Some people

So I was kvetching to a friend the other day, pointing out that I could make far more money and work fewer houes with less training and more job security in a country and state of my choice as a high-school biology teacher, when she was so rude as to ask me why I didn't do so. As though that was a realistic option!

Brave=Denotation(Foolish)-Connotation(Foolish)*2

When colleagues started telling me that what I was doing was brave, I knew I was in trouble. People tell you are brave as you march off to war, or volunteer to babysit multiple toddlers around bedtime, or (it seems), when you undertake the organizing of a new scientific society. They mean, "Man, you're going to end up unemployed, but I'm sure glad you are doing it instead of me."

I waited until they had a few drinks in them and had mostly finished going back for seconds on the salmon, then commandeered one of the cocktail tables as a podium. I proposed the formation of an society and then opened the floor for discussion.

The good news is that we now have about 50 members including many of the big names in the field. The bad news is that everyone seems to think I have an actual plan. How will we fund the first meeting? What kind of official and financial structure should we have? Will we take over that other, mostly defunct but somewhat related society for the benefit of their infrastructure and their resources, or will we start fresh? Do we need to incorporate? I don't know any of these things.

So here is what I am doing. I'm organizing the election of a board, and I'm making sure there are people who know what they are doing standing for election. I'm communicating with the people who will organize the first meeting next year. I want the society to exist, and I'm happy to help, but I certainly don't plan to run the thing by myself. That would be a little bit too brave.

Two offers out

We have now interviewed two post-doc applicants. Both are extremely well qualified for their respective prospective positions. Both seem very easy to get along with, and both have been offered the positions. Neither, unfortunately, has yet accepted. The first because she is scheduled for a competing interview today, the other because she needs to make sure her partner can also get a job in Rostock. If we hire both of them, I will have a wonderful research team. With either one we could make real progress.

We still have one more candidate coming, next week, and if my bosses like him we could offer a position to him also. If we end up successfully hiring all three, I will be very happy.

keen but generic interest

The cover letters of the post-doc applications I have received have included statements along the lines of, "I have been following the exciting publications from your lab with great interest." Which is generally hard to believe, as I don't yet have a lab. I have recently receiveced one that makes a statement like this, which begins, "Dear Dr. ," with a space left for the insertion of a name. I can't help but suspect...

Note to those applying for jobs: it is more efective to have and demonstrate interest than to claim it.

Linguistic injustice; it's good to be a native Anglophone

The English language is good to me. Much of my success in science to date can be attributed to my English skills. The quality of my writing and my speaking attract the praise of my peers at least as frequently as the originality or soundness of my ideas. (I am not such a good speller, but at this point that has very little effect on me.) Further, my wife’s work is very much based on her English skills; she teaches English as a second language and edits scientific articles to improve their English.

All this came to mind when I saw this letter
“Awkward wording. Rephrase”: linguistic injustice in ecological journals

and this response
‘Linguistic injustice’ is not black and white

in the journal Trends in Ecology and Evolution (TREE).

TREE is a high profile journal, publishing mostly excellent review articles, but unfortunately most of its content is not free to the public.

I will quote; the letter’s author, Miguel Clavero, begins,

International scientific communication is monolithically dominated by English, particularly within natural sciences. The professional career of individual scientists relies on their ability to publish in internationally relevant journals, and writing in English is the only way to achieve this. Non-native English speakers (NoNES) seem to be clearly disadvantaged with respect to native English speakers (NES) when trying to get their work published. In fact, English language proficiency has been shown to be a strong predictor of scientific output...

This argument makes sense to me. I have colleagues who are both smarter and harder working than I, who are quite fluent in conversational English, who take much longer to write a paper than I do. Writing crisp, clear, precise, flowing science while staying within word limits is hard, and frankly I’ll never learn a second language well enough to pull it off in anything but English. If Greek, Latin, French, Chinese, Arabic or German were the dominant language of science, I would be in deep trouble.

