My terrible paper

Three days ago I spent the entire day putting the finishing touches on my terrible, unpublishable fourth chapter. The next morning Iris copy-edited it for me, and I sent it to a professor who sent it back to me six hours later. I would hug him if he wasn't 3000 miles away and if one went around hugging members of the National Academy of Sciences. I spent several hours implementing his enormously helpful comments, and sent it to a second professor very late that night. He sent it back 1PM yesterday. He had it for 12 hours, but I'm guessing he was asleep for at least six of those, so that is pretty fast turn-around also. His comments were also majorly helpful. I spent until 1AM this morning implementing his suggestions. Now I have to update my tables and figures, and I'll send it to my third faculty person. At that point the rapid turnover is likely to stop, as she takes her time in editing and produces masses of highly detailed incisive comments.

This seems like an awful lot of work by some incredibly smart, busy people to vastly improve my paper that is still unlikely to be publishable.

That said, it now seems at least plausible that I will have my degree by the time I leave California a week from now.

Intro to Chapter 1

University rules say I have to have transitions between my chapters. They don't say what they have to be, and my professors don't care, so I'm writing little essays.

Here is the intro to Chapter 1:

Demographers and evolutionary biologists have a great deal to learn from each other. That there is no Demographic Evolution Society or Journal of Evolutionary Biodemography attests to the fact that most biologists, even those strongly interested in population processes and the interactions of individuals of different ages don't fully incorporate the insights and methods of demography. Similarly, most demographers give little thought to why such basic variables as mortality risk and fertility vary with age as they do. Any demographer can tell you that the qx curve is shaped like a U or a J or a bathtub, but precious few seem interested in ultimate explanations of how that came to be. Only evolutionary biology can provide such ultimate explanations. Demography is a social science; questions are expected to have some relevance to humans, and the vast majority are solely about humans. In evolutionary biology the assumption that humans must be interesting is quickly labeled as anthropocentrism.

Human demography offers the evolutionary biologist fascinating questions, tremendous stores of readily available data, and the quantitative tools to analyze them to. Evolutionary biology offers demographers the concepts to understand why humans are as we are, how we came to be this way, and how we differ from other organism. A uniquely human, cultural explanation is not needed to explain a trait humans share with all primates. Where humans are unique, this could be because of evolution, or culture, or more likely feedback between the two. Judging whether a trait of human demography is unique requires the methods and concepts of both demography and evolutionary biology.

Chapter 1 asks how unusual women's post-fertile survival is among primates, and what role culture plays. It combines the tools of demography (in developing appropriate measures of post-fertile survival) with those of evolutionary biology (in the comparative method). The result, it is my hope, clarifies a debate in which people have been talking past each other for some time.

Draft of thesis Abstract

While my committee is happy for my thesis to be a pile of loosely connected papers, the university still expects it to be a single unified document with a single topic, a single Abstract, and transitions. This is a bit of a stretch, considering how far afield some of my chapters are (chapters 2 and 4 for example have almost nothing in common). Here is my first attempt at an Abstract that ties it all together:


Abstract:
Humans are a demographically unusual species in many ways, but perhaps the most unusual thing about our demography is the huge portion of our adult females who are post-fertile. This thesis, in four chapters, explores the evolution of post-fertile survival, attempting to understand, from four different angles, how unusual women are in this respect and how they come to be that way.

Chapter 1 is a methodological and comparative study of post-fertile survival in primates. Post-fertile survival is most frequently measured as post-reproductive lifespan, the length of time between reproductive cessation and death. I show that post-reproductive lifespan is not a useful measure for comparative studies and use demographic life-table methods to create more useful measures of post-fertile survival. I then calculate these measures for several human populations and a large group of primate species. These results indicate that women in all populations experience post-fertile survival which greatly exceeds that in other primates under all circumstances. Non-human primates under natural conditions do not experience significant post-fertile survival, while human hunter-gatherers do.

Chapter 2 arises from the question of whether selective pressures associated with being a care-giver tend to increase longevity, potentially partly explaining women's longevity and therefore their post-fertile survival. The chapter focuses on the tradeoff between providing care to existing offspring and competing for matings so as to produce additional offspring. Data on male primates, in which variation in care provided is much greater than in females, are used in a comparative study. I ask whether these data support the assumption of a tradeoff between male care and male mating competition, and if so if one strategy or the other is associated with greater longevity. I find strong support that such a trade-off exists (males in most primate families invest significantly in one or the other, but not both, and care and competition coevolve in a phylogenetically robust pattern). However these data do not support the prediction that level of male care and degree of sex-bias in longevity coevlove meaningfully.

