The Case of the Incomprehensibly Big Super Volcano

The Yellowstone Super Volcano is every American's favorite geological Apocalypse-in-waiting.* Every 700,000 years, give or take a few hundred thousand, this buries a significant portion of the western US in various astounding superlatives. But this article on the recent 4.8 earthquake at Yellowstone has the biggest (and silliest) superlative I've come across in a while. The article states that,

"Late last year a new study into the enormous super volcano found the underground magma chamber to be 2.5 times larger than previously thought — a cavern spanning some 90km by 30km and capable of holding 300 billion cubic kilometers of molten rock." 

Now, 90*30=2700, and 300 billion over 2700 is 111,111,111.1111, or a bit more than 110 million. So for the volume of the cavern to be 300 billion cubic kilometers, the cavern would have to be 110 million km deep, or roughly 8700 times the diameter of the earth, about 2/3 of the distance to the sun. That is one deep hole. With the utmost respect to the Ragnarokian prowess of the great and powerful Super Volcano, I question whether its magma chamber is roughly one third of the entire Earth. Rather, I suspect that this is another case of innumeracy (or at least i-unitacy) on the part of a reporter. 300 billion cubic kilometers of molten rock is not likely, but 300 billion cubic meters of molten rock is quite plausible. A cubic kilometer is a billion cubic meters, so 300 billion cubic meters is 300 cubic kilometers, which is about how big you would expect a 90*30 km cavern to be. Still figuratively, but not literally, astronomical.

The fact that reporters often don't understand units and don't do the basic arithmetic to check numbers is nothing new, but it has only just occurred to me that there is a systematic bias in this. As when NPR casually mentioned the "240 mile deep water" off Alexandria, or when I heard on the radio that a local bank was receiving a bailout in the hundreds of trillions of dollars, reporters always seem to get the numbers wrong in a way that grossly exaggerates the claim. If the magma cavern was stated to be 300 billion cubic millimeters (equal to 300 cubic meters) instead of 300 billion cubic kilometers, a reporter or editor probably would have found that unsatisfying and therefore caught the mistake. If it was instead 300 Sextillion cubic meters, it would look sexy and nobody would likely question it. But there is probably another bias at work. Once a number is really big, substituting another really big number generally doesn't change the impression much, and if one doesn't understand what the numbers mean, it is therefore equivalent. Incomprehensibly Big = Incomprehensibly Big. So overstating your case by a factor of a billion isn't go to raise nearly as many alarms as understating it and thereby eliminating the hugitude.


*You only think you prefer that tired old tectonic fault.

Despair not!

My prediction for hiring success has improved significantly over the past few days, for reasons both rational and irrational.

Rationally, I’ve started to receive more good applications, if not fewer spamly ones. I suspect that this is because the people who are preparing position-specific applications are taking their time to do it, as our deadline is not until April 30th. Also, it being spring, many graduate students are just finishing their thesis defenses and looking for positions.

Irrationally, I have been speaking to people’s references, and the references are of course enthusiastic about the applicants. I knew this was going to be so. I am well aware that the applicants wouldn’t have listed these references if they were going to say terrible things about them, and that the references feel a sense of obligation to say good things, but hearing great things about an applicant from a basically rational and honest colleague inevitably improves my view somewhat. It makes the applicant seem more like a person, and less like a CV. I don’t have any basic predilection to like CVs, but I like most people.

The demographics of evolutionary demographers

A group of us considering organizing a new scientific society have been compiling a list of those we would like to invite to the initial meeting of the society, to be held here in Rostock, probably next year. We are up to 125 people (excluding people who work here, as everyone who works here will be invited). The group making this list is about half male, half female. The list is 100 males and 25 females.

Why this skew? We each listed people whose names came to mind, and in some of the subfields we are drawing from (e.g., mathematical ecology) almost all of the well known people are male. Higher level academics in general still skew strongly male, and the higher the level the stronger the skew, in most cases. This is both a cohort effect (older cohorts of scientists are both more well known and more male) and a selection effect (males find it easier to advance up the ladder). Being demographers, we are very much aware of this, and are very much interested in having a diverse society, but it is not clear what we can do about it. There is also a preponderance of Europeans, North Americans and East Asians; again this is unintentional and difficult to reasonably address.

Despite these skews, it is a wonderful list of researchers, and I hope we can get most of them to attend.

