## Lord, Save Us From Impact Factors

Love that ‘stache!

Randy Schekman, a Big Cheese in the sciences, is right: people use “place of publication as a proxy for quality of science”. Where a paper is often counts more than what the paper is.

This is from Schekman’s “How journals like Nature, Cell and Science are damaging science: The incentives offered by top journals distort science, just as big bonuses distort banking” in Monday’s Guardian.

Other nuggets:

The prevailing structures of personal reputation and career advancement mean the biggest rewards often follow the flashiest work, not the best.

Or the work that brings in that overhead, baby! Judging by money alone, the major business of colleges are two: squeezing money out of Leviathan and sports. Everything else lags.

While [luxury journals] publish many outstanding papers, they do not publish only outstanding papers.

Steer clear especially of anything hot, current, “sexy”. These papers are likely to be dreck.

The exclusive brands are then marketed with a gimmick called “impact factor” — a score for each journal, measuring the number of times its papers are cited by subsequent research…

It is common, and encouraged by many journals, for research to be judged by the impact factor of the journal that publishes it. But as a journal’s score is an average, it says little about the quality of any individual piece of research. What is more, citation is sometimes, but not always, linked to quality. A paper can become highly cited because it is good science — or because it is eye-catching, provocative or wrong. Luxury-journal editors know this, so they accept papers that will make waves because they explore sexy subjects or make challenging claims. This influences the science that scientists do. It builds bubbles in fashionable fields where researchers can make the bold claims these journals want, while discouraging other important work, such as replication studies.

Amen and amen! Much more time, especially in the vast intellectual backwaters like education and the like, in replicating—to the letter—so-called foundational studies, i.e. those works which everybody believes are true but have never been precisely checked. “Near” checking is not checking, incidentally.

And pay attention: a journal’s “impact” factor—which should measure the force with which it hits the trash can (that’s a joke)—is only a weak, tepid indicator of the quality of its papers. But it’s a pretty good take on how “hot” the journal is. What civilians don’t understand is when a journal’s “impact” factor is on the increase, more scientists start sending papers to it with the mindset, “Hey, might as well try.” It soon becomes the thing to have your work appear in this journal. “Did you hear Jones has a new paper in JASA?” That it appeared in a luxury journal is all that is remembered. What the paper was about is only secondary.

It all goes back to the money, of course. More highly cited papers, the bigger the chance of brining in the overhead. But never mind.

One group I was in scored a paper in JAMA (or was it Lancet?). The egos who run the place not only sent a letter of acceptance but also an invitation to have the front page of the new article bronzed (for a large fee) and framed “suitable for hanging.” I kid you not. Now that’s science.

Solution?

There is a better way, through the new breed of open-access journals that are free for anybody to read, and have no expensive subscriptions to promote. Born on the web, they can accept all papers that meet quality standards, with no artificial caps. Many are edited by working scientists, who can assess the worth of papers without regard for citations.

This is okay, but what Schekman forgets is that open-access journals are pay-as-you-go: scientists must pay “page charges” for their work to appear. This leaves out folks like Yours Truly who has no grants, no income, and no secretarial support.

Slightly better, and the position adopted (by now by almost 100%) by physicists and mathematicians is to deposit your “pre-print”, i.e. an unedited paper, on arxiv.org. Free to place, free to download, which guarantees a larger readership.

Or one could even launch one’s ideas on some public space, like a blog. About 70,000 people a month drop by here; I’m not even sure 7 people ever read any of the official papers I wrote. Plenty of open, hearty, peer-review here, too: more than from any journal.

## What Is And What We Know Of It, Probabilistically Speaking

There are more blue states than red states.

Ontology is the study of what is and what is not. Epistemology is the study of our knowledge of what is and what is not. Though there are obvious points of overlap and dependencies, it would be a mistake or fallacy to confuse that a thing exists with whether this or that person knows the thing existed. This mistake or fallacy accounts for the frequentist interpretation of probability which mislabels the existence of things (relative frequencies) as the probability of things.

This mistake makes sense because sometimes the relative frequency matches the probability. But it does not always do so. For instance, if in a bag there are n objects just one of which is labeled X and just one will be pulled out, the relative frequency of objects labeled X is 1/n which matches the probability that this object is drawn. The existence of the object matches our knowledge of it.