Chapter 3 is an allometric study of brain size, body size, age at reproductive cessation and longevity in primates, in which I ask if human post-fertile survival is predictable based on primate patterns. Again using life-table methods to create parameters more appropriate for comparative study than those used in the literature, I show that while women's age at reproductive cessation can be fairly accurately predicted based on primate scaling patterns, their longevity cannot. This result indicates that the selective forces which regulate these scaling patterns in primates have been altered or amended in humans.

Finally, Chapter 4 is an experimental evolution study. Using rotifers, a short lived microscopic metazoan, I experimentally make the survival of young depend on the continued survival of their mothers and grandmothers in a species which has no natural care of juveniles. I show that under this regime those familial lines which are longer lived, and which bear a larger portion of their young before mother and grandmother die, increase while others die out. However because of low heritability of demographic traits in this population, the experiment does not demonstrate adaptive change, but rather differential success based on stochastic variation.

Taken together these four papers serve primarily to underscore the uniqueness of post-fertile survival in women. Some have argued that human post-fertile survival is either an artifact of social rather than biological evolution, or a widespread trait in female primates simply exaggerated in human females. These studies make clear that human post-fertile survival must be considered as a novel trait, and its evolution explained as such.

10 days

My thesis is fully written, in the sense that I have a complete, but not final draft of each of the four chapters. This does not mean I can relax. My last chance to file it in person (as opposed to having a friend print it out for me and file it for me after I've left for Europe, which is much less desirable in several ways) is ten days from today. This is little enough time and there is enough to do that I am almost certain I will be filing via friend.

Chapter 1 is all done.
Chapter 2 is being edited, and three more professors have to edit it after that.
Chapter 3 has been edited by three of four professors, and is very close to done.
Chapter 4 I have just finished writing, and will send to its first professor in the morning.

Assuming that the suggested edits to Chapter 2 are small enough to be dealt with in a day, and assuming a lot of other things go quickly and correctly (a large set of assumptions), I can have all the edits from three of my four professors done by Sept 1st, when the fourth gets back from oversees. I then have until September 4th to have him look at and edit three chapters, and implement all his edits, and print it all out and put it all together, before I leave California for the east coast and then Europe. In that time I also have to plan my final talk, make the powerpoint, practice the talk, fly to California and give the talk. It will be a busy ten days, but as my wife says, "at least now you can see the light at the end of the tunnel, or at least know exactly how deep a hole you've dug.

One week

I have one week in which to finish writing my thesis. I don't expect to be blogging much until after Sept. 2nd. Happy Labor Day.

Science and religion

There is a piece in the NYTimes by Robert Wright, trying to reconcile evolutionary biology. He proposes, in effect that if creationists would just accept that evolution happens as it does, and evolutionary biologists would just accept that the universe could have been set up the way it is by a creator who chose natural laws that would lead to organic evolution, we could all just get along. He makes the theistic evolution argument as well as I've seen it made, and I still think it is lousy both in its internal illogic and in its total lack of realpolitik.
The religious aren't about to accept a greatly diminished (or at least distanced) role of God in the universe, and secular scientists aren't going to accept that the fact that there could possibly be some space for God to slip into the cracks that science can't explain yet means that God is a scientifically viable option. Wright's proposed "bargain" wouldn't satisfy anyone, and wouldn't even be more satisfying than the status quo to many people. Wright questions why most people on both sides of this divide seem more inclined to leave it alone than to either argue over it or try to bridge the two views. The answer seems obvious to me: it is not particularly likely that one will either convince someone on the other side, or come to a common understanding, and people have other things to do with their time.

Conversation

"Are you working?"

"Sorta. Writing a negative result I can't publish is hard."

"What are you looking at?"

"My blog."

"That's not your blog."

"No?"

"You changed the formatting. It doesn't even look like your blog."

"You also do not look like my blog."

"Why would I look like your blog? I don't know where you get your notions."

"I get them from Science!"

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.

Why don't males care?