High r strategy in a high k regime

I have thus far received 39 post-doctoral applications. Of these 29 were immediately rejectable on the criteria that the application did not include the documents requested. Most of the 29 I couldn’t even tell which position the applicant was applying for, or that they had read the ad. About half of these also contain a similar mix of muddled excessive politeness and jumbled frilly clauses, as though they are cut and pasted at random from the same absurdist form letter. I have no doubt that these are smart, competent people, and perhaps this broadcast spawning strategy of application works in some fields or some countries, but my experience suggests no circumstance under which it would be effective.

Whenever I am hiring, or reviewing applications, I ask myself if I am expressing any unintended biases. I was warned by a friend to expect a large number of irrelevant applications out of India and China (where indeed most of the applications have come from) and so now I force myself to consider in detail whether each of these applications may be more relevant than it at first appears. So far if there is any doubt I have refrained from putting them in my reject folder, meaning that the 10 applications I haven’t yet rejected outright contain a few that I probably should. They also contain a few well worth consideration.

We listed April 30th as the application deadline, so I hope most of the people particularly interested in our positions here are simply taking their time to prepare a high quality application.

The right's next big scare tactic

My office mate occasionally organizes a movie night, showing something or other that people at the Institute might want to watch in the seminar room. When he heard that there were two movies, called Demographic Winter and Demography Bomb, he figured they would be of interest to an Institute full of demographers, and he got a copy of the DVDs from somewhere.

Twenty or thirty of us came to watch. Now Demographers are a pretty staid crowd, but by ten minutes in people were chuckling, and within a half hour there was full-bellied, breathing-difficulty, rolled over in pain laughing going on. Clearly, people who actually think about demography were not the target audience.

These two documentaries, are based on the premise, which they take intensely seriously, that humanity (or at least the white section thereof) is at risk of economic ruin, political chaos, pain, suffering, homosexuality, the death of the traditional family and ultimate and total extinction because of a population control conspiracy by the UN, the EU, the Ford Foundation, Democrats, Liberals, Communists, UC Berkeley, Charles Darwin, Malthus, W.E.B DuBois, Gloria Steinem, Big Gay, Nazis, Feminazis, and most of all Paul Ehrlich. Dr. Erhlich, a professor at Stanford is a favorite punching bag of the right because he made many and varied dire predictions back in the sixties and seventies, and like most prolific prognosticators, many of his forecasts were wrong. His 1968 book, The Population Bomb, is identified as the driving source behind the idea that overpopulation might be a problem. In it he made various overly pessimistic predictions about the rate of population growth and the rate of food productivity growth, and concluded that we would see mass starvation of hundreds of millions of people by the 1970s or '80s. That this didn't happen is taken as proof that there are no possible ill effects of overpopulation, and that in fact humans are now heading toward population decline, which will by the end of the century see an under populated world dominated by geriatric patients, Muslims and Latinos. The same three or four animated graphics are shown incessantly, demonstrating that "westerners" (i.e., white people) are going extinct. "By the end of the century, there may not be any actual French people in France." They string together statements from representatives of various Teabagger interest groups and wildly out of context statements by academics (often repeating the same clip of the same academic to make it seem like they are agreeing with two very different ideas) with alternatively faux-reasonable and openly snarky narrators. The failure of the US auto industry, the housing bubble, immigration, homosexuality, terrorism, crime, feminism and the excesses of Wall Street are all shown to be symptoms of insufficiently rapid population growth. Demographers from all over the world hooted and guffawed and thought it was just the funniest damn thing they had seen.

Now like most vehemently presented lies, there is a grain of truth to the hysteria behind the movie. That grain is this: some, but not all, population forecasts predict that world population will cease growing some time around 2050, and may gradually decline for some decades thereafter, falling from maybe 9 billion to maybe 8.5 billion by 2100, and in the mean time the ratio of older people to younger people will temporarily increase. (Forecasts any further out than that are beyond the realm of speculation into pure fantasy, but one thing we can say with high confidence is that no population is likely to just stop breeding and go extinct.) This will pose some serious issues we need to think about over the next few decades. (I've written about this before, here.) Our markets, as currently structured, assume continuous population growth, and we don't yet have very clear ideas about how we need to adapt to population decline if it happens. Having lots of old people per working adult is a problem if you assume that it takes the same number of working adults to take care of each old person, and ignore that their will simultaneously be fewer children for those adults to take care of. The problem with the argument, even if you take out the hysteria, conspiracy theorizing, snarkiness, smear tactics and brain-washing techniques, is that overpopulation has known, current and disastrous consequences (see "Collapse" by Jared Diamond for several hundred pages on that, also a significant portion of the articles in Population and Development Review or Conservation Biology). I have never met a demographer who argues the problems of population decline are likely to be worse than those associated with population growth, or with trying to maintain a planet with more than 9,000,000,000 people on it. Second, I've never heard any demographer suggest that the cause of the eventual decline will be anything resulting from any policy of population control. Rather, educated, urban, mobile populations (and especially educated women) have fewer kids later in life, and that slows population growth. As the educational level and economic mobility of the world's women improves, and as people continue to move to cities, they will tend to reproduce less, no matter what the UN or Professor Ehrlich tells them. The clergy also have relatively little influence (see Italy).