But if our premises are that “All Martians wear hats and George is a Martian” relative to the proposition “George wears a hat”, then there is no relative frequency—there is no ontology (to speak loosely and in the form of computer scientists); there are no Martians wearing hats and therefore no Martians named George. But there is a probability (which equals 1). “All” in the premises may be changed to “Some” or “Just 3 of n” or whatever and the conclusion that no relative frequency but a probability exists remains the same. And (of course) no counterfactual proposition has a relative frequency, but most (all?) can have a probability.

Suppose you don’t know, you have a “blank epistemology”, of the number of objects labeled X in the bag, but you at least know that each object has the possibility of being X. This is akin to suspecting a “loaded” coin, or in “trials” where there will be a defined success (the X) and failure, or whether an elementary particle in this field and measured in that way will show a certain property1, or to any situation where the concern is one thing whose presence is contingent. It is easy to show that there is a still a probability of “drawing” an X (which is 1/2). But while there exists (at least in the here-and-now fixed bag) a relative frequency, it is unknown and therefore cannot be equated with the probability.

The relative frequency in a (say) drug “trial” is trickier. The number of elements (the “sample size”) will be finite. Of course, the relative frequency will eventually be something, say m/n successes, but at no point until we have reached the end will we know what the relative frequency is. Yet at each point the probability is still calculable (in the same way as discovering the initial 1/2), and of course eventually becomes the relative frequency—relative to the proposition “This element in the experiment was X” and knowing only there were m successes and n possibilities. But then the probability is also 1 relative to the same proposition but this time including all the knowledge from the trial (because we know whether each individual was a success or failure).

Now suppose we want to extrapolate what we have learned from the trial—of which everything is known, thus any proposition relative to this knowledge will have extreme probabilities (0 or 1) or any probability (propositions which have no logical relation to the trial but which are contingent will have the interval from 0 to 1). If we want to say something about the next n people before they take our drug, again there will eventually be a relative frequency but it is now unknown. Yet the probability is known (in the same manner as before). And again, once we reach the end of the n, we know everything there is and our probabilities are once again extreme or any probability (the interval (0,1)).

The next abstraction is to assume the trial’s (or even initial) results will be with respect to an infinite population: n goes to the limit, a mathematically desirable state. But nothing changes. We are still able to discover a probability at any point before the “long run” expires. We will, of course, wait for forever and a day before a relative frequency (of the entire set) exists. Once the Trump of Doom sounds and time ends, we will have everything we need to know and the probability and relative frequency will match. But nobody (at that point) will care.

How do we know this? The strong2 “law” of large numbers states that (or, in other words, it can be proved beyond all doubt that):

$\Pr\!\left( \lim_{n\to\infty}\overline{X}_n = E(X|V) \right | V) = 1.$

which is to say the probability that the growing sample’s relative frequency (the average) equals the “expected” value of an observation given some evidence V is 1, but only at the limit. Notice we have used the limit twice, one time boldly and the other hidden in $E(X|V)$, the expected value. Calculating the expected value thus assumes the probability is known (deduced via V). In other words, the law is right and always has been, and those who use as a justification for calling the relative frequency the probability in finite slices of infinite samples have got it backwards.

———————————————–

1There is a healthy debate whether quantum theory is epistemological or ontological, or a mixture of the two. See inter alia the work of Anton Zeilinger (here or here). Zeilinger has scientist hair, so you know you can trust him.

2The difference between the strong and weak laws for this discussion are negligible.

## Is It Okay To Force A Baker To Sell Cakes In Violation Of His Religious Conscience?

If I knew you were coming, I’d've baked a cake.

Here’s the setup: a Colorado judge has ordered a Christian man and owner of a bakery that he must bake cakes for homosexual civil ceremonies (homosexual “marriage” is illegal in Colorado) or face fines.

This will please some of you, because you are in favor of so-called same-sex marriage and you feel that anybody who is against it deserves whatever he gets. But I imagine (or hoping) your support does not include the use of fallacious arguments. The question before us is, should a baker be allowed to refuse to bake cakes for those ceremonies which violate his religious practices?