The defining difference between males and females biologically is that males produce smaller gametes than females do. Sperm are much smaller than eggs. This difference is the starting point for most arguments describing how the sexes have evolved divergent traits. In mammal further apparently inescapable differences arise because only females harbor internal development of young, and only females lactate (while male lactation is not unknown, there are no document cases of male lactation providing meaningful nutrition to the young of a species). These three apparently fixed differences underlie most arguments describing the evolution of sexual dimorphisms found in mammals, including the tendency among mammals for females to be the sole caretakers of dependent young.
Paternal care is rarer in mammals than in most other taxa where parental care is the norm. Post-birth maternal care is found in all mammals (most fundamentally in the form of lactation), and females care alone in ~90% of mammal species. This contrasts sharply with birds, where female-only care is found in fewer than ~10% of species. Primates are unusual among mammals in that approximately 40% of genera display at least some male care, according to an older and therefore probably low estimate (Kleiman et al. 1981). Primates provide the opportunity to examine what factors lead to evolution of paternal care, even when sex specific structural factors (internal development and lactation) require maternal care.
Why do so few mammalian males engage in care? Mated individuals face the choice to continue investing in caring of current offspring (bearing fitness costs in the form of time, individual quality and mortality risk), produce new offspring with the same mate, or abandoning mate and young to seek new mating opportunities. In all mammals lack of post-zygotic and post-pregnancy investment from mothers is fatal to the offspring. Males therefore have earlier opportunities to abandon, leaving females to bear these costs for both of them, than females do. Depending upon timing and the particulars of a species' natural history, mothers may also be more likely to successfully raise the young of the abandoning male than a male could be in raising the young of his absent mate.
Males not only have greater opportunity to desert, but also greater potential payoffs. A male's reproductive success increases more rapidly with multiple matings than a female's would (although females may gain social and genetic benefits from multiple matings), and males therefore experience higher variance in reproductive success than females. This variance is often non-random, relying on traits which influence female choice or the outcome of male-male competition. These traits are necessarily expensive in order to serve as honest signals, and potentially reduce males' ability as care-givers (and longevity, reducing their reliability as care givers) as they increase their ability as competitors. Therefore males who have already mated, and therefore have the opportunity to care for their own young, are likely to also be those who could most successfully remate, and have invested heavily in the capacity to do so. A female who has mated may not be of unusually high fitness, and may not gain fitness from remating, particularly given the cost in future grandchildren associated with abandoning current dependent young. Males, lacking internal incubation, are also less certain of parentage of social young (both probabilistically and in terms of lack of individual information) than are females, further reducing the value of social offspring (measured in number of genetic grandchildren). Mated males in this standard case, have more opportunity to desert, lower risk of losing future grandchildren by deserting and higher potential for remating than do mated females. Given these conditions, it is reasonable to turn the question around, and ask not why so few mammalian males care, but why do those mammalian males who care do so?
The clear answer to this question is that these conditions, or at least the fitness inequalities they imply, are not universal. Under certain conditions, males may gain more by continuing to invest in existing offspring than by attempting to produce additional offspring. Where biparental care is necessary for production of successful young, the opportunity cost associated with abandonment and competitive risk taking increases. Under the same condition, male reproductive success is likely to increase less sharply with multiple matings, at least in cases where certainty of paternity is fairly high. If this results in a decrease in non-random variance in male reproductive success, it is likely to also decrease the potential benefit to competing for new matings, and in investing in the weaponry necessary for that competition.

This by the way, was another start to an intro that didn't quite work out. The problem isn't that the analysis is internally flawed, but that it raises issues I don't have the data to address, and doesn't really lead to the question I can answer.

Rejected

The draft I am currently writing is about the fifth attempt to write this particular paper. The initial idea yielded a basically uninteresting paper, but I had all these compiled data and lots of carefully crafted paragraphs, so I rewrote it with the same concept, but a different focus. That didn't work either, so I changed my question, did a bunch of new analyses, got some interesting results and wrote a really mushy, mealy mouthed paper (because I hadn't done enough background research no my new topic to know exactly what my point was). I sent that to one of my advisers to ask him what I should do to make it less ugly. He sent some comments, which required rewriting. I sent that to another adviser who totally eviscerated my introduction and discussion (her list of comments, suggestions and objections was as long as the paper itself), and had some problems with my methods. Her feedback is tremendously useful, and appreciated, despite being painful. So I spent this weekend doing more background reading and yesterday rewrote my introduction. Today I'm fixing the methods and results, and hopefully will get a start on discussion.

