In order to be recognized, you have to be read: an impish truth?

Edgar Allan Poe was an American short story writer, a master of macabre horror--the 3 G's, one might say: Grim, Gruesome, and Ghastly.  Eeeeek!! If you don't know Poe, a BBC World Service podcast in the series The Forum (Sept 15, 2018) discusses his life and work.  If you haven't yet, you should read him (but not too late at night or in too dark a room!).  The Tell-tale Heart, The Murders in the Rue Morgue, The Pit and the Pendulum, and The Cask of Amontillado should be enough to scare the wits out of you! Eeeeek!!

Edgar Allan Poe (1809-49)

Ah, scare tactics--what a ploy for attention!  At a time when not many people were supporting themselves with writing alone, Poe apparently wrote that this going over the top was justified or even necessary if you wanted to make a living as a writer.  If you have to sell stories, somebody has to know about them, be intrigued by what they promise, go out and buy them.

Is science also a fantasy horror?
Poe was referring to his use of extreme shock value in literature, stories of the unreal.  But a colleague in genetics once boasted that "anything worth saying is worth exaggerating, and worth repeating", and drum-beating essentially the same idea over and over is a common science publishing policy.   This attitude seems schemingly antithetical to the ideals of science which should, at least, be incompatible with showmanship for many reasons.

Explaining science and advocating one's view in responsible ways is part of education, and of course the public whose taxes support science has a right to know what scientists do with the money.  New ideas may need to be stressed against a recalcitrant public, or even scientific, community.  Nonetheless, pandering science to the public as a ploy to get attention or money from them, is unworthy.  At the very least, it temps exaggeration or other misrepresentations of what's actually known.  We regularly see the evidence of this in terms of outright fraud that is discovered, and also yes-no-yes-again results (does coffee help or hurt you?).

This, I think, reflects a gradual, subtle, but for someone paying attention, a substantial dumbing-down of science reporting, by even the mainstream news media--even the covers and news 'n views headlines of the major science journals approach checkout-counter magazines in this, in my view.  Is this only crass but superficial pandering for reader and viewership--for subscription sales, or could it reflect a serious, degeneration in the quality of education itself, on which our society so heavily relies?   Eeeeek!!

In fact, showman scientists aren't new.  In a way, Hippocrates (whoever he was, if any single individual) once wrote a defensive article (On the Sacred Disease) in explicit competition for 'control' of the business of treating epilepsy, an effort to maintain that territory for medicine against competition from religion.  Centuries later, Galen was apparently well-known for public demonstrations of vivisection and so on, to garner attention and presumably wealth.

Robert Boyle gave traveling demonstrations of his famous air-pump, doing cruel things to animals to show that he created a vacuum.  Gall hustled his phrenology theory about skull shape and mental traits.  In the age of sail, people returning from expeditions to the far unknown gave lurid reports (thrills for paying audiences) and brought back exotica (dead and stuffed).  The captain of the Beagle, the ship on which Darwin sailed, brought live, unstuffed Fuegians back to England for display, among other such examples.

Yes, showman science isn't new.  And perhaps because of the various facets of the profit motive (now perhaps especially attending biomedical research) we see what seems to be increasingly common reports of corruption even among prominent senior (not just desperate junior) academic scientists.  This presumably results from the irresistible lure of lucre or pressure for attention and prominence.  Getting funded and attention mean having a career, when promotion, salaries, tenure, and prestige depend on how much rather than on what.  Ah, well, human fallibility!

The daily press feeds on, perpetuates (and profits from) simplistic claims of discovery along with breathless announcements that are often basically and culpably exaggerated promises.  Universities, hungry for grants, overhead, and attention, are fully in the game.  Showboat science isn't new, but I think has palpably ballooned in recent decades.  Among other things, scientists intentionally, with self-interest, routinely sow a sense of urgency.  Eeeeek!!

So should there be pressure on scientists to quiet down and stop relentless lobbying in every conceivable way?  My personal (probably reactionary!) view is a definite 'yes!':  we should discourage, or even somehow penalize showmanship of this sort.  The public has a right to know what they're paying for, but we should fund science without forcing it to be such a competitive and entrepreneurial system that must be manipulated by 'going public', by advertising.  If we want science to be done--and we should--then we should support it properly.

In a more balanced world, if you're hired as a science professor, the university owes you a salary, a lab, and resources to do what they hired you to do.  A professor's job should not depend on being a sales agent for oneself and the university, as it very often is, sometimes rather explicitly today.  Eeeeek!!

The imp of the perverse--in science today
One of Poe's stories was The Imp of the Perverse.  The narrator remarks upon our apparent perverse drive to do just the opposite of what we think--or know--that we should do.

The Imp of the Perverse.  Drawing by Arthur Rackham (source: Wiki entry on the story)

I won't give any spoilers, since you can enjoy it for yourself.  (Eeeeek!!)  But I think it has relevance to today's attitudes in science.  Science should be--our self-mythology is that it is--a dispassionate search for the truth about Nature.  Self-interest, biased perspectives, and other subjective aspects of our nature are to be avoided as much as possible.  But the imp of our perverse is that it has become (quoth the raven) ever-more important that science be personally self-serving.  It is hard to prevent ourselves, our imp, from blurting out that truth (though it is often acknowledged quietly, in private).

On the good side, careers in science have become more accessible to those not from the societal elite.  The down side is that therefore we have to sing for our supper.  Darwin and most others of science lore were basically of independent means.  They didn't do science as a career, but as a calling.

