Many more words are extinct than those we get to read

I'm starting a new human evolution book project. Technically I've already started it but I've got the greenlight from my agent so it's for real. 

So much writing, at least for me, is just exploratory, organizational vomit that I never times infinity wish to see on the printed page. 

But, here, let me show you my vomit from this morning:

High heels are sexy because they change a woman’s posture so that her boobs and butt stick out and that’s attractive because boobs and butts and because waist hip ratio. 

Wait, no, they’re sexy because they make a person taller and taller is universally attractive. 

What if they’re a handicap or a fitness indicator like a risky bird call or a peacock’s tail? The hampered, painful locomotion signals to potential mates how badass the high heel wearer is. “We will have badass kids!” say high heels. 

source

Or they keep women from being able to escape too quickly if ambushed by aroused men, but that’s too macabre for me to consider further and pisses me off. 

How about, they’re sexy because we decided they are. Culture is weird and powerful: neck lengthening rings, circumcision, Taco Bell. 

Or they’re sexy because they make a woman’s feet look small for her height and this is sexy because … Fibonacci? (Must do calculations.) I don’t know. "Hold me closer tiny footed," isn’t how the song goes. 

But, wait, high heels change a woman’s locomotion. Women who walk in them have an exaggerated female-stereotyped gait. Ask those biomechanists who said so. That’s why heels are sexy, then, they heighten femininity and project its signal further out across the savannah, and into the gaze of more men for longer in each of their numerous salivating minds. 

But why are swinging hips sexy? Because they’re opposite of a man’s? 

But there’s something else that heels do to gait. They make a person unstable, careful, as if they're just learning to walk. One slips into those torture slippers and they're suddenly precious, adorable, in need of rapt attention. Like a toddler, walking for the very first time. 

The idea’s out there, somewhere, that heels make a woman helpless and that’s attractive to men who want to rescue women. This toddler idea is just a fraction of a degree away from that one. Is male attraction to helpless women the same thing that drives them to be doting fathers? Gawd. If that’s true, that means I shouldn’t be as annoyed when they want to rescue full grown women, and when full grown women want to be rescued, because, after all, it’s just good fatherly mojo. But, we’re not babies, dammit. 

High heels. Sexy for so many reasons, but also because they make women into babies and, hey, wait a second...

We don’t think babies are sexy. What the bleep am I talking about? Back up: what we prefer in babies can be preferred in adults for fundamentally similar reasons but those preferences can result in different outcomes. 

Attractive helpless babies get cared for and not sexualized (too much) and attractive helpless women do too but that affection includes bleeping. 

It all makes perfect sense. How on earth did our lineage survive this long without high heels?

Who speaks for the facts?

Everyone else is speculating on what happened to Malaysia Airlines Flight 370, so we don't have to. The one thing that most people agree on is that the plane met a tragic end, and we pause for a moment to recognize the pain and sorrow this has caused so many people. But, the wide range of hypotheses is fascinating, and we wanted to briefly consider why there are so many and what this might say about science.

We don't need to rehash the possibilities, which range from simple accident to malicious intent on the part of one or more passengers, or even the pilots.  Indeed, you can generate your own conspiracy theory right here.  E.g.:

But a new hypothesis is intriguing and puts the rest in stark relief -- a piece over at Wired, "A Startlingly Simple Theory About the Missing Malaysia Airlines Jet", written by a pilot named Chris Goodfellow, is a reminder that perspective is everything. Well, informed perspective.

Goodfellow says:

There has been a lot of speculation about Malaysia Airlines Flight 370. Terrorism, hijacking, meteors. I cannot believe the analysis on CNN; it’s almost disturbing. I tend to look for a simpler explanation, and I find it with the 13,000-foot runway at Pulau Langkawi.

He goes on to say that pilots are trained to always know where the closest, safest airport is if something were to happen to the airplane they are flying.  He says the pilot of Flight 370 must have landed at Pulau Langkawi many times, and that he must have realized that there was an emergency on board, and turned toward that airport, knowing it was the closest place he would be able to land.

What I think happened is the flight crew was overcome by smoke and the plane continued on the heading, probably on George (autopilot), until it ran out of fuel or the fire destroyed the control surfaces and it crashed. You will find it along that route–looking elsewhere is pointless.

Goodfellow says this fits all the data, from the loss of transponders to the turning of the aircraft.  He is appalled that people are considering the pilot to have had malicious intent, when in all likelihood -- in fact Goodfellow is certain -- instead he acted heroically.  See his post for the detailed explanation.

Our point here is not to explain what happened, because we have no idea, but to take a look at how hypotheses are made, and how they are evaluated.  Goodfellow is an old and experienced pilot.  He is evaluating the data from inside the pilot's head, and it turns out that his is probably the most parsimonious explanation.  And, as everyone knows, a parsimonious explanation is always the best explanation.  Occam's razor.  And add to that that 'experts' are assumed to have judgment as to what explanation is most parsimonious.