For anyone who is interested, here is the deeply flawed and poorly written introduction I just threw out:

Trivers (1972) set the direction of much of the modern study of sexual selection by stating that, "what governs the operation of sexual selection is the relative parental investment of the sexes in their offspring. Competition for mates usually characterizes males because males usually invest almost nothing in their offspring (pg 141)." In this view, female parental investment is a resource for which males are expected to compete, and the less investment males make in offspring, the more valuable the investment of females becomes. The relative lack of paternal investment drives male-male competition, which in turn influences a wide range of other morphological and life history variables.
Trivers' statement then implies that interspecies variation in paternal investment is a key to understanding the evolution of life histories, socioecology and sexually selected traits. While a large and fruitful comparative literature on primate life-histories has matured over the last few decades (e.g. Gage 1998; Lee 1999; Nunn 1999; Ravosa and Dagosto 2007), few of these studies have considered paternal investment as a variable (but see Geary 2000; Mitchell and Brandt 1972; Smuts and Gubernick 1992; Wright 1990). Those that have done so have incorporated data on relatively few species or not coded paternal care in a way that allows for quantitative analysis.
One need not subscribe to Trivers' (1972) view to see paternal care as an important life history variable. Interspecific variation in paternal care may be caused by, rather than causing, male-male competition: because males compete for mates, male variance in reproductive success is relatively high, increasing the opportunity cost to males who provide care (Queller 1997). In this model, male-male competition is predicted to determine both paternal investment and sexual dimorphism. The prediction that intensity of sexual selection on males should be correlated with paternal care is common to both mechanisms. This prediction has been addressed using data from cichlid fishes (Gonzalez-Voyer et al. 2008) and shorebirds (Thomas and Székely 2005). These papers attempt to establish the direction of causality through a series of phylogenetic analyses (Maddison 1990; Pagel 1994) that attempt to describe the coevolution of traits. This type of analysis requires two types of assumptions, each of which is questionable. First, each trait is treated as binary (paternal care or none, sexual selection or none). Second, one must assume that the details of the inferred pattern of past change (or the probability distributions thereof, (Maddison 1990) are correct. There is reason to doubt the validity of these assumptions when studying a group of inter-correlated, continuously varying traits. Furthermore, while these mechanisms are positioned as alternatives, it is also plausible that sexual selection and level of paternal care may influence each other reciprocally.
Sexually dimorphic traits are useful exemplars of sexually selected traits. Observations of sexual dimorphisms were the impetus that caused Charles Darwin to introduce (Darwin 1872), and explore (Darwin 1882) the concept of sexual selection. Where natural selection is expected to act similarly on the two sexes so long as they differ only in gametes, sexual selection may apply quite distinct pressures to each, causing them to diverge. Indeed, primates, particularly Haplorhines (apes and monkeys) are known to display greater dimorphism in species with more intense male-male competition (Mitani et al. 1996; Plavcan and van Schaik 1992; Plavcan and van Schaik 1997; Thoren et al. 2006). The present study presents a comparative dataset, with each species assigned to one of four levels based on intensity of paternal investment. We use these data to test the prediction that paternal care is closely correlated with male-male competition, and to examine the utility of paternal care as a variable in models explaining sexual dimorphism. We specifically predict that if the linkage between dimorphism and paternal care is through male-male competition, models containing both paternal care and male-male competition should have little more explanatory power in describing patterns of dimorphism than do models excluding paternal care. A further prediction is that measures of dimorphism should be more closely correlated with male-male competition than with paternal care, and that this inequality should be robust to phylogenetically controlled analyses.
Primates are an ideal taxon in which to make this type of comparison, as their breeding systems are highly varied and they are well studied. The large number of studies of individual primate species allows a rich field of comparative studies compiling single variables for many primate species (Lee 1999). From this literature we draw comparative data on intersexual canine tooth dimorphism, mass dimorphism, and sex-differential longevity (longevity dimorphism). Primates employ their canine teeth in threat displays, and as weapons, and as such males are expected to invest in disproportionately larger canines when fighting between males is common (Plavcan and van Schaik 1992). Canine dimorphism incorporates information on both mass dimorphism (assuming allometric scaling) and disproportionate investment in canines by one sex. Mass dimorphism, has also been suggested to reflect intensity of intrasexual conflict, but to a lesser extent than canine dimorphism (Plavcan and van Schaik 1997).
Our final measure is sex-differential longevity, which by analogy we refer to as longevity dimorphism. The sex experiencing more intense sexual selection is predicted to live less long (Promislow 1992). This prediction arises both because of direct mortality associated with intrasexual conflict, and because of physiological and developmental tradeoffs between competitive ability and longevity. Allman et al. (1998) compared longevity dimorphism and paternal care in a group of ape species and New World monkeys (Platyrrhini), and suggested that the correlation they found was attributable to sexual selection. However their analysis was not phylogenetically controlled. New World monkeys are unusual among primates in several life history variables (Ross 1991; Wright 1990), including their tendency to have caring and long-lived males. In this light, the correlation between paternal care and longevity dimorphism observed by Allman et al may be attributable to a phylogenetic correlation. As most life history variables are correlated with each other, most are also correlated with phylogeny (Leigh and Blomquist 2007); we examine their correlations in this light.
A more direct link between longevity dimorphism and differential care by the two sexes is proposed based on the value of caregivers. As the selective disadvantage caused by death before a particular age is related to the residual expectation of reproduction at that age (Charlesworth 2000; Hamilton 1966), and as care is a form of reproduction which on the average is expected to occur later in life than fertility, a population that provides care to descendents may experience selection for greater longevity (Chu and Lee 2006). Males who provide care may tend to live as long or longer than conspecific females because of this selective pressure. This hypothesis does not depend upon male-male competition, and therefore predicts that paternal care is an directly important in the evolution of longevity dimorphism.