Of course, as science has become more bureaucratic, bourgeois, and routine, Nature yields where mythology--lore, dogma, and religion--had held forth in the past.  So, it is not clear whose interest that imp is serving.  That's more than a bit unnerving!  Eeeeek!!

Science 'ethics': can they be mainly fictional, too?
Each human society does things in some way, and things do get done.  Indeed, having been trained as an anthropologist, perhaps I shouldn't be disturbed or surprised by the crass aspects of science--nor that this predictably includes increasingly frequent actual fraud egged on by the imp of the pressure of self-interest.  Eeeeek!!

Our mythology of 'science' is the dispassionate attempt to understand Nature.  But maybe that's really what it is: a myth.  It is our way of pursuing knowledge, which science, of course, does.  And in the process, as predecessors such as those I named above show, gaming science is not new.  So isn't this just how human societies are, imperfect because we're imperfect beings?  Is there reason to try, at least, to resist the accelerating self-promotion, and to put more resources not just to careers but to the substance of real problems that we ought to try to solve?

Or should we just admire how our scientists have learned to work the system--that we let costly projects become entrenched, train excess research personnel, scare the public about disease, or make glowing false promises to get them to put money in the plate every tax year?  In the process, perhaps real solutions to problems are delayed, and we produce many more scientists than there are jobs, because one criterion for a successful lab is its size.

Were he alive and a witness to this situation, Poe might have fun dramatizing how science has become, though wonderful for some, for many, a horrible nightmare: Eeeeek!!

Separating science and science politics?

Some people feel that scientific issues should be kept separate from science politics.  But is that even possible?  The fear is often voiced that even if science does often work largely as a business even with its self-promotional components, that is just how things are, and that if anybody listened to what people like ourselves say (which is, of course, unlikely!), many large-scale projects, which are older than your parents' first car (and just as rusty), might be phased out, which would be unfortunate, because it would be losing all that valuable information after decades of careful effort.

But we think it is not reason enough to maintain large projects that may once have yielded valuable results but that are now running on fumes, kept running for legacy reasons.  Nobody would suggest that the data be discarded, but it could be made available while funds moved to more promising approaches.

The unlimited insult
The widely touted 'new' idea of genomic 'precision' medicine is an example.  Here is a quote we ran across from George Eliot's 1871-2 book Middlemarch:

"I believe that you are suffering from what is called fatty degeneration of the heart, a disease which was first divined and explored by Laennec, the man who gave us the stethoscope, not so vary many years ago.  A good deal of experience--a more lengthened observation--is wanting on the subject.  But after what you have said, it is my duty to tell you that death from this disease is often sudden.  At the same time no such result van be predicted.  Your condition may be consistent with  a tolerably comfortable life for another fifteen years, or even more.  I could add no information to this, beyond anatomical or medical details, which would leave expectation at precisely the same point."

What's the point of this quote?  After all, anyone can mine almost anything for juicy quotes that support their biases or points they want to make, and invoking some prior author--not to mention a fiction writer!--is a form of rhetorical trick that really has little actual cogency.  Who gives a hoot what George Eliot thought, after all?

When our NIH Director proclaimed a billions of dollar project that we would finally do 'precision' based medicine, it was an insult to every physician who has ever practiced medicine, back to Hippocrates and of course all the others who did not write books and are thus not known to us today. The reason is, of course, that every honorable physician throughout history was doing his/her best to be as precise and (to borrow a previous advertising slogan for NIH) to do 'personalized' medicine.

We've written before about the vacuous or transparently lobbying nature of words like 'precision', and the point here is not that being as precise in medical diagnosis, prevention, prediction, and treatment as is possible at any time is anything other than wholly noble.  The point is that blanket statements suggesting that genotypes are going to predict everything about a person is a costly way to divert funds from being directed more precisely, one might say, where that word is actually appropriate. 

There are many disorders that are highly predictable from genetic data (sickle cell anemia, cystic fibrosis, muscular dystrophy, and many, many others).  The genetics community should show that knowing this can lead to effective gene-based approaches to what is truly and clearly 'genetic', before we just spew resources out across the entire genomic landscape.  

Even if it were clearly important to assemble genomic data as part of a unified health-care and health-research system, new large-scale databases should start fresh without the legacy of past work imposing various frameworks on the future resource.  Various rationales, almost amounting to 'we need practice building data bases' have been suggested in defense of keeping elderly projects afloat, but these seem, to us, as much political rationale for holding on to resources as it is truly the best way to start making a national resource.  But rather than just being cranky about this, we have various thoughts to offer, about the current inertia that is built into our system.

The idea of better ways of identifying risk groups, for example, especially far in advance of when their risk becomes manifest as disease, is a proper major goal of public health research.  Medicine usually deals with people when they are already ill or at high risk, but research can benefit from partitioned analysis of low and high risk individuals, where that is possible and as early as possible. This can be useful, e.g., in determining risk alleles or environmental exposures, or who will respond well to a given drug or therapy.  The earlier the better--and when genotypes at conception do truly have high predictive power that is a proper kind of data to collect.  But how often is that?  After about a generation's worth of mapping studies, the answer is rather clear--if the politics is separated from the actual science. 

We think there are several reasons why building huge data bases to partition populations into high and low risk groups or, much harder, individuals is right-minded in principle, but will have problems.

1.  Inertia, and Momentum.  Without real change, in personnel and in projects, the gravitational pull of business as usual is huge.  A system of science Patricians is established, and they become Geriatric Patricians.  They are, as you know, getting the bulk of the grants (e.g., first-time NIH grant recipients are about age 45 according to some recently published data, the percentage age 36 and younger has been plummeting and the percentage of PIs over age 66 growing steadily since 1980, as the graph below shows).  Any savvy scientist knows that big long-term projects are politically hard to phase out.  That is science politics, not science, though isn't specific to science.   However, in science it can impose inertia on current methods and concepts.  