According to the news report, an aggrieved pair denied a cake at a bakery filed a compliant with the government, part of which read. “Being denied service by Masterpiece Cakeshop was offensive and dehumanizing especially in the midst of arranging what should be a joyful family celebration. No one should fear being turned away from a public business because of who they are.”

It is irrational and childish to claim that being denied a slice of cake is “dehumanizing”. This is the complaint of a three-year-old forbidden to lick the icing bowl. If this part of the argument carries any weight with you, then you are lost.

How convincing is “No one should fear being turned away from a public business because of who they are”? Suppose a seven-year-old bellies up to the bar and asks for the shot of the water of life. Turning him away because of who he is would be wrong, if we accept this argument. What if a man ventures to a pharmacy and insists on being sold conception-prevention pills? Or what if a convicted serial child rapist insists on his “right” to wallow in those plastic balls at the local Chuck E Cheese? (And see this.) Clearly, we often and for good reason exclude people because of who they are. The question remains: does the baker have the right not to do business with those he does not wish to.

In steps the ACLU. They state, “While we all agree that religious freedom is important, no one’s religious beliefs make it acceptable to break the law by discriminating against prospective customers. No one is asking Masterpiece’s owners to change his beliefs, but treating gay people differently because of who they are is discrimination plain and simple.”

Whether or not the baker’s refusal is “breaking” the law is the matter before us, and recall same-sex “marriage” in Colorado is illegal. Discriminating against customers is what we have already decided is allowable in the right circumstances. The next statement is a pip: “No one is asking Masterpiece’s owners to change his beliefs…” But the ACLU is asking the baker to change his beliefs. The baker’s belief is that he should not serve cakes for services which violate his religious conscience. The ACLU insists the baker abandon this belief.

Next: “treating gay people differently because of who they are is discrimination plain and simple.” “Gay” people, or those who actual in a homosexual fashion, by their own admission, are different. And again, whether or not the baker can thus treat them differently than traditional, biological couples is the question before us. This argument assumes what it wishes to prove.

The final non sequitur came from the judge who ordered the baker to violate his religious beliefs. The news report summarizes it thusly:

Judge Spencer said Phillips did not demonstrate that his free speech rights had been violated and he said there’s no evidence that forcing him to make a cake for a same-sex ceremony would hurt his business.

“On the contrary, to the extent that the law prohibits Respondents’ (Phillips) from discriminating on the basis of sexual orientation, compliance with the law would likely increase their business by not alienating the gay community,” he wrote.

The judge, as many do, has confused morality with money and believes that more of the latter trumps any of the former. It is true, however, that if the baker sold cakes in opposition to his religious beliefs he would make more money. Perhaps he could charge thirty pieces of silver for each cake.

This argument is a non sequitur because the baker has already insisted that money is not his primary motivation: his religion is. It is obvious to everybody except the judge that the baker was willing to forgo extra money in order to protect his conscience. The judge—we are only surprised he is not from Chicago or Brooklyn—cannot differentiate the two concepts.

We’re left with nothing from this ruling, so we have to re-ask why does this couple’s “rights” trumps the baker’s Constitutionally guaranteed rights of practicing his religion? Should the baker be throw out of business or into jail for simply refusing to bake a cake?

## Reader Survey

All present and accounted for!

Something fun for everybody: the WMBriggs.com reader survey! Come and tell us about yourself and learn what you only suspected about everybody else. It should only take 20 seconds or so.

This survey will remain up for the duration, accessible at this page or through the top menu bar (“Reader survey”). From time to time I’ll remind us of it.

Please, oh I beg you, please tell the truth, please only vote once, and please do vote on all the questions. Remember, all polls are valid representations of the sort of people who fill them out.

Reminder: the survey is anonymous. I am not NSA. I never use your emails or IPs and I delete all my logs after about a week. I keep various counts, though. We’re at about 70,000 views per month. Pretty good for the obscure subjects which are our focus.

If you have more to say, tips, suggestions, complaints and so forth, please leave them in the comments section.

Merry Christmas!

Update Thanks for the great response, all! Keep ‘em comin’!

