new technology, ways of creating new medicines, and so on. But all these things take time to happen. It’s difficult to look at what a lab is doing now and say “Yes, this will yield valuable results in twenty years”. Yet that may be what is required: trying to evaluate it using a proxy of how many papers it gets into high-IF journals this year will most certainly mitigate against its doing careful work with long-term goals.
Second we have no good way to reward the right individuals or labs. What we as a society care about is the advance of science as a whole. We want to reward the people and groups whose work contributes to the global project of science — but those are not necessarily the people who have found ways to shine under the present system of rewards: publishing lots of papers, shooting for the high-IF journals, skimping on sample-sizes to get spectacular results, searching through big data-sets for whatever correlations they can find, and so on.
In fact, when a scientist who is optimising for what gets rewarded slices up a study into multiple small papers, each with a single sensational result, and shops them around Science and Nature, all they are really doing is breeding rats.
If we want people to stop behaving this way, we need to stop rewarding them for it. (Side-effect: when people are rewarded for bad behaviour, people who behave well get penalised, lose heart, and leave the field. They lose out, and so does society.)
Q. “Well, that’s great, Mike. What do you suggest?”
A. Ah, ha ha, I’d been hoping you wouldn’t bring that up.
No-will be surprised to hear that I don’t have a silver bullet. But I think the place to start is by being very aware of the pitfalls of the kinds of metrics that managers (including us, when wearing certain hats) like to use. Managers want metrics that are easy to calculate, easy to understand, and quick to yield a value. That’s why articles are judged by the impact factor of the journal they appear in: the calculation of the article’s worth is easy (copy the journal’s IF out of Wikipedia); it’s easy to understand (or, at least, it’s easy for people to think they understand what an IF is); and best of all, it’s available immediately. No need for any of that tedious waiting around five years to see how often the article is cited, or waiting ten years to see what impact it has on the development of the field.
Wise managers (and again, that means us when wearing certain hats) will face up to the unwelcome fact that metrics with these desirable properties are almost always worse than useless. Coming up with better metrics, if we’re determined to use metrics at all, is real work and will require an enormous educational effort.
One thing we can usefully do, whenever considering a proposed metric, is actively consider how it can and will be hacked. Black-hat it. Invest a day imagining you are a rational, selfish researcher in a regimen that uses the metric, and plan how you’re going to exploit it to give yourself the best possible score. Now consider whether the course of action you mapped out is one that will benefit the field and society. If not, dump the metric and start again.
Q. “Are you saying we should get rid of metrics completely?”
A. Not yet; but I’m open to the possibility.
Given metrics’ terrible track-record of hackability, I think we’re now at the stage where the null hypothesis should be that any metric will make things worse. There may well be exceptions, but the burden of proof should be on those who want to use them: they must show that they will help, not just assume that they will.
And what if we find that every metric makes things worse? Then the only rational thing to do would be not to use any metrics at all. Some managers will hate this, because their jobs depend on putting numbers into boxes and adding them up. But we’re talking about the progress of research to benefit society, here.
We have to go where the evidence leads. Dammit, Jim, we’re scientists.
Every attempt to manage academia makes it worse
March 17, 2017
I’ve been on Twitter since April 2011 — nearly six years. A few weeks ago, for the first time, something I tweeted broke the thousand-retweets barrier. And I am really unhappy about it. For two reasons.
First, it’s not my own content — it’s a screen-shot of Table 1 from Edwards and Roy (2017):
And second, it’s so darned depressing.
The problem is a well-known one, and indeed one we have discussed here before: as soon as you try to measure how well people are doing, they will switch to optimising for whatever you’re measuring, rather than putting their best efforts into actually doing good work.
In fact, this phenomenon is so very well known and understood that it’s been given at least three different names by different people:
- Goodhart’s Law is most succinct: “When a measure becomes a target, it ceases to be a good measure.”
- Campbell’s Law is the most explicit: “The more any quantitative social indicator is used for social decision-making, the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor.”