The response published in TREE points out that other disadvantages (e.g., being from a developing country) are vastly harder to overcome than being NoNES. A Swede has a much better chance to succeed in international science than an Anglophone African. A Swede may even come to speak and write English which is better than that of some Anglophones. It also points out that most English language journals won’t reject a paper because of language problems, so long as the science is sound and the writing is comprehensible and reparable. Both of these things are surely true, but don’t negate Clavero’s point. Bad English may not be a huge disadvantage, but skilled beautiful English is, it seems to me, a big advantage, and native speakers are much more likely to speak a language beautifully. This is particularly true, I think, when it comes to job applications. When one is being evaluated not only on the quality of one’s work, but also on one’s presentation skills, ability to answer complex questions clearly and leadership potential, language skills are important. I have seen application talks at the Institute given in such poor English that I had trouble following them; these people were not hired. The graduate students and post-docs I work with are mostly NoNES; a larger portion of the Research Scientist and lab heads are NES or have lived for extended periods in English speaking countries. This is not because of hiring decisions beeing made inappropriately. Rather, those fluent in English tend to be more successful in those tasks on which hiring decisions are legitimately based.

I doubt that English will cease to be the dominant language of science in my lifetime, and for this I am glad. That said, I take Clavero’s point, and I suppose we should add NoNES to the list of groups disadvantaged in scientific careers (females, underrepresented minorities, the disabled, citizens of developing nations, etc.). I am not sure what is to be done about it. Clavero argues that journals should cover the costs of language editing by charging a fee to all authors, whether they need language editing or not, spreading the costs. They would have to waive this fee for those without sufficient funding to cover them. Some journals in fact already do this, paying in-house language editors from author fees. This has not obviated the linguistic injustice. I am not sure what will, short of sci-fi quality automatic simultanious translation technology. I would love to have this technology, if for no other reason than because then I could stop struggling to learn German.

Two talks at once!

My task, apparently, is to give a talk to both audiences simultaneously. Those viewing my job talk will include “a specialist in your field” as well as committee member representing the breadth of backgrounds of the Human Sciences Section of the Max Planck Society. That Section consists of the following Institutes, which I have casually categorized:

Anthropology:
MPI for Evolutionary Anthropology, Leipzig
MPI for Social Anthropology, Halle/Saale

Psychology:
MPI for Human Development, Berlin
MPI for Human Cognitive and Brain Sciences, Leipzig
MPI for Psycholinguistics, Nijmegen, Netherlands

Economics:
MPI of Economics, Jena
MPI for Research on Collective Goods, Bonn

Law:
MPI for Foreign and International Social Law, München
MPI for Intellectual Property, München
MPI for Comparative and International Private Law, Hamburg
MPI for Foreign and International Criminal Law, Freiburg
MPI for Comparative Public Law and International Law, Heidelberg

Sociology:
MPI for the Study of Religious and Ethnic Diversity, Göttingen
MPI for the Study of Societies, Köln
MPI for Demographic Research, Rostock

History:
MPI for Art History, Florence, Italy
MPI for the History of Science, Berlin
MPI for European Legal History, Frankfurt/Main

You will note that I put my own institute, Demography, under the heading of sociology. Demography is in many way rooted in sociology, despite my belief that it should be a branch of biology. You will also note the preponderance of topics such as Law, Economics and Psychology, which have little theoretical overlap with evolutionary demography.
This is, in a way, a brilliant way of evaluating an applicant. Anyone who can describe their topic in a way which is simultaneously comprehensible and exciting to experts in one’s own field and experts in distant fields is at least a talented communicator. If they threw in some toddlers, who also had to like my talk, and maybe a few Tea Partiers, then it would be a real challenge.

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.

Academic constipation

The NYTimes has a recent article about the current academic job market. In two words, it sucks. Professors who thought they could afford to retire are staying on, so positions aren't opening. Even when they do retire, hiring freezes are leaving their positions vacant until the economy improves, so post-doctoral researchers aren't likely to find a tenure-track position, and remain in underpaid temporary jobs. This means there are extremely few positions (as faculty or post-docs) for recent grad-students, and the usual routes out of academia, industry jobs, also aren't available. But while the routes out for grad-students are limited, recent college graduates who can't find real jobs are apply to graduate programs in record numbers.