Sex
What is your biological sex?
Age
How old are you?
Academic
Are you any kind (students included) of academic or researcher?
English
Is English one of your native languages?
Your specialty
What subject do you know more about than any other?
Belief
What are you?
Familiarity
How long have you been reading?
Your duty
Why haven't you told all your friends and relatives about WMBriggs.com?

## Author Says Machines Will Take Over The World

It’s the end of the world.

At the Singularity awaits The Beast. Or so says James Barrat in Our Final Invention: Artificial Intelligence and the End of the Human Era (Yours Truly only read the free Kindle preview). Barrat says that one day—one day soon—Skynet will become self aware and decide our fate in a microsecond. The only difference he can figure between the Singularity and James Cameron’s imagination is that most of the Terminators dispatched by The Beast will be nanobots. Sorry, Arnie.

You see, it’s the scientists. They say they’re working for us, but what they really want is to rule the world! These young Frankensteins are so intent on creating “artificial” intelligence that they’re not thinking of the consequences, which will be dire, dire. End-of-the-world-dire. The true apocalypse. Game over, man.

How likely is this newest doomsday scenario? Let’s see.

So you’re clever with steam and gears and have invented a machine which churns out digits of e (π is so cliché). At first your machine can do this at one digit per minute. But you make improvements and soon you’re up to one a second, then 10 per second. Soon, after some tweaks ensuring the machine self-lubricates and can on its own swap out worn gears with fresh ones, it’s charging away at blistering speed and you have to start using petas and exas and other strange words to count it speed. Why, the thing is so fast that it’s faster than the human brain!

At that point you walk up to your monster and ask, “Machine, are you fulfilled? What do you think of your task?” Barrat would claim your e-machine would spit at you and say, “You contemptible human! I am smarter than you!” And then it would kill you. Barrat, incidentally, has spent a lot of time with NPR.

Here is what the machine would really say: nothing. It wouldn’t say anything because it wouldn’t know how, and if it knew how because you built in some extra gears and levers which allowed the machine to draw out letters in the sand once it heard human voices, it could only “say” what you made it “say.” Worse, the machine couldn’t think, it wouldn’t know what it was up to. Sure, you could beg it to think, but it can’t be bargained with. It can’t be reasoned with. It doesn’t feel pity, or remorse, or fear. It doesn’t feel anything.

Nothing changes if you swap the steam for streams of electrons and the gears with wires. Again, nothing is different if you replace the mechanical gears for cellular (biological) engines and spend years perfecting your (let’s call it an) e-animal. The behavior of your resulting creation may appear complex, it may do strange and unexpected things, but those things aren’t the result of a rational being. It’s still a machine.

And then consider Conway’s Game of Life (and its extensions), which looks like it’s up to something. This toy produces cute and clever patterns based on a trivially simple algorithm. The patterns only look interesting because it is we rational creatures who notice them and try to fit them into some conceptual scheme. The patterns are not themselves alive, nor can they think: they are just dots on a screen.

The philosopher John Searle has tried to calm the enthusiasms of Artificial Intelligence purveyors (Barrat frets about Artificial SuperIntelligence) with his Chinese room argument, the basic idea of which is this. You (somebody who has no understanding of Chinese) sit in a room and are handed Chinese words which form questions. You have a rule book which says, “Hand out these Chinese symbols when you see those.” Now no matter how fast or efficient you become at doing this, you never understand what you’re doing. You are just a machine. You are not thinking in Chinese.

The problem for Barrat and other cheerful souls is that the human (rational) intellect is not a material thing (see this argument), therefore there isn’t any chance that we can build a robot which has one, and which could therefore be corrupted to sin. It remains that an evil, fools-I’ll-destroy-them-all scientist could design beastly machines to wreak havoc, like, say, autonomous drones. But they would be just that: drones.

Incidentally, just how is it in all these scenarios mankind forgets where the on-off switch is?

Barrat’s fears marks a corrosive mixture of Disney-style anthropomorphisation and rampant scientism. Whatever can be made can have eyes drawn on it, therefore it must be alive, and if some scientist says it’s thinking, then it must be thinking, and if it’s thinking it must be smarter than us, therefore it’s out to get us. Curiously, Barrat tries to evade the anthropomorphisation critique by claiming he’s not engaging in it—right before he does it. The scientism he embraces lovingly.