Source

Occasionally a new idea, technology, method, or, today, 'omic, does come along, and there is a swell of momentum as the herd rushes to adopt it.  Again, however, the goal is to establish too-big-to-stop longterm projects.  Of course, such change may sometimes be a very good thing, if the method, idea, or technology is truly beneficial.  But often it is not much of an improvement, or perhaps the questions being asked are themselves conveniently changed as a funding stratagem.  Do you not think this is an important part of the current system?  Perhaps that's only to be expected, since real innovation is clearly hard to come by, which is nobody's fault.  But the more inertially entrenched this system, the less may be the opportunity for real innovation.

For example, when everyone uses the same data sources or sequencing approach or statistical packages for analyzing data, there is a kind of channeling conformism.  This is in part because lab equipment and software are complex and highly technical, and developing one's own is generally not feasible.  That requires large, long-term funding, so the problem is not an easy one to solve.  There are of course always innovators, and we should be grateful for that.  But when struggling for one's career, or to keep continued funding, it is easier, for many reasons--in science as in other fields--to simply do what others are doing.

2.  The 'Quantum Mechanical Effect.'  In quantum mechanics, when a basic property of a primary particle like an electron or photon is measured, it affects the particle's other properties.  The combination is probabilistic and measuring is a form of interference, which generates change.  You can't know the exact nature of the change without re-measurement--which then creates the same problem.

This Quantum Mechanical Effect has a kind of analogy in biomedical genetics and epidemiology.  When even a bad study's findings are trumpeted to the media by the investigators and the journals, in full-throated self-promotion mode, and the media report is more or less without serious circumspection, ordinary people may change their behavior accordingly.  One reason is that most doctors themselves cannot keep up, and since the findings are so oscillating and fickle, even researchers may not have a grasp on complex causation.  As a result, diets and other habits change, companies change their products, advertising, and even their labels (because, believing the results, the FDA insists).  So the pattern of exposure to the purported risk factors changes and hence so does the risk itself.  That is, the effects of retrospective statistical data-fitting themselves constitute a kind of 'measurement' that itself affect the risks being measured.  

3.  The unknown unknowns.  Donald Rumsfeld doesn't really deserve the ridicule he gets for his quip about the unknown unknowns (even if he may deserve ridicule for other things).  It is very clear from recent history, not just remotely distant lore, that lifestyles change in major ways, and very quickly. If it were just a matter of differing doses of the same old risk factors, then we're faced with problem #2 above that the exposure levels will change in unknowable ways.  

This is true if the mix of exposures act in additive ways (just add up the estimated risk of a change in this behavior, and then of that behavior).  But even if this additivity assumption were accurate, what is more likely to be important, is that exposures to entirely unforeseeable factors will arise.  Nobody in the 1950s could have predicted the number of hours we'd spend watching flickering images, or flying in jets or being CT-scanned, or eating new fad foods, or new manufactured foods, or the kinds of infection or antibiotic exposures we would experience. Yet changes like these have made a huge difference in disease patterns just in the lifetime of us seniors: obesity, lung cancer (down in men, up in women), diabetes, autism, asthma, psychiatric disorders of all sorts.  Some of these have gone from being not so important, to being pandemic.

There are many things to think about in relation to our approach to the biomedical and public health problems and how genes relate to them.  It is easier not to think about them too much, and to just plow ahead with what we're doing or flocking to each new fad that comes along.  Ignore the politics as just the way the big boys play to get the funds, a game we all know about and can play ourselves if we wish to.  But the system is slick and it is often intentionally or biased reporting (e.g., exaggerated claims, unreported negative results, impenetrably technical methodology, etc.), which (sometimes intentionally) makes it hard to recognize that science politics is what's afoot, and to try to think  how to do things differently in ways that might make a difference. 

Business as usual is a form of science politics that need not be closely tied to the best science we should be able to do.  Science politics forces investigators to do what is needed to continue to be funded.  Many are now writing about various aspects of the current system in which the politics seems to be trumping the science.  The Fourth Estate is too often a co-conspirator with the establishment, rather than doing its job of being knowledgable skeptics.

Some of course defend the system not just as the game we know but also arguing that it is the best way to generate good science.  This is where the serious debate should take place.  Whether real change can be forced on the system is an open question.

Story required.

It might seem like it this week, but sex isn't the only recurring theme here on the MT. From various angles, we hit on the culture of science quite regularly, quite relentlessly, and quite hard. We can't help it, we think anthropologically. We want to know the truth of things as much as anyone else, and we think discussing and revealing what we don't know and what obstacles we face are important steps in the process toward knowing. 

One of the ways that science is so clearly cultural is its love of stories. 

I even did the story thing just then. I made science into an actor. 

Try again:  Science is done by humans and humans love stories. 

source

Hardly anybody I know'd deny that.

But what we scientists (particularly evolutionary scientists) seem to resist like the dickens is that we require stories and we are required to fit our work into others' or to write new ones. 

These superstitions can't be the straightest path toward the Truth, can they?

Back up a sec. First, I'm not trying to dump on the power of analogy. Without analogy we couldn't have gotten this far, scientifically. Lacking analogous thinking is a big reason why chimps don't reason. 

And, second, I'm not trying to dump on anthropomorphism or personification because I've done that already recently (and I'd love to talk about something else today).