While the situation is bleaker for the humanities, which have long been in decline economically, the scientific community in the US is keenly aware that however this turns out will have effects that will be felt for generations. The closest comparison I can make is the tremendous expansion of enrollment in colleges in the 1960s and '70s. As the students flooded in, colleges hired large numbers of professors right out of grad school. By the 1980s there were extremely few positions opening up, almost every professor had been hired in the previous two decades, and there were almost no retirements. A whole generation of academics had almost no chance of finding a professorship. I know several people of that era whose careers were permanently put onto alternate tracks because they simply couldn't find a professorship. Then, just in the last decade, that flood of professors hired to teach the baby-boomers have been retiring in droves, and many people were expecting a new wave of hires. More than one person has told me, "When I finished grad school, there were no jobs. When you finish, there will be openings everywhere." Now, given the economy into which I am graduating, I feel lucky to be in a sub-field that has some post-doctoral positions for a few years. Perhaps in three or four years universities will start filling all those vacant positions, and a new wave of young faculty, hopefully including me, will be an impediment to the career aspirations of our younger colleagues.

If this science thing doesn't work out.....

As I've mentioned before, my cousin David is the National Sales Director at Ozone Socks. Ozone has a yearly sock design competition. I submitted three designs themed around (what else?) science.
I just got the call from David. He had to recuse himself from much of the judging, in order to avoid bias. He didn't even tell them I was his cousin, he claims. But my oceanic drawing, "30000 Feet" won second place. Iris will be so excited. We get 12 free pairs of socks.


Oh, and by the way. It is not at all certain they will actually make this sock. They have in effect purchased rights to my design for the price of 12 pairs of any socks they already make. If you want to see this sock made, and would purchase a pair, please contact@ozonesocks.com and tell them.

Le Deluge

I'm in a new place. For the first time in my career, I have gobs of data. Over the last couple of years, with the help of all my students, I have amassed a couple of enormous data sets. I've got this data-gathering thing down.

Faced with all these data demanding to be analyzed, written up and published, I have a new and different challenge. I need to decided which of the hundreds of different papers I could potentially write with all these data I actually will write. In some cases it is obvious that I need to write a particular paper. For other potential papers, it is fairly obvious that the opportunity cost would be higher than the benefit. This still leaves a vast middle ground.

I need to figure out how to think about how many, and which, papers to try to publish soon, which to present at conferences, get feedback, then publish, and which could be filed away in case I ever decide they are important.

Some of this last group I will use as motivational tools for my students, saying in effect, "I will put the time in to get the project you worked on published if you do a particularly good job moving the process along, and I will make you an author on the paper." Relatively few of my papers do I expect to be co-author on. Most I will need to include advisors, collaborators, students, or some combination thereof.

What is clear is that between now and next August (when I will move to Germany) I need to write about two papers a month, which is about two papers a month more than I am accustomed to writing.

Graduating into a Depression

The number of professorships in the country does not vary much from year to year. Usually the number of positions opening up approximately equals the number of professors dying, retiring or moving to other jobs. Occasionally a new campus opens or there is a major expansion of enrollment, and a bunch of new positions are created. Other times the economy sucks (to use the technical term) and as a cost-cutting measure positions are retired or left vacant for a few years. As an example, the budget problems California has been having ever since the dot com bust have caused UC Berkeley to greatly increase the average time between one professor leaving and another being hired.
Right now, professorships are hard to get and I fully expect them to get harder. Somebody or other, a housing economist I think, was on NPR today predicting that the housing market will hit bottom in another three years. I expect the academic job market to hit bottom around the same time, or possibly a year or two later.

Which brings me to me. I will be getting my PhD in a little under a year. I then expect to spend two or three years as a Post-Doctoral researcher in Germany. That should have me searching for an assistant professorship just about the time there are no professorships of any sort to be had.

President-Elect Obama, I think an investment in our nation's universities and research institutes would be a great way to stimulate the economy, improve education and develop the technologies we need to deal with environmental issues and health care. Sooner is better than later. I have this three-year plan.