- The Cobra Effect refers to the way that measures taken to improve a situation can directly make it worse.
As I say, this is well known. There’s even a term for it in social theory: reflexivity. And yet we persist in doing idiot things that can only possibly have this result:
- Assessing school-teachers on the improvement their kids show in tests between the start and end of the year (which obviously results in their doing all they can depress the start-of-year tests).
- Assessing researchers by the number of their papers (which can only result in slicing into minimal publishable units).
- Assessing them — heaven help us — on the impact factors of the journals their papers appear in (which feeds the brand-name fetish that is crippling scholarly communication).
- Assessing researchers on whether their experiments are “successful”, i.e. whether they find statistically significant results (which inevitably results in p-hacking and HARKing).
What’s the solution, then?
I’ve been reading the excellent blog of economist Tim Harford, for a while. That arose from reading his even more excellent book The Undercover Economist (Harford 2007), which gave me a crash-course in the basics of how economies work, how markets help, how they can go wrong, and much more. I really can’t say enough good things about this book: it’s one of those that I feel everyone should read, because the issues are so important and pervasive, and Harford’s explanations are so clear.
In a recent post, Why central bankers shouldn’t have skin in the game, he makes this point:
The basic principle for any incentive scheme is this: can you measure everything that matters? If you can’t, then high-powered financial incentives will simply produce short-sightedness, narrow-mindedness or outright fraud. If a job is complex, multifaceted and involves subtle trade-offs, the best approach is to hire good people, pay them the going rate and tell them to do the job to the best of their ability.
I think that last part is pretty much how academia used to be run a few decades ago. Now I don’t want to get all misty-eyed and rose-tinted and nostalgic — especially since I wasn’t even involved in academia back then, and don’t know from experience what it was like. But could it be … could it possibly be … that the best way to get good research and publications out of scholars is to hire good people, pay them the going rate and tell them to do the job to the best of their ability?
[Read on to Why do we manage academia so badly?]
References
- Edwards, Marc A., and Siddhartha Roy. 2017. Academic Research in the 21st Century: Maintaining Scientific Integrity in a Climate of Perverse Incentives and Hypercompetition. Environmental Engineering Science 34(1):51-61.
- Harford, Tim. 2007. The Undercover Economist. Abacus (Little, Brown). 384 pages. [Amazon US, Amazon UK]
Bonus
Here is a nicely formatted full-page version of the Edwards and Roy table, for you to print out and stick on all the walls of your university. My thanks to David Roberts for preparing it.
The Medical Journal of Australia vs Elsevier
May 6, 2015
While Mike’s been off having fun at the Royal Society, this has been happening:
Lots of feathers flying right now over the situation at the Medical Journal of Australia (MJA). The short, short version is that AMPCo, the company that publishes MJA, made plans to outsource production of the journal, and apparently some sub-editing and administrative functions as well, to Elsevier. MJA’s editor-in-chief, Professor Stephen Leeder, raised concerns about the journal getting involved with one of the most ethically problematic publishing companies in existence. And also about this having been done without consultation.
He was sacked for his trouble.
After Leeder was pushed out, his job was offered to MJA’s deputy editor, Tania Janusic. She declined, and resigned from the journal, as did 19 of the 20 members of the journal’s editorial advisory committee. (Some accounts say 18. Anyway, 90%+ of the committee is gone.)
When we first discussed the situation via email, Mike wrote, “My take is that at the present stage of the OA transition, editorial board resignations from journals controlled by predatory legacy publishers are about the most important visible steps that can be taken. Very good news for the world, even though it must be a mighty pain for the people involved.”
Yes. I feel pretty bad for the people involved, but I’m hugely supportive of what they’re doing.
I don’t know what we can do to materially contribute here, beyond amplifying the signal and lending our public support to Leeder, Janusic, and the 19 editors who resigned. That’s a courageous thing to do, but no-one should have to do it. The sooner we move to a world where scientific results and other forms of scholarly publication are freely available to all, instead of under the monopolistic control of a handful of exploitative, hugely profitable corporations, the better.