Fossils from the Cretaceous, found in Lebanon; Wikimedia

Except that parsimony is an arbitrary measure of the quality of data assessment.  The basic idea, and it certainly has much merit, is that when a simple explanation will do, adding other variables and explanations is not called for by the data and as a general principle we avoid making explanations more complex than they need to be to account for our data.  Which is not to say that parsimonious explanations can't be the best, just that parsimony itself isn't why they are the best.

Everyone is working with the same data on this airplane mystery.  But terrorism experts see evidence of terrorism, mechanics see sure signs of engine trouble, and so forth.  It's the pilot who can imagine himself in the pilot's seat who, at least to us, makes the most sense.  Not because of parsimony -- do we have good reason to think that the flight tragedy was due to one thing only?  An electrical failure or fire, or a hijacking, or sudden gain in altitude that knocked everyone, pilot and passenger, out cold?  Normally, in this case, we would not think that there was, say, a hijacking and then an on-board fire.  That would be complex compared to just one of those--but how would we know that more than one event didn't account for things?  The hijackers could have jerked on the controls and sent the plane too high, which knocked everyone out, etc.

Also, of the separate hypotheses, is there really at this stage a good reason based on parsimony to choose one over the other?  Each author has his own idea, or advocacy.  The pilot's explanation seems to make the most sense because he's a pilot, and can evaluate the evidence as if he'd been flying a troubled plane.

And in science
Everyone saw the same world Charles Darwin saw in the early to mid 1800's, too, and only he and Alfred Wallace made lasting order from the data, suggesting that the diversity of life is the result of descent with modification from a common ancestor via natural selection, and the fact of evolution is confirmed every day in biology labs around the world.  Alternative explanations for the origins of the diversity that everyone saw around them were many; then as now fundamentalists saw the hand of God and, fossils were thought to be 'sports of nature', not evidence of extinct species, because God wouldn't have made species that went extinct.  A case can be made that Darwin lost his faith after the death of his daughter, Annie, and a theory that didn't require a divine being was one he could readily accept.

One argument against the God argument is that God would have had to have a separate reason for making insects have 6 legs, but not spiders or lobsters, and vertebrates four, but not fish or birds, who have fins and wings.  That is, God made a separate, unique decision about each creature.  That is more complex than saying evolution and common ancestry generically account for what we see. 

Now evolution is different for every creature, just as God's choices would have been, and 'God's choice' is as parsimonious as 'evolution', so the criteria for what is the empirically simplest explanation does involve some subjective judgment.  If evolution is a true generic explanation for life and its diversity, and all the evidence suggests that it is, we tend to seek the simplest evolutionary explanation.  Still, nothing guarantees that an ad hoc phenomenon like evolution has to go from A to Z by the shortest path!

Indeed, there are even those who question the 'obvious' physics principle that radiation like light travels in 'straight' lines (here, modern physics might say 'geodesic' lines in spacetime).  However, some physicists say that energy takes infinite histories all at once, and that the straight-line path is not 'the' path but the average path taken by the radiation.  That puts a twist, so to speak, on parsimony ideas.

And in genetics, everyone has access to the same data, when GWAS results are reported, or genome sequences uploaded to GenBank, yet some geneticists see simple answers and some see complexity. And evolutionary psychologists see adaptive explanations where others might see genetic drift. And many look for one explanation -- this gene, or that bad lifestyle -- even when it is blatantly obvious that genes and lifestyles have effects only in their overall context.  So what is the most 'parsimonious' explanation is debatable and we have no real rigorous way to adjudicate in many instances -- even if we would all agree that we don't invoke a gene plus the tooth fairy plus raging storms on Jupiter to account for a case of cystic fibrosis.

Observations don't speak for themselves, in science or forensics.  It is through the mouths of subjective observers that they speak, observers with more and less credibility.  Who we choose to believe is in turn affected by our own subjective decisions, not usually an evaluation of which argument is more parsimonious.  Parsimony can be one criterion, but it may not be 'the' true explanation, or even the best one.  Life, due to its meandering and highly probabilistic pathways, may be one of the least parsimonious phenomena that science tries to understand.

Take on a Big Problem? A ton of money or a tub of water?

Two Nobel laureates were interviewed recently on the BBC Radio 4 program, The Life Scientific, and they said some relevant and interesting things.  The program is new series, interviews with some of the most influential scientists alive.

