The big scandal this weekend: Peter Boghossian and James Lindsay pulled a hoax on a social-science journal by getting a deliberately nonsensical paper published there, and then crowed that this demonstrates the field of gender studies to be “crippled academically.” However, when people with a measure of sense examined B&L’s stunt, they found it to be instead evidence that you can get any crap published if you lower your standards far enough, particularly if you’re willing to pay for the privilege and you find a journal whose raison d’être is to rip people off. Indeed, B&L’s paper (“The conceptual penis as a social construct”) was rejected from the first journal they sent it to, and it got bounced down the line to a new and essentially obscure venue of dubious ethical standing. Specifically, I can’t find anybody who had even heard of Cogent Social Sciences apart from spam emails inviting them to publish there. This kind of bottom-feeding practice has proliferated in the years since Open Access publishing became a thing, to unclear effect. It hasn’t seemed in practice to tarnish the reputation of serious Open Access journals (the PLOS family, Scientific Reports, Physical Review X, Discrete Analysis, etc.). Arguably, once the infrastructure of the Web existed, some variety of pay-to-publish scam was inevitable, since there will always be academics angling for the appearance of success—as long as there are tenure committees.

Boghossian and Lindsay made the triumphant announcement of their hoax in Skeptic, a magazine edited by Michael Shermer. And if you think that I’ll use this as an occasion to voice my grievances at Capital-S Skepticism being a garbage fire of a movement, you’re absolutely correct. I agree with the thesis of Ketan Joshi here:

The article in Skeptic Magazine highlights how regularly people will vastly lower their standards of skepticism and rationality if a piece of information is seen as confirmation of a pre-existing belief – in this instance, the belief that gender studies is fatally compromised by seething man-hate. The standard machinery of rationality would have triggered a moment of doubt – ‘perhaps we’ve not put in enough work to separate the signal from the noise’, or ‘perhaps we need to tease apart the factors more carefully’.

That slow, deliberative mechanism of self-assessment is non-existent in the authorship and sharing of this piece. It seems quite likely that this is due largely to a pre-existing hostility towards gender studies, ‘identity politics’ and the general focus of contemporary progressive America.

Boghossian and Lindsay see themselves as the second coming of Alan Sokal, who successfully fooled Social Text into publishing a parody of postmodern theory-babble back in 1999. But after the fact, Sokal said the publication of his hoax itself didn’t prove much at all, just that a few people happened to be asleep at the wheel. (His words: “From the mere fact of publication of my parody I think that not much can be deduced.”) Then he wrote two books of footnotes and caveats to show that he had lampooned some views he himself held in more moderate form.

Meanwhile, Steven Pinker—who happily boosted the B&L hoax to his 310,000 Twitter followers—strips all the technical content out of physics, mixes the jargon up with trite and folksy “wisdom,” and uses the result to support pompous bloviation.

… Which, funny story, is one of the main things that Alan Sokal was criticizing.

I gotta quote this part of B&L’s boast:
Continue reading Bogho-A-Lago

Simple Equations are No Good When the Variables are Meaningless

A few weeks back, I reflected on why mathematical biology can be so hard to learn—much harder, indeed, than the mathematics itself would warrant.

The application of mathematics to biological evolution is rooted, historically, in statistics rather than in dynamics. Consequently, a lot of model-building starts with tools that belong, essentially, to descriptive statistics (e.g., linear regression). This is fine, but then people turn around and discuss those models in language that implies they have constructed a dynamical system. This makes life quite difficult for the student trying to learn the subject by reading papers! The problem is not the algebra, but the assumptions; not the derivations, but the discourse.

Recently, a colleague of mine, Ben Allen, coauthored a paper that clears up one of the more confusing points.

Hamilton’s rule asserts that a trait is favored by natural selection if the benefit to others, $B$, multiplied by relatedness, $R$, exceeds the cost to self, $C$. Specifically, Hamilton’s rule states that the change in average trait value in a population is proportional to $BR – C$. This rule is commonly believed to be a natural law making important predictions in biology, and its influence has spread from evolutionary biology to other fields including the social sciences. Whereas many feel that Hamilton’s rule provides valuable intuition, there is disagreement even among experts as to how the quantities $B$, $R$, and $C$ should be defined for a given system. Here, we investigate a widely endorsed formulation of Hamilton’s rule, which is said to be as general as natural selection itself. We show that, in this formulation, Hamilton’s rule does not make predictions and cannot be tested empirically. It turns out that the parameters $B$ and $C$ depend on the change in average trait value and therefore cannot predict that change. In this formulation, which has been called “exact and general” by its proponents, Hamilton’s rule can “predict” only the data that have already been given.