Short note on writing

Frequently I will think of something I should have said in a paper. I'll be reading a related paper, or writing another section of the same paper, and think, "Damn, I really should have clarified X in paragraph Y." It is always heartening when I go to paragraph Y and find that it does in fact already contain point X. It helps me to believe that I am able to keep track of what my argument is and how I intend to make it for more than a single day.

Speaking of New Scientist:

They have an article about methane plumes found bubbling up from from methane hydrates in the Arctic Ocean near Svalbard, where warming water seems to be releasing (and then redissolving) large quantities of the greenhouse gas. First talking polar bears and now potentially catastrophic climate changing gasses.

Science News that isn't

Google news has a science/tech section which I occasionally glance at to see if there is any interesting science news. Of the 20 some stories on their main page at any given time somewhere between 0 and 2 are usually science. The rest are Tech, including video game reviews, prospects for the newest iPhone app, and other useless hogwash.

The New York Times online Science section is better, but they lump in technology, health and the environment, including stories with no science news involved.

BBC science news is still better, focusing on science (although they always have a few non-science environment stories mixed in). They also tend to get less of the science wrong than the American press.

The source I am starting to like more is New Scientist.

Your biggest misconception about science

Among the frantic madness of trying to finish a thesis, I've been thinking a lot about how we evaluate scientific evidence. This has brought me to realize what I see as the single greatest, most damaging, and potentially most widespread misconception held about science. I'm not talking about disbelief in evolution, or climate change, or the moon landing, or any of the other usual loony bin stories. The misconception I have in mind is at the root of, or at least facilitates, many of these more discussed fallacies.

Imagine if you will that you are an electrician. I ask you to install a solar power system, in which you have specific training, and then to run the power to batteries, outlets and appliances in various parts of a house I am building for my grandmother. You carefully chose the type, size and placement of the photovoltaic panels, figure out how to attach them securely to my roof, how to run the wires, how to ensure safety and consistency of power. You comply with various and sundry codes I've never heard of, use materials whose properties I'm not knowledgeable enough to appreciate, and otherwise exercise your expertise and skill.

I, as an intelligent well-educated person with some layman's knowledge of wiring should be able to ask you questions about your work, and if you know what you are doing, you should be able to explain your choices in ways that make sense to me. Why are you using the more expensive panels instead of these cheap ones my cousin bought? Why does the wire go through there instead of through here? But you would rightly think I was an idiot if I thought I could evaluate the soundness of the plan in all its intricacies. Other than getting independent opinions from other experts, assessing your reputation, or spotting huge obvious flaws like a lack of power to the kitchen, I would have no way of telling if you were really planning an ideal system, or screwing me because you secretly own stock in the company that sells that brand of battery. And if three electricians gave me three divergent opinions on the same design, I would not presume to know which was right without asking a fourth. The same would be true of work by almost any expert in almost any technical field. Non-experts should be able to understand, should be able to spot obvious flaws, should be able to ask multiple opinions, but should not assume they are qualified to assess the finest points. No one without training as an electrician can say if a complex wiring diagram is perfect or adjudicate a disagreement between master electricians.