I'm talking about making our research, our methods, our findings, our results fit our desired narratives. Or any narrative for that matter.

One of these habits we often discuss here at the MT is selectionism which is closely related to adaptationism.

Ken's recent post on this is brilliant: 'Every trait is due to natural selection!'... often said but is it true?

And since reading his piece (and since before) I've been stewing about some related matters, like, why don't negative results get published? 

I'm of the frame of mind to spin the following: Because the story arc where there is no change (no arc?) isn't usually the one that sells the screenplay to Paramount, and likewise, isn't usually the one selling Nature ads and subscriptions.

There's a pretty big recent exception to the negative attitude toward negative results. When they didn't find dark matter, we heard all about it! 

But that's because it was the first exploration of its kind and the spin was that some big time physics equations were wrong and needed to be scratched and reconceptualized. How exciting and productive! And wtf is dark matter?! 

But when people find no significant p-values for any effect of a food or drug on some aspect of health, who cares right? No change. No cause and effect to bring no change about! No results! which is not true, but still... Boring!

In fact, "boring" is what a reviewer called the last paper I tried to publish in a relatively high impact anthropology journal. It was because I didn't push one hypothesis over the others and instead discussed how unfalsifiable and untestable some present anthropological explanations are. The hypothesis I was expected to push--and it was punishably confusing why I didn't--was the story I'd written not too long ago.  Well, because I had already rewritten this entire manuscript since initially submitting it and because I don't think I could have gotten it through a second round of revisions without insincerely and unscientifically pushing one idea over others (which aren't even falsifiable to my mind), I withdrew the paper and will try somewhere else. All I had to do was convince the reader to join me in favoring at least one clever story and I dropped the ball entirely. I flopped because I didn't even try. The story, I thought, was that there might not be a story! If Charlie Kaufman had co-signed my paper, maybe it'd have had a chance? It might have no chance in anthropology journals, but I haven't given up yet. 

Try to find, let alone publish, an evolutionary paper without a story, without circumscribed causes and real or apparent effects. I haven't tried that hard, but I haven't succeeded yet either. It's probably much more common for people to attempt to publish stories but to have those rejected as the wrong stories, the ones not preferred by reviewers, or pushed by reviewers with vested interest in the 'correct' stories. 

Even my little flipbook classroom exercise, which simulates genetic drift, got rejected for publication partly because they feared it would tell the wrong story: intelligent design.

What's hard to swallow is, we can't really know the real natural history in all its glory, and so there's really nothing preventing us from writing natural history the way we want to (within bounds, whatever those may be). And so why's that enough for so many scientists? Why does that suffice? Maybe doing natural history is more like doing history than I ever thought. You get the details correct and you can write the story, the agents, the causes and effects based on your own interpretation and arrangement of those details. And as long as people like your story, you're good, you might even be golden. 

O! What if I'm just an anal retentive weirdo taking it all too literally? 

I didn't bait you here to read me whine and gasp existentially. I actually had more interesting thoughts about the bigger picture to share today. 

For instance, when you see so many potentially real but unfalsifiable evolutionary hypotheses as the stories that they are, it makes it so awkward to watch when science-minded folks spew venom at the "ignorant fantasy stories" of creationists.  

For more in this vein, or related to it, even remotely, I leave you this afternoon with some recent stories about stories, some favorites, others just plain interesting or relevant:

There's no Santa Claus, There's no Easter Bunny and there's no Queen of England! by Joel Adamson
~ If you want to know why I love this piece, see the comments.

Are hobbits human? Textual and genetic analysis of our closest real and magical relatives by Matthew Yglesias
~This is great, but took flak from both sides: scientists for the paleo and nerds for the Tolkien.

...and timely follow-up to that...
Myths matter from Maria Popova 

...and a response to Slate's story about a story...
Slate's embarrassing Middle Earth error by Max Read

Standing up for sex by Henry Gee
From the piece: "Now, I advance the above more than half in jest. It’s possibly no better or worse than any other idea, but I’m not going to pin anyone against a wall and shout about it. "
~ I have a hunch I'll like his book but I'm head-cocking over the attitude given what Nature publishes.

Public's views on human evolution by Pew Research Center

Surprising number of Americans don't believe in evolution by Jaweed Kaleem 
~ I don't believe in evolution either if it always ends in a white dude like the crappy figure they used here.

I had my DNA picture taken, with varying results by Kira Peikoff

Does reading actually change the brain? by Carol Clark-Emory

Claims of 'virgin births' in U.S. highlight pitfalls of self-reported data by Sharon Begley

In saving a species you might accidentally doom it by Ed Yong
~ Knowing the story of natural selection saved these birds from the humans who started out by ignoring it.

We need to talk about TED by Benjamin Bratton
From the piece, "If we really want transformation, we have to slog through the hard stuff (history, economics, philosophy, art, ambiguities, contradictions). Bracketing it off to the side to focus just on technology, or just on innovation, actually prevents transformation." 
~ So many parallels with what admins and students expect of profs.

And finally...

Editing your life's stories can create happier endings by Lulu Miller
~ THIS IS WONDERFUL.

Let's use evidence (not intuition, semantics, politics, or dogma) to navigate 'belief,' 'knowledge,' and 'science.'

image source

Recently, Adam Blankenbicker asked me to contribute my thoughts for a post he was preparing on "believing in science." Here it is.

This is an important discussion for many reasons. And I have lots of opinions. Sometimes they're so strong I get to read them on NPR! Sometimes they're so strong that my teeth squeak when I hear a teacher quoted as saying, "I’m here to show you the evidence. If you want to believe the evidence when we’re done, that’s up to you." This kinda kills me just a tiny bit and I have to remind myself that quotes like these are plucked out of a much richer context that's omitted entirely.