A short list of links, nowhere near exhaustive, if you’d like to read more:
UPDATE: In the first comment below, Alex Holcombe pointed us to this post written by Leeder himself, explaining the reasoning and consequences of his decision.
Also, dunno how I forgot this – if you haven’t already, you might be interested in signing the Cost of Knowledge boycott against Elsevier. Here’s the link.
Interview with Open Access Nigeria
October 22, 2014
Last night, I did a Twitter interview with Open Access Nigeria (@OpenAccessNG). To make it easy to follow in real time, I created a list whose only members were me and OA Nigeria. But because Twitter lists posts in reverse order, and because each individual tweet is encumbered with so much chrome, it’s rather an awkward way to read a sustained argument.
So here is a transcript of those tweets, only lightly edited. They are in bold; I am in regular font. Enjoy!
—
So @MikeTaylor Good evening and welcome. Twitterville wants to meet you briefly. Who is Mike Taylor?
In real life, I’m a computer programmer with Index Data, a tiny software house that does a lot of open-source programming. But I’m also a researching scientist — a vertebrate palaeontologist, working on sauropods: the biggest and best of the dinosaurs. Somehow I fit that second career into my evenings and weekends, thanks to a very understanding wife (Hi, Fiona!) …
As of a few years ago, I publish all my dinosaur research open access, and I regret ever having let any of my work go behind paywalls. You can find all my papers online, and read much more about them on the blog that I co-write with Matt Wedel. That blog is called Sauropod Vertebra Picture of the Week, or SV-POW! for short, and it is itself open access (CC By)
Sorry for the long answer, I will try to be more concise with the next question!
Ok @MikeTaylor That’s just great! There’s been so much noise around twitter, the orange colour featuring prominently. What’s that about?
Actually, to be honest, I’m not really up to speed with open-access week (which I think is what the orange is all about). I found a while back that I just can’t be properly on Twitter, otherwise it eats all my time. So these days, rather selfishly, I mostly only use Twitter to say things and get into conversations, rather than to monitor the zeitgeist.
That said, orange got established as the colour of open access a long time ago, and is enshrined in the logo:
In the end I suppose open-access week doesn’t hit my buttons too strongly because I am trying to lead a whole open-access life.
… uh, but thanks for inviting me to do this interview, anyway! :-)
You’re welcome @MikeTaylor. So what is open access?
Open Access, or OA, is the term describing a concept so simple and obvious and naturally right that you’d hardly think it needs a name. It just means making the results of research freely available on the Internet for anyone to read, remix and otherwise use.
You might reasonably ask, why is there any other kind of published research other than open access? And the only answer is, historical inertia. For reasons that seemed to make some kind of sense at the time, the whole research ecosystem has got itself locked into this crazy equilibrium where most published research is locked up where almost no-one can see it, and where even the tiny proportion of people who can read published works aren’t allowed to make much use of them.
So to answer the question: the open-access movement is an attempt to undo this damage, and to make the research world sane.
Are there factors perpetuating this inertia you talked about?
Oh, so many factors perpetuting the inertia. Let me list a few …
- Old-school researchers who grew up when it was hard to find papers, and don’t see why young whippersnappers should have it easier
- Old-school publishers who have got used to making profits of 30-40% turnover (they get content donated to them, then charge subscriptions)
- University administrators who make hiring/promotion/tenure decisions based on which old-school journals a researcher’s papers are in.
- Feeble politicians who think it’s important to keep the publishing sector profitable, even at the expense of crippling research.
I’m sure there are plenty of others who I’ve overlooked for the moment. I always say regarding this that there’s plenty of blame to go round.
(This, by the way, is why I called the current situation an equilibrium. It’s stable. Won’t fix itself, and needs to be disturbed.)
So these publishers who put scholarly articles behind paywalls online, do they pay the researchers for publishing their work?
HAHAHAHAHAHAHAHAHAHA!
Oh, sorry, please excuse me while I wipe the tears of mirth from my eyes. An academic publisher? Paying an author? Hahahahaha! No.