You've probably spotted where the long analogy is headed. It is often said, quite rightly that any scientist who can't explain his work to an intelligent layman is a fraud (or at least very bad at explaining). I forget the original quote. This, and the general (and correct) view that scientists should feel obligated to explain our work to the public reinforce the view that any thinking person should be able to evaluate the correctness of a scientific conclusion. But if I, having worked as a carpenter and done some wiring, can't evaluate the optimality of a complex circuit diagram, why should I, as a biologist, expect to be able to assess whether the uncertainty is understated in a climate prediction model which took hundreds of person years to design and build, went through multiple iterations, been evaluated by independent experts and are so complex it would take me months of reading just to understand what all of the variables are? I shouldn't and neither should you, unless you have years of intense training in that sub-field. I can read the papers, get a sense of what the question and conclusion is, understand an outline of the methodology. But I have no hope of just stumbling upon a conceptual or methodological error. I have no hope of finding the climatologist's errors if what I read is not the primary paper, but an article written by a journalist who also has no training in climatology. This is the blind leading the blind in trying to find flaws in the color scheme of a digital drawing. If two climatologists with opposing viewpoints were to write a trade book in which they lay out their disagreements, present evidence for their views and question each other's evidence, I would understand the science much better than I do, but I would still not be qualified to say which one of them was right and why.

It is unfortunate that non-experts generally can't evaluate science. It leads to the view that science is esoteric, made up, snobbish, arbitrary, undemocratic, religious and most of the other negative things people believe about science. It is also unfortunate that people don't know, or won't admit, that they can't just sit down and by thinking hard decide whether a scientist's work is useful, novel and correct. But they can't. You can't. I can't either, except in fields where I have reviewed the literature, thought deeply about the issues for weeks or months, read more literature in tangentially related fields, discussed the issues with other scientists and then sat down and written out my objections and concerns. This is why PhDs take more than five years on average. Science is hard and requires masochistic attention to detail, not only for those making statements, but also for those evaluating it. If you could sit down read a few papers on a subject and make a novel, well reasoned and convincing argument showing that previous papers are substantially wrong, you could have a PhD in a few weeks. No one has ever done it (or if they did their was fraud involved.)

This misperception, that anyone can evaluate science is widespread. I know scientists who openly contradict conclusions which are long since the consensus in fields in which they have no particular expertise. I've talked to several extremely well educated non-scientists who claim to have evaluated the evidence for human-caused global warming and come to firm conclusions. My conclusion that humans are causing climate change is based not on my personal review of the arguments pro and con, but on the fact that the vast majority of people who are qualified to judge, including many who were originally skeptics, say that it is no longer reasonable to doubt. But many, perhaps most Americans feel qualified to personally cast judgment based on the evidence. I have seen no polling on this, but expect that a larger number of Americans would tell you they are capable of offering informed opinions of scientific controversies than on disagreements between electricians.

As an evolutionary biologist, I feel qualified to read a book by an "Intelligent Design" proponent and say exactly what is wrong with their argument. I can map the circular logic, find the flaws in their interpretation of the Second Law of Thermodynamics, and point out which references are being misquoted. I can describe exactly how their evidence fails to support their argument, and explain exactly why the argument fails to qualify as a science. A nonscientist, reading these books, and armed with the delusion that if there are flaws she will see them, is likely to believe or disbelieve based on religion, politics and predilection. The scientific soundness of the argument is tertiary. Before I was versed in evolutionary biology, I could see logical flaws in Intelligent Design. But had I been raised with as little knowledge of evolution as I have of climatology, I could have only trusted to expert opinion. Similarly, while conspiracy theories about the moon landing are grossly implausible, I am not qualified to judge the claim that the physics of the landing wouldn't work as NASA says they do. The fact that physicist say it works just as explained is good enough for me.

It is not the moral of this story that you shouldn't ask questions, be skeptical and challenge authority. It is not my intention to claim that laymen should never question the competence and motives of experts. Rather, I urge that we try to be realistic in judging our ability to evaluate complex arguments in fields we don't know much about. I am not an expert in whatever it is you studied, and I am not hubristic enough to think that I am.