But I actually hesitated on whether to respond to Adam's invitation to comment for his post because I'm writing a book right now that turns out to be hugely relevant to this knowledge/science/belief issue and (this is the kicker) it's relevant only because of the immense evidence-based, scientific journey that led me write [sick] up to this issue.

In other words, I hesitated to respond to Adam's email because I am uncomfortable with describing my present state-of-mind on this issue without first leading a person through the steps it took to get me there. The evidence! And those steps are about 60,000 words high and counting...

Regardless, I couldn't resist writing back to him. I knew mine probably wouldn't be the answer that he or at least most of his readers would warm to, but I just had to attempt to get across my discovery (yes, that's what it feels like!) that belief and knowledge aren't so distinct (or maybe aren't distinct period). I saw my response as sort of like a little test to see how it would float out there...

And it kinda sunk.

Let me show you...

Here's just the meat of the email with what I was asked to respond to:

If you have a few minutes, could you provide me some of your thoughts?
Why shouldn't I say "I believe in science"? What should I say instead to express the idea that I accept science? As a process or just a "thing".

Here's my klunky response (given some new punctuation for clarity here):

I'll answer your question as if you were told by someone else (not me) that "you shouldn't say 'I believe in science'" and that after they told you that, you came to me for help in understanding why they said that.

...Maybe because science isn't an entity, it's a perspective. It's also a process that's part of that perspective to arrive at knowledge that fits into that perspective. My This I Believe essay is about the difference between "believing in" something and "believing" something. And all I'd have to say about that is in that essay already.

Not all science-minded folks liked my essay because many think that "to believe" is different than "to know" because "knowledge" to many is based on facts and "belief" is not, so the verbs knowing and believing are therefore different. I don't agree. Even if some things can be distinguished as belief vs. knowledge, the possession of those things is believing/knowing for both the wrong (or completely evidence free) beliefs and the beliefs based on facts. Both can be just as real for the person who holds them so what's the difference? And when you think about all the "knowledge" that's passe and that's been overturned during the history of science, and when you do some serious reading about history and cross-cultural beliefs and knowledge, it's easier and easier to accept that these distinctions we make as scientists are cultural just like any other tribe's when they're describing their own system versus another.

Here's how my response was presented in the post:

I reached out to Holly and she told me that there were a number of “science-minded” individuals who did not agree with her essay. They “think that ‘to believe’ is different than ‘to know’ because ‘knowledge’ to many is based on facts and ‘belief’ is not, so the verbs knowing and believing are therefore different.” Where I agree with this perspective, Holly disagrees. But she goes on to say that just having the belief or knowledge is fine, not matter what word is used.

The delicate issues I tried to briefly convey are not included in my quote. Those parts that he says he disagrees with (the parts I italicized in my email up there) are not included and are poorly paraphrased.

Basically, my quote is plucked out of a much richer context that's omitted entirely! 

Am I crazy for posting this? Probably a little. But it's an issue I care very very deeply about...and more now than ever with this journey that I've taken while writing my book. I may be too sensitive, but I've had my mind blown by evidence this summer and it's led me to see knowing/believing and knowledge/science/belief in new ways. As my mind is all exploded right now, I'm not exactly composed about these things--not that I was ever very composed about much in the first place.

#overlyhonestmethods or, Telling the Truth in Science

Y'all have seen the #overlyhonestmethods thread on Twitter, no?  The hashtag tells the story -- scientists, and surely some ex-scientists, revealing how and why they do what they do.  E,g.:

Dr. Twittenheimer ‏@DrTwittenheimerThe instrument was fully calibrated prior to use in this study. Several decades prior to use in this study. #overlyhonestmethods

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Claire Turner ‏@claz0rTHIS. RT @benosaka Blood samples were spun at 1500rpm because the centrifuge made a scary noise at higher speeds.#overlyhonestmethodsExpand

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If you haven't seen it yet, and you have any interest in science -- which you do because you're here -- you really should go check it out.  The tweets just keep on rolling, and they are hilarious.  In a very edgy way.  We're tempted to say they are getting even more edgy, but that's unfair because they were edgy to start with.  (If you don't want to hop all the way over to Twitter, here's a sample.)

We've read enough of these now to be able to detect some recurring themes.  Of course, the major theme is that science is rarely done the way it oughta be (see above re. the centrifuge speed, and others like "we used an n of 19 because one Eppendorf tube rolled under the freezer," "incubation time was 3 hours because that's how long I took for lunch," etc.).

But additionally:

• a lot of students and post-docs really don't like their supervisors, or at least distrust their knowledge of lab work since they've spent years or decades writing grants instead of working at the bench.  
• a lot of experiments are very sloppily done.  
• and/or a lot of people have no clue why they use the methods they do,  
• or, maybe it's that a lot of methods don't need to be strictly adhered to,
• or that we often have no clue whether they need to be or not.
• a lot of papers are cynically written.
• much (most?) of science is done with both eyes on the next grant.
• people cite a lot of papers they haven't read, not only when they are behind a paywall.
• a lot of kissing ass is going on in science. 
• very cynically. 
• undergrads get blamed for everything.  Probably correctly.  When it's not the post-doc's fault.
• no one likes reviewer #2.  
• a lot of scientists are very funny.  