But now that the lie is out there, no matter how laughable, it is a convenient tool for anyone who wants to argue against population control measures, family planning, contraception, feminism, etc. A friend pointed out to me a post on The Weekly Standard's blog stating that, "the discussion in demography circles isn't 'How do we cope with two extra China's?' Rather, it's "'How do we manage one of those extra China's disappearing?'" Living in a "demography circle," I can report that the Weekly Standard's unnamed source for that statement is a made-for-Fox-News propaganda special called "Demographic Winter" and its sequel (which borrows numerous lengthy sections from the first part) called "Demography Bomb." Type "population decline" into Google blog search and up come numerous posts on conservative blogs mumbling the same point.

So while my international colleagues were laughing their lungs out, I was exchanging dark glances with the only other American in the room. To those not familiar with the propaganda machine of the U.S. far right, the movie was pure, bizarre, hilarious fluff. Man-eating purple platypus stuff. One of my colleagues later asked me, "Republicans aren't idiots right? So they do not take that [compound expletive] seriously. Maybe a few nutballs? This is a joke?" But to me, it was clear this was yet one more battle being opened in the American right's war on science. As long as one is denying evolution, climate change and the moon landings, may as well claim that demographers don't see any possible drawbacks to overpopulation, and in fact that population collapse is just around the corner.

Expect to hear more of this particular lie in the years ahead. As the right touts the four biologists willing to deny the possibility of evolution, expect them to repeatedly trot out the few demographers willing to pretend that humanity's very existence is threatened by population control.

The climate tempest's teapot

You may have noticed the recent hullabaloo about the stolen email records from the Climate Research Unit at the University of East Anglia. The people who hacked into the system, and the climate-change-denier community generally, have taken the content of these emails as proof positive that climate science is all one big hoax. What they actually have is evidence that on one occasion one climate scientist informed his colleagues that he was doing some mildly misleading things to one graph to make it look prettier. Clearly he shouldn't do that, but this is proof of basically nothing beyond itself. I won't dwell on the point. Those who can't accept the global flood of evidence for anthropogenic climate change are not susceptible to logic or evidence, and none of the seven regular readers of this blog are among that crowd.

What I think is interesting about this is the extraordinarily high level of truthfulness we expect from our scientists these days. Journalists, politicians, doctors and lawyers are all expected to, in varying degrees, present pictures which are rosier, clearer, more advantageous or less illegal than the straight hard truth. A defense attorney is expected to find the most preferable interpretation of truth, rather than the straight up truth. Doctors need to make their patients feel comfortable and confident, even if that means overstating their confidence. No one is surprised when Republican appointed judges reach different decisions than Democratic appointed judges. Text-book writers are free to get as much wildly wrong as they want, usually for no apparent reason. Advertising is the art of misleading without directly lying in a provable way. But Phil Jones, the guy who fudged the graph, is resigning his appointment.

This is not to say that I think this level of expectation is a bad thing. Scientists don't have the excuses for bending the truth that lawyers or doctors or journalists have. We are supposed to fight desperately hard against our biases, against anything that prejudices our communications or thinking. Of course realistically many scientists fail to live up to this ideal, and there are (and should be) consequences when these failings are exposed. But one of the many things reactionary deniers of all sorts (moon landings, evolution, Holocaust, climate, HIV/AIDS, etc.) tend to refuse to see is that science also has powerful mechanisms for keeping any one person's malfeasance from making too much of a difference to our larger understanding. The more respected and influential a scientist is, the more people there are looking to poke holes in everything he does. The more enshrined an idea is, the more it benefits the career of a young researcher if she can point out a fatal flaw, an exception, a modification, even an unexplained corner. Every scientist that was ever great built his or her reputation and career by finding flaws, limitations or unanswered questions in the work of older, more established scholars. If I could produce convincing evidence that macroevolution doesn't happen, I would be the most successful scientist of the century (unfortunately for me, macroevolution happens, so producing that evidence is going to be hard). Under such a system, fakery may help get a single paper published, even help build a successful career, but it can't easily lead to a lasting consensus that is contrary to data that somebody else can go out and collect, because somebody is always trying to tear a hole in anything that could possibly be torn. The single best argument for anthropogenic climate change is that nobody has yet succeeded in blowing a hole in it.