Not only do academic publishers never pay authors, in many cases they also levy page charges — that is, they charge the authors. So they get paid once by the author, in page-charges, then again by all the libraries that subscribe to read the paywalled papers. Which of course is why, even with their gross inefficiencies, they’re able to make these 30-40% profit margins.
So @MikeTaylor why do many researchers continue to take their work to these restricted access publishers and what can we do about it?
There are a few reasons that play into this together …
Part of it is just habit, especially among more senior researchers who’ve been using the same journals for 20 or 30 years.
But what’s more pernicious is the tendency of academics — and even worse, academic administrators — to evaluate research not by its inherent quality, but by the prestige of the journal that publishes it. It’s just horrifyingly easy for administrators to say “He got three papers out that year, but they were in journals with low Impact Factors.”
Which is wrong-headed on so many levels.
First of all, they should be looking at the work itself, and making an assessment of how well it was done: rigour, clarity, reproducibility. But it’s much easier just to count citations, and say “Oh, this has been cited 50 times, it must be good!” But of course papers are not always cited because they’re good. Sometimes they’re cited precisely because they’re so bad! For example, no doubt the profoundly flawed Arsenic Life paper has been cited many times — by people pointing out its numerous problems.
But wait, it’s much worse than that! Lazy or impatient administrators won’t count how many times a paper has been cited. Instead they will use a surrogate: the Impact Factor (IF), which is a measure not of papers but of journals.
Roughly, the IF measures the average number of citations received by papers that are published in the journal. So at best it’s a measure of journal quality (and a terrible measure of that, too, but let’s not get into that). The real damage is done when the IF is used to evaluate not journals, but the papers that appear in them.
And because that’s so widespread, researchers are often desperate to get their work into journals that have high IFs, even if they’re not OA. So we have an idiot situation where a selfish, rational researcher is best able to advance her career by doing the worst thing for science.
(And BTW, counter-intuitively, the number of citations an individual paper receives is NOT correlated significantly with the journal’s IF. Bjorn Brembs has discussed this extensively, and also shows that IF is correlated with retraction rate. So in many respects the high-IF journals are actually the worst ones you can possibly publish your work in. Yet people feel obliged to.)
*pant* *pant* *pant* OK, I had better stop answering this question, and move on to the next. Sorry to go on so long. (But really! :-) )
This is actually all so enlightening. You just criticised Citation Index along with Impact Factor but OA advocates tend to hold up a higher Citation Index as a reason to publish Open Access. What do you think regarding this?
I think that’s realpolitik. To be honest, I am also kind of pleased that the PLOS journals have pretty good Impact Factors: not because I think the IFs mean anything, but because they make those journals attractive to old-school researchers.
In the same way, it is a well-established fact that open-access articles tend to be cited more than paywalled ones — a lot more, in fact. So in trying to bring people across into the OA world, it makes sense to use helpful facts like these. But they’re not where the focus is.
But the last thing to say about this is that even though raw citation-count is a bad measure of a paper’s quality, it is at least badly measuring the right thing. Evaluating a paper by its journal’s IF is like judging someone by the label of their clothes
So @MikeTaylor Institutions need to stop evaluating research papers based on where they are published? Do you know of any doing it right?
I’m afraid I really don’t know. I’m not privy to how individual institution do things.
All I know is, in some countries (e.g. France) abuse of IF is much more strongly institutionalised. It’s tough for French researchers
What are the various ways researchers can make their work available for free online?
Brilliant, very practical question! There are three main answers. (Sorry, this might go on a bit …)
First, you can post your papers on preprint servers. The best known one is arXiv, which now accepts papers from quite a broad subject range. For example, a preprint of one of the papers I co-wrote with Matt Wedel is freely available on arXiv. There are various preprint servers, including arXiv for physical sciences, bioRxiv, PeerJ Preprints, and SSRN (Social Science Research Network).
You can put your work on a preprint server whatever your subsequent plans are for it — even if (for some reason) it’s going to a paywall. There are only a very few journals left that follow the “Ingelfinger rule” and refuse to publish papers that have been preprinted.