Paul Nurse, who won his prize for work on the genetics of cell division, was interviewed in October.  His prize was earned essentially because cell division is in many ways a similar process in all forms of life.  In light of evolution this could be said not to be a surprise: the same process might be expected to involve the same mechanism.  On the other hand, there is a lot of parallel evolution and given the complexity of many controlling mechanisms, one gene might substitute for another for the process.  But, at least in terms of some of the controlling genes, evolution somehow maintained the same mechanism over more than a billion years.

The other scientist of particular interest, interviewed in November, was John Sulston.  He innovated methods for mapping (locating) the genes on the genomes (chromosomes) of an important experimental model, the tiny flatworm called C. elegans, and then led the race to sequence the entire human genome.  A main part of this work was done at the Sanger Centre, near Cambridge, England, where I was fortunate enough to spend a sabbatical in 2005.  In his modest self-description, Sulston said that his job was just to identify the entire genome, and let people more clever than he have that information to do the work to find out what different parts of the genome do.

C. elegans; Weiss and Buchanan, The Mermaid's Tale, 2009

This moved the field from 'genetics' that dealt with single genes and classical hypothesis-driven science (where you have a specific, restricted idea, and then design experiments to test it), to 'genomics' or what is called hypothesis-free science: sequence everything in every individual you study, and search for unsuspected pattern to emerge that can then be specifically tested.  The latter is more like Victorian plant and beetle specimen collection, that we so often love to criticize as useless, not even 'science', really.

There are two aspects of this that are relevant to the current drive to understand life, largely from the genome perspective. First, Nurse said one should start out a science career by picking a really Big Problem.  Even if you work on a narrow scale, do it to solve a major problem about life--he started out with yeast, before turning to human cells and generalizing how cell division work.

Sulston got a similar prize but by taking a diametrically opposite view: his job was to collect the beetles and let everyone have a crack at the data to see what they could find.  Genomics has been driven by the technology that makes it possible. But it is in some ways the opposite--or even the antithesis--of Nurse's idea.  It is doing a really big study on a really small problem.

GWAS (genome wide association studies) to understand, say, the genomic basis of diabetes may not seem like a small problem.  If the genomic approach works, and it leads to major reductions in diabetes morbidity or mortality, it would be a big success.  But the problem itself is very local and particular, and there is no intent that solving it would apply to a bigger problem.  One can criticize the blind following of this Big Science approach, and it richly deserves the criticism for the manifest, numerous reasons we often point out.

But is this also a big problem hiding under a big budget for a small question?  It is often argued so.  In defense of ever-larger studies of biobanks, GWAS, and the like (or, in regard to evolutionary genetics, of ever more whole genome sequencing from ever more species, applying ever more detailed and exotic statistical tests for evidence of natural selection), defenders often argue that yes, it's expensive, and yes it may be decades before it bears fruit, and yes, GWAS may not identify major causal genes, BUT these studies will reveal biological mechanisms or pathways that will have much broader applicability.

There is no answer to this.  We are clearly, however, training a generation of technocratic scientists who think big budget and big technology either first, or immediately after whatever question they are asking.  And the questions are nowadays mainly applied ones: what causes diabetes or stomach cancer, for example, or what cause skull shape variation.  However the studies are routinely justified for what they will reveal more generally.  We often, if not routinely, point to chance discoveries in the history of science, and say that's what we're aiming for.

Of course, the vast majority of science is routine, if not hum-drum and with little likelihood of any impact other than to feed the investigator and his or her lab group.  It is vainglory of a high magnitude to promise serendipitous Eureka! moments as justification for dipping so deeply into the public treasure for each of our studies.

On the other hand, it is certainly true that Eureka! discovery moments do arise.  So is this an acceptable justification for investment in, say, big-scale genomic approaches?  This is for you to decide.

But what we're doing clearly is proposing the kinds of studies to answer the kinds of questions that require big data and expensive, extensive, and often very complex instrumentation and statistical methods to address.  Inevitably and systematically, perhaps, some issues are being closed to us while others are being opened.   One can argue that the narrower your training or focus the less likely you'll have one of the major moments, but in any field in any era it has always been only the very rare, lucky person who has had one.  Also, without the investment, they certainly can't happen.

Or are these correct arguments in support of the way we do things today?  In the past, it was individuals slogging doggedly after a problem (Galileo, Newton, Darwin, Einstein, others) rather than big factory operations (which, to be fair, didn't really exist until fairly recently), that delivered Eureka! discoveries.  Will the lone, persistent, investigator have the next transformative insight?

Nurse had substantial though we think not enormous funding.  Sulston and the Human Genome project garnered enormous funding for their work.  Both got Nobel prizes for their work.  On the other hand, Darwin just worked in his backyard after a low-cost sailing trip round the world, Mendel in his modest garden out back of a monastery, Galileo with a cheap telescope and under house arrest.

And the real Eureka! moment?  That just required Archimedes to take a bath.