Publication bias

Much of the culture and methodology of science has been specifically designed to help combat bias. The human brain takes sensory inputs, filters them through our biases before we even perceive them, assigns them whatever interpretation seems most reasonable given what we already think, stores them (or not) depending on how they fit into our preconceived notions, and then retrieves them when they seem to support the view we already have on the topic at hand. We are like perfect bias machines, and we have to bend ourselves into all sorts of intellectual contortions to achieve any measure of impartiality on almost anything. Most of the statistics scientists employ, rather than testing for support for our preferred hypotheses, are designed to test for support of the opposite of our hypothesis. Only if someone tries really hard to prove the opposite of their point and utterly fails to do so are we convinced that their data significantly support their point. The scientific review process, the sometimes painfully stilted manner in which science is written and even the reluctance of many scientists to have any polling based system of evaluating scientific consensus are all designed to help us keep our biases in check. The Spockian view that one should act as though emotions and unreason don't exist is clearly illogical.
Despite all this anti-bias fervor, scientists are still human, and still have biases. One such bias is that we want, as individuals, to be successful. We would rather study a topic that is going to win us praise, jobs and funding than something else that will take a long time to reach any conclusion, even if the payoff for society is much greater for the long term project. We are also far more likely to publish results that are going to advance our careers than those that won't. This leads to the title of a 2006 paper called, "Publication Bias: The Problem That Won't Go Away." To be clear, I am not referring to a reluctance to publish papers that challenge the dominant viewpoint. Name any truly successful scientist, and I will bet you that his or her career was built on a paper that challenged the dominant viewpoint. Scientists know this, and we are pretty much obsessed with finding holes in the dominant view. Publication bias rather is most commonly a tendency to publish clear positive results ("our data strongly support hypothesis X over hypothesis Y") over the less clear cut cases ("our data do not allow us to confidently support or refute the hypothesis we set out to test"). This kind of thing happens a lot.

Publication bias on the part of others, and by me, has been on my mind recently. In writing a paper on the evolution of paternal care in primates, I ran into the problem that almost nobody makes the statement, "in 72,000 hours of behavioral observation we did not observe males caring for their young." But if after 120,000 hours of observation they see a male pick a couple of burrs out of a juvenile's fur, they might well write a paper titled, "first observation of paternal care in species X." This results not only from the logical impossibility of proving the complete absence of a behavior, but because in many species where males don't care the assumption is that males don't care, and a failure to see counterexamples isn't that interesting to the people studying the species or the editors reviewing their papers. The result of this is that we have lots of publications stating the presence of care, even when that result is rare, but almost nobody stating the likelihood of its absence. I ended up having to make the rule that if multiple papers describe patterns of care in a species, and none of them say anything about male care, that counted as too little care to qualify. In my own studies of rotifers, I absolutely would have written a paper on parental care if I had observed any, but absolutely could not get a paper published in which I state that I didn't see any.
But my publication bias when it comes to the rotifers is much more profound than that. The results of one of my major experiments were negative, and as such not particularly interesting. I am writing it up anyway, because my dissertation committee wants me to, but I and they think it unlikely any journal will publish it. Of course if 20 different labs did similar experiments, and only one got a positive result, only the positive result would be published, creating a very false impression. I recognize this as a source of bias, I don't like it, and I don't see any way around it. The best I might be able to do is post the whole damn paper on my blog and hope that anyone interested in the topic stumbles upon it.

The other option, which I won't take but is far more common than you might think, is to simply analyze my data until I do find something interesting in there, then write up the paper as though that was my main question all along. This is something that advisers have specifically told me to do in the past, although not on this project. It is grudgingly accepted that this happens, and like publication bias, isn't going away.

The Free Encyclopedia and 'Hairless' Apes

Without having done extensive checking, I would guess that Wikipedia is the only encyclopedia in the world in which the section on primate taxonomy includes nude photos of male and female humans with all their body-hair removed.

I suppose one could argue that body hair would obscure some portion of our typically primate anatomy, or make the photos appear less clinical. That said, none of the other primates pictured are shaven, so why the humans? And honestly, human's body hair doesn't hide that much anyway. As humans are naturally the least hairy of any primate, the clean shaven models seem to me to unduly exaggerate our distinctness from other primates. I don't approve.