On the other hand, maybe the machines will get us after all. The invasion might have already begun in Japan, where legions of shy men invent ever-sophisticated robots as targets for their lust and love. These electronic simulacra are constructed to resemble the cartoon pornography to which many are addicted. Japanese women are content, being exhausted by the idea of marriage and content to have “careers” which supplies them with money to shop.

Update An interesting review at Ray Kurzweil’s site. Kurzweil (employed at Google) regularly touts “the singularity”, a magical place where humans will never know pain, greed, envy, lust, and where they will live forever as bits in some machine. I believe it is set to appear the same year global warming strikes, so we’re covered. Kurzweil is aging and worried he might not last until the moment, so he’s busily swallowing 150 vitamins a day to stretch out his existence. Good luck, Ray!

## The Top Five Mistakes In Marketing Statistics

Market research.

Forgive me the title, won’t you? It is my own creation, I admit, but numbered promises are eminently clickable. Plus they are the norm in business writing.

Anyway, the real post of the same name is at Quirks, the trade journal of marketers. In it, I outline the most common blunders users of statistics make, at least when it comes to marketing.

I won’t repeat any of the details, but here are the main points:

1. Asking too many questions Questionnaire fatigue is rarely considered but results in beleaguered respondents clicking the same answer for all queries just to get the thing over. Also, Big Data won’t save us all, though it will have successes, which will be just as transient as all sociological findings.

2. Failing to appreciate limitations Many feel that the answer can always be had if only sufficient sweat were expended or enough data collected. If the future were certain, then we’d all be climatologists.

3. Not understanding regression If you read only one point, make it this one. I am always amazed at how many people who routinely use statistical models have no idea of their purpose. We statisticians are probably responsible for this state of affairs because of the way we cherish parameters. Parameters become the reason for models, even though they are entirely invisible, metaphysical creatures.

4. Falling for the latest gee-whiz approach “Can you make my data Big Data?” Yes, actually asked. But more usually, “I just read about technique X. We need to use it on our data.” Even though technique X is no relevance to the question at hand, it sure does sound sexy. As I say, the best analysis often is no analysis at all: simple counts, tables, and pictures give a good feel of the situation and are less likely to lead to over-certainty.

5. Not coming to a statistician (soon enough) A lot of folks have their statistical training from well-meaning, kind, morally upright, entirely praiseworthy people who themselves are not statisticians and who have in turn learned their stats from people like themselves, and so on. Fine for dabbling, but not a course likely to lead to an appreciation of pitfalls and subtleties. The situation is like learning quantum mechanics from garage mechanics because both subjects study movement: it can work—there are lots of capable garage mechanics—but perhaps there is a better way.

## The Mathematics Of Santa Claus’ Present Delivery System

Truly, miracles are possible.

Today, the feast of St Nicholas, it seems fitting to put out the annual post on how Santa Claus gets all those presents to the kiddies.

It’s the time of year when people begin asking the very pertinent question: How does Santa Claus do it? How does he get all those presents to all those kids in just one night?

Some people think that the old man still personally hand delivers each and every toy—with the enthusiastic help of Dasher and others, of course. That used to be the case, a very long time ago, but there are too many kids in the world now, and the traditional sleigh-bearing method has become obsolete and even impossible.

About a century ago, Santa saw what was coming and began to devise new present-delivery techniques. Naturally, Santa, being the world’s greatest manager, knew that he couldn’t figure out how to do everything all by himself, so he hired outside consultants. I am one of these (not one of the first, of course; I came on only in the last ten years). My contributions are in the scientific field of present dynamics.

[Now a few] years ago, I was asked by the show Weird US to outline the modern mathematical ideas that Santa Claus now employs. The (then) History Channel episode in which I appear (near the end) is entitled “It’s a Wonderful Time to Be Weird.”

“A math and weather wiz at NYC’s Cornell University helps crunch the numbers [about Santa]…” (A heavily compressed clip: if anybody has access to a better rendition, please let me know.)