Multiscale Structure of More-than-Binary Variables

When I face a writing task, my two big failure modes are either not starting at all and dragging my feet indefinitely, or writing far too much and having to cut it down to size later. In the latter case, my problem isn’t just that I go off on tangents. I try to answer every conceivable objection, including those that only I would think of. As a result, I end up fighting a rhetorical battle that only I know about, and the prose that emerges is not just overlong, but arcane and obscure. Furthermore, if the existing literature on a subject is confusing to me, I write a lot in the course of figuring it out, and so I end up with great big expository globs that I feel obligated to include with my reporting on what I myself actually did. That’s why my PhD thesis set the length record for my department by a factor of about three.

I have been experimenting with writing scientific pieces that are deliberately bite-sized to begin with. The first such experiment that I presented to the world, “Sporadic SICs and the Normed Division Algebras,” was exactly two pages long in its original form. The version that appeared in a peer-reviewed journal was slightly longer; I added a paragraph of context and a few references.

My latest attempt at a mini-paper (articlet?) is based on a blog post from a few months back. I polished it up, added some mathematical details, and worked in a comparison with other research that was published since I posted that blog item. The result is still fairly short:

Social Media Experiment

I decided to give Mastodon a whirl, so a while back I created an account for myself at the instance. (After all, a big part of my research is to generalize regular icosahedra to higher dimensions and complex coordinates.) There I am: Blake C. Stacey ( It’s been fun so far.

It seems the best way to explain Mastodon to an old person (like me) is that it’s halfway between social networking, the way big companies do it, and email. You create an account on one server (or “instance”), and from there, you can interact with people who have accounts, even if those accounts are on other servers. Different instances can have different policies about what kinds of content they allow, depending for example on what type of community the administrators of the instance want to cater to.

If I ever administrate a Mastodon instance, I think I’ll make “content warnings” mandatory, but I’ll change the interface so that they’re called “subject lines.”

New Paper Dance Macabre

C. A. Fuchs, M. C. Hoang and B. C. Stacey, “The SIC Question: History and State of Play,” arXiv:1703.07901 [quant-ph] (2017).

Recent years have seen significant advances in the study of symmetric informationally complete (SIC) quantum measurements, also known as maximal sets of complex equiangular lines. Previously, the published record contained solutions up to dimension 67, and was with high confidence complete up through dimension 50. Computer calculations have now furnished solutions in all dimensions up to 151, and in several cases beyond that, as large as dimension 323. These new solutions exhibit an additional type of symmetry beyond the basic definition of a SIC, and so verify a conjecture of Zauner in many new cases. The solutions in dimensions 68 through 121 were obtained by Andrew Scott, and his catalogue of distinct solutions is, with high confidence, complete up to dimension 90. Additional results in dimensions 122 through 151 were calculated by the authors using Scott’s code. We recap the history of the problem, outline how the numerical searches were done, and pose some conjectures on how the search technique could be improved. In order to facilitate communication across disciplinary boundaries, we also present a comprehensive bibliography of SIC research.

Also available via SciRate.


Maybe I need an “I told you so” category for this blog. Quoting the kicker from The Atlantic‘s portrayal of the State Department:

“This is probably what it felt like to be a British foreign service officer after World War II, when you realize, no, the sun actually does set on your empire,” said the mid-level officer. “America is over. And being part of that, when it’s happening for no reason, is traumatic.”

Reflecting on Confusion

While I was writing Multiscale Structure in Eco-Evolutionary Dynamics, I found myself having a frustrating time reading through big chunks of the relevant literature. The mathematics in the mathematical biology was easier than a lot of what I’d had to deal with in physics, but the arguments were hard to follow. At times, it was even difficult to tell what was being argued about. A blog post by John Baez, on “biology as information dynamics,” called this frustration back to mind—not because it was unclear itself, but rather because it touched on the source of the fog.

I think the basic cause of the trouble is the following:

The application of mathematics to biological evolution is rooted, historically, in statistics rather than in dynamics. Consequently, a lot of model-building starts with tools that belong, essentially, to descriptive statistics (e.g., linear regression). This is fine, but then people turn around and discuss those models in language that implies they have constructed a dynamical system. This makes life quite difficult for the student trying to learn the subject by reading papers! The problem is not the algebra, but the assumptions. And that always makes for a thorny situation.


Last night I thought of a way to summarize why my current big research project appeals to me.