On further consideration of the nature of Wikipedia, the inclusion of these photos could be intended purely to annoy social conservatives who object on religious grounds to the placement of humans among the primates. In that case the hairlessness would presumably be intended to emphasize the nudity of the models.

Demographics of Science!

African Americans are generally underrepresented, both in the universities, and in the sciences. Berkeley is no exception in this case.

During my time in grad school I have interviewed well over 100 undergraduates who were applying to work with me, and taken on (as volunteers or paid workers) about 30 of them. Currently, I have 18 undergraduate collaborators. I've not given a great deal of thought to the demographics of this group, other than to notice that the great majority of my applicants (and therefore of my assistants) are female. A recent conversation (about Pres. Elect Obama) made me stop and think about the race and religion of this group. It is a very diverse group. I have had assistants who are Christian, Jewish, Hindui, Muslim and non-religious. Maybe other religions, I don't know. I have had assistants whose ancestors (or they themselves) came from East Asia, South Asia, the Middle East, Eastern Europe, Western Europe, Pacific Islands, Latin America and possibly other places I am not aware of. They have been male and female, heterosexual and homosexual. There are few places in the world where I could have ended up with a more diverse group, but I have no one of obvious African decent.

African Americans are not represented in my lab for a simple but sad reason. I have had not one African American applicant (that I am aware of), out of maybe 120. It is striking that African American representation in this group is lower than among our nation's elected officials. I am not sure why exactly this is, what combination of bias, cultural factors and public policies to blame, but I know this is one area where African Americans don't yet seem to have made sufficient inroads.

Misquotes of Science!

Science is the least precise way of describing the world, except for all those others that have been tried.

Whose next?

Of the thirteen students working with me in on rotifer work, only one is white Christian heterosexual male. This never occurred to me before yesterday, when we were sitting around the lab, talking about the fact that should Obama win, he would be the first POTUS who was not a straight white Christian man.

I asked my students if they thought, now that we were getting a non-white president, we would have a female president, a non-Christian president or a homosexual president first. Some said we would have a woman soon, others said America would elect a Jewish president before a woman. Everyone agreed that there is still too much bias against homosexuals to have an openly gay president any time soon. I asked them if they thought Americans would ever elect a scientist as president. They all said no, and a couple of them said that was probably a good thing.

Three of my students a naturalized citizens, and therefore are barred by our constitution from running for president. But the other ten, in my opinion, should all have equal shots at the White House. The fact that they are all science students studying evolution at Berkeley means that this chance is zero is bearable, so long as it is an equal and unbiased zero.

Stereotyping of students based on intended career

There is a commonly sited and widely believed in stereotype of a certain group of biology undergraduates, and this stereotype, I have reason to believe is frequently used in labs in my department to determine which students are desirable to have in one's class or section or lab, and how much responsibility and trust to give students. This stereotype is based not on race, sex, religion or socioeconomic background, but rather on intended career. I have heard faculty, grad-students and even other undergraduate students (including other pre-meds and pre-vets) rail against the pre-meds and pre-vets. At the new-grad student orientation last year the first response to the question, "What are the undergrads here like?" was, "too many pre-meds."

The stereotype goes something like this:
They only care about grades and letter of recommendation, they aren't interested in learning, they have no interest in science but will apply for any and every research position just to put it on their resumes. They will do a desultory job at any task you give them, so you may as well give them menial tasks. They are unpleasant to teach because they aren't interested and they spend all their time grade-grubbing. They are motivated to cheat by their fanatical devotion to getting A's.

This stereotype is, in my opinion, quite destructive. Not to say it has no basis in fact. I have had students who match the stereotype fairly well, both in classes and as lab assistants, and I will admit to finding myself hoping never to find myself or a member of my family in their medical offices. Our campus has both pre-medical and pre-vet undergraduate clubs, and while I have no direct knowledge of the advice these clubs give their members, the students who seem to be living up to the stereotype will occasionally say that they want the A or want the job because their pre-professional society told them so. (See here for my thoughts on how and why undergraduates should get involved in research. One important point, don't apply because your pre-med society told you you should, and if you do, don't admit to it, and if you do, expect menial tasks from most labs.) I suspect that some students really are led astray by receiving advice that emphasizes grades over learning and items on a resume over experience.