So preprints are option #1. Number 2 is Gold Open Access: publishing in an open-access journal such as PLOS ONE, a BMC journal or eLife. As a matter of principle, I now publish all my own work in open-access journals, and I know lots of other people who do the same — ranging from amateurs like me, via early-career researchers like Erin McKiernan, to lab-leading senior researchers like Michael Eisen.
There are two potential downsides to publishing in an OA journal. One, we already discussed: the OA journals in your field may not be be the most prestigious, so depending on how stupid your administrators are you could be penalised for using an OA journal, even though your work gets cited more than it would have done in a paywalled journal.
The other potential reason some people might want to avoid using an OA journal is because of Article Processing Charges (APC). Because OA publishers have no subscription revenue, one common business model is to charge authors an APC for publishing services instead. APCs can vary wildly, from $0 up to $5000 in the most extreme case (a not-very-open journal run by the AAAS), so they can be offputting.
There are three things to say about APCs.
First, remember that lots of paywalled journals demand page charges, which can cost more!
But second, please know that more than half of all OA journals actually charge no APC at all. They run on different models. For example in my own field, Acta Palaeontologica Polonica and Palaeontologia Electronica are well respected OA journals that charge no APC.
And the third thing is APC waivers. These are very common. Most OA publishers have it as a stated goal that no-one should be prevented from publishing with them by lack of funds for APCs. So for example PLOS will nearly always give a waiver when requested. Likewise Ubiquity, and others.
So there are lots of ways to have your work appear in an OA journal without paying for it to be there.
Anyway, all that was about the second way to make your work open access. #1 was preprints, #2 is “Gold OA” in OA journals …
And #3 is “Green OA”, which means publishing in a paywalled journal, but depositing a copy of the paper in an open repository. The details of how this works can be a bit complicated: different paywall-based publishers allow you to do different things, e.g. it’s common to say “you can deposit your peer-reviewed, accepted but unformatted manuscript, but only after 12 months“.
Opinions vary as to how fair or enforceable such rules are. Some OA advocates prefer Green. Others (including me) prefer Gold. Both are good.
See this SV-POW! post on the practicalities of negotiating Green OA if you’re publishing behind a paywall.
So to summarise:
- Deposit preprints
- Publish in an OA journal (getting a fee waiver if needed)
- Deposit postprints
I’ve written absolutely shedloads on these subjects over the last few years, including this introductory batch. If you only read one of my pieces about OA, make it this one: The parable of the farmers & the Teleporting Duplicator.
Last question – Do restricted access publishers pay remuneration to peer reviewers?
I know of no publisher that pays peer reviewers. But actually I am happy with that. Peer-review is a service to the community. As soon as you encumber it with direct financial incentives, things get more complicated and there’s more potential for Conflict of interest. What I do is, I only perform peer-reviews for open-access journals. And I am happy to put that time/effort in knowing the world will benefit.
And so we bring this edition to a close. We say a big thanks to our special guest @MikeTaylor who’s been totally awesome and instructive.
Thanks, it’s been a privilege.
How to negotiate with Elsevier
April 25, 2014
Eminent British mathematician Tim Gowers has written an epic post on his attempts to get universities to disclose how much they pay for their Elsevier subscriptions. There is a lot of fascinating anecdote in there, and a shedload of important data — it’s very well worth a read.
But here is the part that staggered me most. Gowers wrote to (among others) Queen’s University Belfast, requesting the subscription cost under Freedom of Information rules. The reply was from Amanda Aicken, Information Compliance Unit (and by the way was addressed to Mr. Gowers, but let it pass). It refused to disclose the price on the basis that:
The disclosure of this information would be likely to have a detrimental effect on Elsevier’s future negotiating position with […] the University.
Now that paragraph is exactly equivalent to:
The disclosure of this information would be likely to have a positive effect on the University’s future negotiating position with Elsevier.
Wouldn’t a decent university administrator think that’s a good thing?