But beyond all this, this thread is a beautiful example of the anthropological concept of emics and etics, emics being the way 'natives' explain a behavior or idea and etics being the way an outside observer explains the same thing.  Except that here the scientists are playing both roles.  They can readily say the right thing -- those tens of thousands of papers that get published every year -- but they can also step outside the culture of science and deconstruct why they said or did what they did.

What is truth?  What can be reasonably expected?
The truth is often unclear, and no complex operation like a science experiment or study worthy of the name is entirely straightforward.  Generally, if it were so easy, we'd know the answer and wouldn't need to do the study.

Yes, and we're all fallible.  We can forget various steps of a procedure, misremember what we did, make errors in our notes, inadvertently or even subconsciously color what we say or how we interpret data. We can even yield to temptation to make various short-cuts and alterations to data, like throwing out 'outlier' observations that just don't seem to be right (relative to our preconceptions, or reporting only the segment of our results (the one transgenic mouse out of many) that 'best' represents the results as we present them (that is, that best fits our theoretical expectations) -- and #overlyhonestmethods has a lot of that.

These are sins, because brutal objective honesty with precision is the goal.  But given human failings, if we're really right about the problem at hand, the results of these kinds of distortions from purity won't change that--the truth will out, so to speak.

But what the twitterati here are discussing is something very different indeed!

"Oh, what a tangled web we weave when first we practise to deceive!"  (Walter Scott)
What this set of tweets so accurately reflects is the current culture in science, which is explicitly expressed (though often not said publicly except between colleagues or faculty and their graduate students).  We're aware of it, it is systematic if not systemic, and it is driven, clearly, by the rush to publish, the strongly felt need to hype our work to build our careers, and the desperate and relentless struggle for grants, jobs, and the like.

Grantsmanship, or how to strategize your ideas to get funded, is often at its core, and sometimes openly, about deception of reviewers and funders.  A very common, if not typical, example is the smug grins with which investigators say that the thing they do is propose funding for work that is outlined in the proposal as to be done, but in fact has already been done.  Or to present work selectively, or to cite reviewers' work to butter them up, and so on.  This is all driven by the 'business model', and the rush, rush, rush to publish and spend.

Well, you might say, this is just the game we play.  We all know we're doing it.  Human society is always laden with this sort of organized dishonesty. It's what you have to do to compete for resources and after all, what is life about if not that?  If we all do it, the system internally adjusts accordingly.

This may be the hard truth, but it's a worse offense is to acquiesce to it.  Because then we end up in Scottsville: we weave tangled webs of dissembling and disinformation, of untruths known and unknown, of habits of deception that become essentially routine.  And here the idea of science as self-correcting and hence immune to such tangled webs becomes a myth.

That's because untangling this kind of web is often impossible.  Studies are too large and too expensive for them to be replicated.  Or the sample or working material is unique: if I mis-report a study of a particular disease in, say, Bongabonga, you can't go to Bongabonga and repeat it.  Samples from elsewhere are only partly relevant.  Likewise with intricate experimental systems involving high technology, and very particular setup.  The costs of the kinds of knowingly huge studies we do these days prohibits such checking-up even if it were technically possible.  And the many intricate details, often only sloppily reported in reams of 'Supplemental Information' on the journal's web page, are often challenging to understand if not intentionally obscure.

And more than just checking up, we have to build on others' work because we simply can't do everything over.  So what we build on needs to be reliable.  That's why human fallibility and vanity is no matter to be joking about, despite #overlyhontestmethods, given how true it actually is.  Huge investments are made, and we have a very unclear understanding of the degree to which this sort of cheating is meaningful and felonious, rather than simply the misdemeanors of imperfect beings.  Cheating is, in a sense, rewarded if we just smile and look the other way.  Even if we might just say it's not worth worrying about because most science, like most anything else, is rather pedestrian and headed for obscurity even if it were as pure as Ivory soap.

But when this is how we train our students, we sow seeds of a problematic future.  Especially in an era when funds are limited, any avoidable dishonor in the system should be avoided, and we have to hope that the result of systematic misdemeanors we smile about will not become so accepted that we cannot untangle our weaving.  That could lead to science becoming just another shaky belief system, on which much of our lives rely.  Hasn't human history had enough of those already?

The mouse that roared, or the lion that peeped?

The Mouse that Roared was a funny comedy film, decades ago, about a little Alpine principality (the Duchy of Grand Fenwick) that managed to bring the US to its knees, to win major concessions.  The idea was to declare war on us, to lose, and then be the beneficiary of all the largesse we dump on those we defeat.

In science as in other areas of human endeavor, especially in a society slavishly obsessed with the 'business model' and 'competitiveness' and the bottom line--even in universities, we want to get the most bang for the buck as this little mouse of a country did by roaring at the huge US.  Science as it is practiced today raises some relevant issues.

The other day we criticized a very big study about calcium intake and heart disease risk, and it was but one of many critiques we have made again and again (and again) here on MT.  Our point was that sloppy designs and non-definitive results, that have to be repeated again and again (and again) with ever larger scales and for ever larger budgets, are becoming more of the rule than the exception.

In our areas of (we hope) knowledge, we blog away at the practice of ever increased scale for ever diminished payoff.  Examples are massive GWAS to find hundreds of miniscule, ephemeral possibly-causal genetic effects.  Despite fervent denials and claims of success, that's what's afoot in biomedical and other sciences.  It's the way we build careers, maintain labs and reputations, and earn our nice academic salaries.

But that is not the same as roaring lions of discovery.  Real progress.  We need ever larger, ever repeated studies because what we're trying to find are unclear, non-definitive, or (generally) minor effects.  It is more like fiscal lions generating peeps of results (but then roaring about them as if they were lions).