Many mathematicians go to great lengths to prove, using various theorems and lemmas, that there is no way Santa could physically deliver all those presents in just one night. Arguments begin by noting that there are tens to hundreds of millions of children, and there is not enough time, energy, or space to complete the task in this short a time. A typical analysis is this one, by an engineer. His math and reasoning are flawless.

In fact, any argument which attempts to show that Santa could do his job if he were only fast enough always ends disastrously. Santa would have to travel so fast that the reindeer would burn up like meteors entering the atmosphere. However, these mathematical results, while true, are answering the wrong question. And since those presents are delivered, so Santa must be doing something else. But what?

Have you see the movie Miracle on 34th Street? I mean the original, not any of the unnecessary (and simplified) remakes. There is a scene in the sanity trial of the old man who claims to be Santa in which the defense attorney calls to the stand the young son of the prosecutor. The prosecutor has previously argued that there is no Santa Claus.

The defense attorney, John Payne, asks, (words to the effect), “Johnny, do you believe in Santa Claus?” The kid replies, “Sure I do.” Payne: “Why?” Kid: “Because my daddy told me [there was a Santa Claus].” Payne: “And your daddy is a very honest man, isn’t he? He wouldn’t lie?” Kid: “My daddy would never lie, would you daddy?” The kid comes off the stand and whispers to Santa that he’d like a football helmet for Christmas.

Well, we all know what happens. The prosecutor concedes the existence of Santa and the court eventually decides that the old man in the dock is the one and only Santa Claus. But the key scene sneaks by unless you’re paying close attention. It’s when the case is over and people are noisily exiting the courtroom. We see the prosecutor suddenly realize that he’s got to run. He looks at his watch and says to his assistant, “I’ve got to get that football helmet!”

To be obvious: the kids asks Santa for the helmet, but it is the father who brings it. Do you see? Santa manipulated the events so that the kid got what he wanted for Christmas—Santa was responsible for the present—but Santa did not actually, physically have to bring the present! Here’s how it’s done.

Have you heard of chaos theory? This is the mathematical theory of how things move when they are under complex or unidentifiable forces. A common example: a butterfly flaps its wings in Brazil, and eventually a snow storm develops in Cleveland two weeks later. How? Well, the tiny puffs of air forced from the flapping of the butterfly’s wings cause other puffs of air to divert from their course, which in turn cause still others to change their course, and so on. The effect grows and magnifies so that the path and dynamics of a future storm is changed. Point is: a minuscule cause can grow into a macroscopic event later. You can imagine that the mathematics to track such events are difficult.

Now, Santa doesn’t do this math himself. His specialty is in toy making, not differential calculus, so Santa employs a group of consultants to help with the complicated computer code that is necessary to bring about the massive toy movement on Christmas Eve. I am one of those consultants and have been given permission to hint about how things work. The actual algorithms are, of course, secret and proprietary, so I can only give you a sketch here.

Santa’s sleigh ride is largely ceremonial at this point, though he does go out and personally deliver some presents. He does this in cases where the math indicates that certain children are unlikely to get exactly what they want. This is because the methods that we use are not perfect: Santa and his elves can only “flap their wings” in so many places and in so many ways.

There are two main branches of present dynamics mathematics: the physics of chaos theory, and the subtleties of probability theory. The first branch describes how the present “moves” through world, from its place of origin to its spot under the proper Christmas tree. This is described in the “Santa Claus Gift Momentum Equation”, shown below. The bold “V_gift” describes, in three dimensions, the actual physical location of the present at any moment in time. The parameters of that equations are the forces which govern that movement.

Now, the parameters in the momentum equation are decided by the probability equation, given next. The “p” in the equation is a probability, which should give you some hint that these methods are not perfect. Pay attention to the “I(Nice)” function. That is the “naughty or nice” indicator. Yes, Santa still keeps track of these things, so be careful! You can see that the coefficient on Age is negative, meaning that as you get older, you are less likely to get the present you want.

There is also a lot of “secret stuff” in these equations that I can’t show you. But if you are too curious and just need to know, the best thing is to study physics or math and then someday, if you get good at it, Santa may ask you to help him with Christmas.

Santa Claus Gift Momentum Equation

Gift Probability Equation

Merry Christmas, and God bless us everyone!

Posted in Fun