The SIC problem gives us the opportunity to travel all throughout mathematics, because, while the definition looks pretty small, the question is bigger on the inside.

For a taste of why this is so, try here:

The American Physical Society Finally Speaks

The APS, my professional organization, has made some dunderheaded moves of late, but this is more encouraging. An email from the APS president and CEO, broadcast today to the membership at large, begins thusly:

We share the concerns expressed by many APS members about recent U.S. government actions that will harm the open environment that is essential for a successful global scientific enterprise. The recent executive order regarding immigration, and in particular, its implementation, would reduce participation of international scientists and students in U.S. research, industry, education, and conference activities, and sends a chilling message to scientists internationally.

The American Chemical Society had already spoken up:
Continue reading The American Physical Society Finally Speaks

Shorter Pinker

Wasn’t I just kvetching about Steven Pinker? Not that long ago, even? Well, some gifts just won’t stop giving. He’s at it again, this time complaining about the “anti-science PC/identity politics/hard-left rhetoric” of the March for Science. It might have been obvious to some of us ten years or more ago that basic respect for empirical data had become a partisan issue, but not everybody has caught up quite yet.

An academic type like me has a hard time responding to accusations of “identity politics” or “political correctness,” not because the accusations have any intellectual merit, but because the real message isn’t the words on the page. People like me, we see a thing wrapped up in the form of a scholarly argument, and we try to respond with footnotes and appendices. But the clauses and locutions are just dances around the real issue, the fundamental point that was expressed most clearly by the Twitter account @ProBirdRights:

I am feel uncomfortable when we are not about me?

Science Is Now the Enemy

No, let’s be a little more forceful than that. The news warrants that much, and it just keeps coming. For the party now in power, the people who keep rat shit out of your food and stop rivers from catching on fire are now the enemy.

I’m really not feeling that good about our ability to handle the next epidemic that comes our way.

And on a personal note, I’m a queer scientist who has published on biological evolution and the need for financial regulation. So, you can sod off with your cheery hot takes about America becoming Great Again through space exploration, or whatever the Quisling line is this week. Stuff your white dick back in your pants and sit your ass down while the adults work, m’kay?

As Of Today

The United States of America is a failed experiment.

We went out in the way a bad joke would have predicted. We lost against our own racism and sexism, our endemic illnesses whose symptoms were intensified by corrupt law enforcement and institutionally rotten mass media. Undone at the final hour by a bizarre codicil in a slaveowners’ constitution. Undone, pushed over the edge—but the edge was too close all along. When it really mattered, we proved ourselves incompetent: not able to handle our civil responsibilities, indeed, in a sense, not ready for adulthood. In the name of national glory, we have voted ourselves a government of the worst. And now a generation will grow up ignorant, poor and sick, if they get the chance to grow up at all. Many of the things we will lose will be things we can never regain, from international respect to endangered species to the lives of our loved ones.

Many good people will keep up the good fight and stir up, as John Lewis says, the good trouble.

The abyss has opened before us.

Whether the future we make for ourselves will have anything to commend it now depends upon our ability to stare into that abyss and make it blink.

Google Scholar Whisky-Tango-Foxtrottery

Google Scholar is seriously borked today. I heard about the problem when Christopher Fuchs emailed me to say that he had his Google Scholar profile open in a browser and happened to click the refresh button, whereupon his total citation count jumped by 700. After the refresh, his profile was full of things he hadn’t even written. Poking around, I found that a lot of publications in the American Institute of Physics’s AIP Conference Proceedings were being wildly misattributed, almost as if everyone who contributed to an issue was getting credit for everything in that issue.

For example, here’s Jan-Åke Larsson getting credit for work by Giacomo D’Ariano:

screenshot of Google Scholar

And here’s Chris picking up 38 bonus points for research on Mutually Unbiased Bases—a topic not far from my own heart!—research done, that is, by Ingemar Bengtsson:
Continue reading Google Scholar Whisky-Tango-Foxtrottery

Good News if You’re an Evil Prof, Though

This is entertaining:

Let’s say you tell your students that arm folding is a genetic trait, with the allele for right forearm on top (R) being dominant to left forearm on top (L). Results from a large number of studies show that about 11 percent of your students will be R children of two L parents; if they understand the genetics lesson correctly, they will think that either they were secretly adopted, or Mom was fooling around and Dad isn’t their biological father. More of your students will reach this conclusion with each bogus genetic trait that you add to the lesson. I don’t think this is a good way to teach genetics.

Via PZ Myers, who is teaching genetics this semester and has an interest in getting it right.

"no matter how gifted, you alone cannot change the world"