This kind of hyperbole is in the science news every day.  Indeed, the fact that there is a science news is part of the story, because the news outlets need to sell and the news needs stories, and investigators need the publicity to get their grants and make their careers, so we have a positive-feedback system where the big begets bigger, and the brag begets bragger.  We have come to something ColdWar-like: Mutually Assured Dependence.

As in the other day's post's example, larger and larger studies are needed if the effects we want to find are smaller and smaller.  And that also generally means that they are part of complex interactions in multi-factorial causal systems.  A small cause's effect depends on the other causes present or not present.  Even a cause that's always present, but is small, requires large studies to detect.

By contrast, truly major causes can be detected, replicably and reliably by small studies, that don't cost that much money and don't have to be endlessly repeated.  They are the mice that roar.  The late curmudgeonly David Horrobin said something to the effect that if you can't find it in samples of 30, it's not worth finding.  That's an exaggeration....but how much of one?

But our culture today is about spawning nearly mute lions.  We harp on this because lots of your money is paying for this kind of research.  Instead, we should be able to  provide smaller funding to more people, hoping somebody will make lucky or insightful discoveries, or being less socialistic, we could really pour funds at problems that really are genetic or more clearly addressable with accountable impact in the case of  public health or evolutionary science.  Maybe truly genetic diseases could be prevented or cured more effectively and more quickly if we did that.

Nothing's perfect.  First, pouring money into what should be soluble problems could be like the War on Cancer and other government allotments:  There may only be so many good researchers, and they may already be funded, for these problems.  And, as is manifestly clear, anytime there is a pot of dough, the hogs rush frantically to the trough so one would have to have strong constraints so the funds don't get divided up among a crowd of claimants generating chaff.  In fact, this is how the system largely works now, with me-too being a major modus operandi. And, ironically, those who would rail against socializing funding (equalizing distribution, etc.) may not realize that to a great extent that is what our system currently does.  It's how all the med schools keep their research factories in operation 24/7--by investigators flocking to wherever the funds are, inventing whatever rationales for their own ideas that we can think of.  In a way, because it is also intensely competitive, it is a form of capitalistic socialism, a strange beast!

Instead, we build empires of hoarse lions, omitting the potentially much more cost-effective mice who, like humble miners' canaries, could lead us out of the most troubling problems we face.

The shelf life of a banana

We're in New York where I'm working with collaborators on a project in which we're developing  software to simulate complex genetic systems, so that knowing the 'truth' we can investigate some of the  questions being pursued these days in both epidemiological and evolutionary genetics.  Simulations don't generate actual reality, but when they generate what is very similar, one can hopefully make inferences about the truth, and in this arena the truth is in some ways unknowable.  The idea of simulation is to improve our ability to guess the truth from data, when things are complex as they clearly are here.

For some years our collaborators (Joe Terwilliger and Joe Lee at Columbia University) have been saying that much of the discussion of problems is needlessly about  limitations in the available genetic data.  GWAS and other similar genomic approaches to the genetic causes of traits like disease, and the results of evolution, have used increasingly extensive kinds of data.  For example, more sites of the genome are used to try to infer causation in parts of the genome that are near to those sites (we can refer to these as 'mapping markers').

Genetics has been going from one fad to another.  We first had mapping with limited sets of markers, that suggest regions of the genome that could be causally involved in some question (like adaptation to diet, or the risk of diabetes).  But the implicated regions of the genome were large, and many functional elements are in the region.  We couldn't easily identify the actual causal site or sites in the region.

Then someone discovers that there is more use of the genome than as an intermediate code for protein (that's messenger RNA, mRNA), but the RNA itself has direct function; some, called microRNA, (miRNA) affects the translation of mRNA into protein.  Someone else discovers that gene regulatory sites are important in the genome to control the expression of protein-coding regions.  Somebody else probes interactions among genes, claiming that these 'networks' are higher-order functional units.  Then it's found that chunks of DNA are duplicated or lost in some people but not others (called 'copy number variation', or CNV). Others explore the modification of DNA by various chemical means in cells, that affect which genes are expressed; this is called 'epigenetics'.

All of these things become 'omicizied--in the scramble for money, attention, and yes, even to actually do some real science, analytic platforms are developed for detecting these various elements in the genome: special genomewide tests for epigenetic sites, or non-coding RNA, or rapid sequencing methods for the protein-coding parts of the genome (called 'exome sequencing').

Many people recognize that these are temporary stop-gaps.  In part, those who think that CNV will be the killer-discovery that explains a huge fraction of the cause of diabetes or autism, or that miRNA is the key to regulation, argue about and develop special molecular and statistical tools for detecting it.

Even those specializing in one or another of these fads, or subsets of genetically related causation, know that the tools are rather temporary.  The individual applications are discovering complex causal elements, but everyone knows that in total they still promise only to account for a fraction of causation of the traits of interest.  They are holding actions, and this is openly acknowledged.  They keep the funds and research moving, and feed the technology companies, so they can develop the next level to genomic methods.  We know this, but we are institutionalized so we can't wait for better tools.  We must keep the factories moving with these methods.

But they have the shelf-life of a banana.

It's easy, and perhaps correct, to be cynical of the great hype machinery that keeps the system in high gear.  It's costly, but we need to be paid, the tech companies need to sell something today while they develop a tool for tomorrow.  We need to keep the graduate student pipeline flowing.