Plagaism, homicide and Wyeth

In trying to understand why America's healthcare system is so much more expensive and so much less effective than in other rich nations, I usually blame the insurance companies. But as is common with problems of this magnitude, there is more than enough blame to go around. The New York Times today highlights another major problem: distortion of the scientific literature by moneyed interests, particularly the pharmaceutical companies. Corporate culture, and corporate law, effectively require officers of publicly owned companies to do everything they legally can to maximize profit. A pharmaceutical company, faced with the option of doing something that boosts profits but decreases health, has every incentive to do so, and predictably will do so in many cases. Americans end up spending money to decrease our own health.

The case described in today's article should be shocking, but due to a long standing pattern of this type of thing, is only disgusting and outragous. Pharma giant Wyeth, maker of among many of things, synthetic hormones for hormone replacement therapy, has been paying ghostwriters to write review articles highlighting the benefits and minimizing the dangers of hormone replacement for post-menopausal women. These review articles were then passed to respected medical researchers who published them in their own names (whether for money, or just to boost their publication records, I'm not sure). The ghostwriters are not mentioned. Wyeth used these articles to paint a false consensus that its product was safe, and thereby boost sales and stave of regulation.

"But the seeming consensus fell apart in 2002 when a huge federal study on hormone therapy was stopped after researchers found that menopausal women who took certain hormones had an increased risk of invasive breast cancer, heart disease and stroke. A later study found that hormones increased the risk of dementia in older patients."

Wyeth's behavior is certainly harmful and reprehensible, and may or may not be illegal; they are currently being sued by several thousand former patients or their survivors. What is absolutely clear is that the researchers who went along with this are some seriously sleazy people who should not be allowed anywhere near medicine, or research. One of the first things we tell students in freshman science classes is that you never ever ever put your name on something that someone else wrote. It is fine to quote people, it is fine to collaborate and have everyone involved in the collaboration listed as authors, but we have a name for taking something someone else wrote and claiming it as your own, even with the blessing of the true author: plagiarism.

One of the many reasons plagiarism is illegal, and specifically forbidden in the ethics codes of universities and publishers, is to avoid exactly this kind of nonsense. We are trained to always question the motivation and bias of the author of anything we read. Why does this person take such a sunny view of the medicine? Why isn't that other study that showed increased risk of strokes mentioned? If the author is a well respected medical researcher with no apparent ties to the manufacturer, maybe the medicine really is that good, and the stroke study wasn't done well enough to be worth mentioning. But if the real author is an employee of Wyeth, with the specific goal of boosting sales, our interpretation might be different. This applies as much to the peer reviewers who were tricked into approving these fake reviews as to the average reader. Peer reviewers are supposed to evaluate conflicts of interest which cold make the article less valuable to the reader. Plagiarism makes it impossible to know the interests of the real author, which was undoubtedly the goal of Wyeth's scheme.

All researcher shown to be publishing articles written in part or whole by ghost-writers (a.k.a. plagiarists) should be publicly discredited by both their employer and their publisher. Furthermore, they should be held legally responsible for the harm and deaths caused by their unethical practices. Such sleazebags are bad for science, bad for medicine, bad for patients and bad for America. Although Wyeth is the most identifiable villain in this particular debacle, the "researchers" who shilled for them should lose the reputations they let Wyeth borrow. Laws should be enacted to make it clear that pharmaceutical companies may not produce deceptive scientific literature to boost sales, and are legally and financially liable both for the deception and for any harm that arises from it. Governments and insurers tricked in buying medicines through deceptive practices should be able to collect recompense and penalties from those perpetrating the fraud. If other pharmaceutical companies have been engaging in similar practices, they and their mouthpieces should also be exposed. It took decades and hundreds of thousands of lives lost to kill the Tobacco Institute. I hope that it will take less time to rid Pharma, which uses largely the same playbook, of their homicidal tendencies.

The plan

At the end of this month, I fly out to Berkeley, give a finishing talk, get my advisors to sign my thesis, spend a couple of days closing everything up, and then Iris and I fly to Deutschland. That is the plan. It is an ambitious one, in that only one chapter of the thesis is done, the second needs major revisions, the third my committee members have not yet commented on, and the fourth I am still struggling with analyzing my mountains of data. And two of my committee members, including my major professor, are doing fieldwork on other continents for most of August, meaning they won't be doing much editing and approving of thesis chapters.

But that is my plan, and I'm sticking to it, until I am forced to think of something more realistic.