But honestly, the best undergraduates, bar-none, I have worked with have been pre-med and pre-vet. When I was a teaching assistant for Animal Behavior last year, the student in my section who asked the best questions, was the most enthusiastic and was the most helpful in explaining the material to her fellow students was a pre-vet student, very active in the pre-vet society. She also happened to get by far the highest grade in the course, but the high grade was clearly not her only reason for being there. My most accomplished lab assistant, whose thesis is nearly ready for publication, just applied to 20 med schools. I will admit to trying to talk her into a career in research, but I also have no doubt she would be an excellent physician. I could give as many examples of excellent pre-med and pre-vet students as I could examples of terrible ones.

Why do I think the stereotype is damaging though, if it is at least sometimes at least partly true? Partly because it colors interactions with undergrads. Some very large portion (well over half, I think) of students taking classes taught by my department are on pre-health career tracks. If one goes into interactions with more than half of one's students assuming that they are uninterested in learning, this affects one's teaching. If one offers only menial lab tasks to more than half of one's students, this affects their opportunity to learn about science. If instructors try to avoid teaching the classes that pre-med students flock toward, that doesn't say anything great about the educations of our pre-med students. It is also damaging if students feel compelled to live up to it. I had a pre-med students say to me that he was not interested in participating in anything that didn't contribute to his grade because that wasn't how pre-med students worked. I had the distinct impression he was striving to be the stereotype.

What actions do I suggest? The first would be for people on all levels of the department to be aware of this stereotype, and the biases it causes, and to be careful about how those biases affect their actions. The second would be for the pre-vet and pre-med clubs to make their members aware of this stereotype, and urge them to avoid being pigeon holed. Just as racism cannot be combated without acknowledging that it exists, I feel that carrerism must be exposed to the light of day.

Public warned that lead bullets make meat toxic

In an extremely important, despite being obvious, revelation, the government of North Dakota has ordered the destruction of tons of venison, after being presented with evidence that deer shot with high velocity lead bullets are not fit for eating because of microscopic lead fragments spread throughout the body of the deer.

While the science is not new, the difference this time is that the study was done by a hunter from North Dakota, rather than by the Peregrine Fund.

Note to hunters: If you shot a deer with a lead bullet and you are planning on feeding it to your family, you are poisoning them. Throw that meat out, buy some copper bullets, go shoot another deer.

Gender Biased applicants

In the time I have worked on the rotifers, I have had the following assistants:

Lauren
Myfanwy
Rose
Laurel
Chris
Phoebe
Polina
Christina
Nicole
Deanna
Willard
Vincent
Catherine

That makes 3 males and 10 females. Hardly 50/50.

I was wondering why this was, if I was in some way unconsciously discriminating against male applicants, or practicing affirmative action. So I counted how many male and female applicants I have had in the last two rounds of hiring. The most recent I had 2 male and 8 female applicants. The previous time, I had 3 male and 13 female applicants. So if anything, I'm over-hiring males as compared to their representation in the applicant pool.

What I am wondering about now is why so many more females than males apply. The biology classes in my department have a slight majority of females, but not nearly that big. My guess is that because the project specifically investigates the evolutionary basis of menopause, and women tend to be more interested in (and comfortable with the topic of) menopause, fewer males are interested.

Sloppy

I've written here before about what a poor job journalists generally do in describing science to the public. I was just reading this Op-Ed piece in the NYTimes and wincing over phrases such as "sharks are very primitive living fish" and "ensure the survival of a species," which reveal a very out of date and human-centric misunderstanding of evolution. The piece includes at least half a dozen points contradictory to modern evolutionary theory. I was just considering writing yet another response letter explaining to the author that natural selection does not favor traits because they help ensure the survival of the species, and so forth, when I looked at who the author is.

The attribution:
"Neil Shubin, an associate dean at the University of Chicago and the provost of the Field Museum, is the author of 'Your Inner Fish: A Journey Into the 3.5-Billion-Year History of the Human Body.'"

Neil Shubin knows that evolution doesn't work that way. So why is he writing like a journalist? I can only guess it is because he wants to sell more books, and someone (the NYTimes, his publicist or him) felt that one has to adopt the public's misunderstanding in order to interest them. It is sad when scientists start writing like science journalists.

Writers' Strike

It seems to me that economists should be able to quantify the value of the work of a profession to society based on the larger societal impacts of that group temporarily ceasing their work. We'll call this variable V(s). In France, when the transit workers go on strike the nation is temporarily paralyzed. High V(s). If the New York City police department went on strike, serious trouble. They have a high V(s). I hear that the Screen Writer's Guild has been on strike for a while now. Is anyone outside of LA missing them? V(s)=?