For years in our various talks and mini-courses and papers, Joe Terwilliger and I have been saying that rather than spending too much time arguing about the best way to use and analyze these kinds of bananas, we should just assume that whole genome sequences will be available for everybody in the population. Given the lock that the science establishment has on funds, and the way that technology makes serious increases in the amount of data we can generate and analyze, and the way that leads to drop in cost, it seems likely that barring international catastrophe, ubiquitous sequence data will be available.

This is now viewed by some as a kind of inevitable end point: finally we'll have all the data we need from a genomic point of view, and we can then really, truly, identify all the genetic causation that is involved in diabetes, cancer, how you vote, or whether you respond negatively to being sexually abused.

There are a couple of problems with this view.  First, the system will need to continue to produce and sell new gear, so clearly new things will be discovered that need documentation.  That itself means that even whole genome sequencing is likely to have the shelf life of a banana.  The kinds of things we measure will be shown to be incomplete, and in that sense 'out of date'.  The way we measure the trait--like diabetes or cancer--will be elaborated in this way, so that prior measures will be denigrated as primitive.  We'll have to do the same megastudies over again.

But no matter how comprehensive these tools and data will become--and some have already gone beyond genes, even whole genomes, to enumeration of all cellular processes and so on, as though in recognition that genomes really aren't the answer, but that the research machinery must march on--they will not in themselves solve the main issue that we face:  causation is often clearly complex, changeable, statistically elusive, and not really reducible to an enumerable set of causes.  In addition to making sure that each step is only a partial step--rarely if ever reaching the point where something is actually 'solved' (because that would put us out of business)--we have not really come to grips with the fluid and complex nature of causation of the traits we're interested in.

The more contributing 'causes' there are for a trait, and the weaker that each is on its own, the more unstable their actual effects will be, and the harder to estimate accurately, the less useful such estimates will be as predictors.  In a sense, the trait may be the same, but its causes always substantially different.  The problem is dealing with the trait, rather than attempting to enumerate its ephemeral causes.  How to do that is for the future, if we would really come to grips with it.  That, we think, is where real innovation, rather than the kinds of technical improvements that are steadily being made, will have to come.

Whether in a population that is already 7 billion strong, it will be good to continue to nibble away at the causes of traits that affect us as we age, or whether we'll just be creating countless new problems due to stress on resources and so on, is essentially a philosophical question.

The Lobbyists: the emics and etics of our culture

Much of what human culture is all about has to do with the distribution of resources--material resources such as wealth or property, and psychological resources such as power and prestige. Anthropologists studying the world's populations routinely observe what people actually do, and ask people what they believe that they do. The first, what a culture looks like to an external observer, referred to as 'etics' in anthropology-speak, is usually not the same as the latter, the insider's view, the 'emics'. People may routinely act in ways that deviate from the accepted tenets of their culture, for various reasons including self-interest, and this is often rationalized by the 'deviant'.

Anthropology has a long tradition of labeling cultures by some major feature--'The Basketmakers', 'The Fierce People', and so on. While anthropology is popularly seen as the study of the exotic 'other', the same principles of analysis also apply to our own culture. These days, one might refer to the US and other industrialized cultures as "The Lobbyists". What we do is organize, posture, dissemble, advocate, pressure, and persuade to gain preferential access to resources. Scientists may be among the most educated people in our society (according to some definitions of 'educated', at least), but we are not exempt from emic-etic differences.

Lobbying for research funds is part of our system. Lobbying includes providing, stressing, repeating and so on, our reasons why this or that particular project that we want to do should be funded. There is always an emic element--some justification of the argument in terms of our beliefs (e.g., that this will lead to major health advances). But the facts are routinely stretched, dissembled, and strategized in order that we, rather than somebody else, will corner the resources. We even give our graduate students courses in 'grantsmanship' which often if not typically amounts to teaching how to manipulate the funding system--it's certainly not about how to share funding resources!

We, your bloggers, often complain about the kind of science that is being funded. Among the reasons are not the sour grapes of being deprived of resources, because we have done well for decades in that regard, but that we are unhappy with the hypocrisy and self-interest intrinsic to the system. We think that is not good for society, and not good for science.

From an emic point of view, our complaining may be OK--what science is doesn't match what it is supposed to be! But our complaints probably reflect a poor acceptance of the etics of the situation on our part--science works like all other systems for sequestering resources, and we should not expect it to be perfect or in perfect synch with its emics.

Anthropologists are trained to try to be detached when evaluating a culture, even their own. From a detached, anthropological point of view, our system (our mix of emics and etics) is what it is. As anthropologists, perhaps we should learn to accept these realities, rather than complain about them as if emics could ever be identical to etics, which they never are. Whether the discrepancy in relation to science and its lobbying is serious, damaging to society--or, despite its lack of complete honesty actually good for society--are interesting and important questions, that themselves require one to specify what is good, and for whom.

In understanding our culture as The Lobbyists, we should not be surprised at its nature: we understand how it is, and the game is open to all to play. We are as free to dissemble as anyone, and we can dive after funding resources as greedily as anyone. In fact, the players generally (if privately) recognize the nature of the game. In that sense the rules are known so the game is fair, as games go.

Still, we have not been able to accommodate our views on science to the etics. We try to cling to our emics, thinking that science should be more honest and free of vested self-interest or greed. It doesn't take away from our, or anyone's skepticism about what is being said or done in science these days. And if the science is distorted because of its material or psychological venality, it is fair game for criticism--it may that only if at least a few point out the emic-etic disparities that things are adjusted to stay within societally accepted limits. Still, we should probably just learn to accept that we, too, are part of the The Lobbyist society!

Since the deadline is nearing, we have to end this blog, so we can get back to work on our stimulus-package grant application.