Strengths

In science, as in most anything, it pays to know your strengths and weaknesses.

I am about as good as anyone I have known at understanding, remembering, integrating and evaluating biological concepts. I am terrible at calculus. I am very good at recruiting, evaluating and training assistants. I am hopelessly slow at learning programming. I have very steady hands for lab work and a hip that is bad enough to keep me from doing much field work. I am a gifted improviser and a mediocre follower of protocols. I am the king of scrounging and am pretty good at applying for funding, but I struggle with remembering to do the accounting or keeping track of receipts. I am a great teacher but a disinterested disciplinarian. I am unrivaled in my ability to start research projects, but need serious improvement in my ability to finish them. I have great fun with ideas but no fun with spelling. I collaborate well but self-motivate poorly. I am good at being blunt and bad at being not-blunt. I am a good scientist, but need improvement as an academic.

What I've been working on

Here is the last bit of my post-doc fellowship application:

Summary and Conclusion:
Evolutionary Biodemography has focused on explaining late-life mortality patterns and overall longevity. The evolutionary basis of early-life mortality has been studied more rarely and less systematically. My proposal boils down to four basic steps intended to firmly establish the field of early-life evolutionary biodemography:
1. Mathematically define and parameterize the age specific mortality patterns that characterize Human-like Early-life Mortality (HEM).
2. Compile, review and organize those evolutionary hypotheses potentially explaining HEM.
3. Use these hypotheses to predict life-history traits that may be necessary causative factors of HEM, and thereby predict which taxonomic groups are not subject to HEM.
4. Gather data to determine in what species or populations, if any, HEM does not occur, thereby testing my collection of evolutionary hypotheses.
Early life mortality has a tremendous effect on a wide range of populations, and our failure to date to understand its evolutionary basis is a major gap in our understanding of both evolution and demography. Working at MPIDR, I will begin to fill that gap.

Compresed Timeline

The Max Planck Society is a network of research institutes, mostly but not entirely in Germany. Many people consider it, to be the world's leading non-university research organization. The member institutes are more or less autonomous in terms of planning and executing research, as far as I understand, but all of them have the reputation for world-leading excellence.

A couple of years ago, at a conference on aging I had the pleasure of meeting the Executive Director of the Max Planck Institute for Demographic Research, Jim Vaupel. At the time, he and my professors, Ron Lee, discussed the possibility of me coming to MPIDR at some point. I was excited by the prospect. Here at Berkeley there is effectively no one outside of Ron's lab group who thinks much about the kinds of questions I do, while MPIDR has a whole Evolutionary Biodemography Lab, at which they think about and work on pretty much everything I do, plus a lot more.
But then I went off to PNG, and then I was injured, and pretty soon I figured the opportunity had passed. But then I got an email announcing that there was a fellowship available through the German Academic Exchange Service (better known by its German acronym, DAAD, for North American researchers to come work in Germany if they had the invitation of a German institution. The email conversation that followed was suprisingly short, spanning little more than 24 hours, and completely reorganized my timeline for finishing grad school. If I may paraphrase, it went something like this:

Me to Ron: Should I apply for a DAAD fellowship to work at MPIDR.
Ron to me: Do you want me to ask them?
Me: Yes, thank you.
Ron to Jim Vaupel: Dan is an excellent young biologist, should he apply for a DAAD fellowship to come work there?
Jim to Ron (to me): Yes, he should apply, but even if he doesn't get the fellowship he should come here as soon as is convenient, and we can support him.

Just like that, no application, no interview, I had a desirable post-doctoral position lined up at a time when the economy is tanking and most of my peers are wondering if there will be any positions for them at all. My deliberations consisted of describing the situation to my wife to make sure she didn't mind spending some time on the Baltic, and emailing Dr. Vaupel to make sure I understood him properly.

What this means for my grad-school timeline is that instead of 16 to 21 months, I have eight to ten months to finish. I was thinking I would finish December of 2009 or May of 2010. After the offer from MPIDR, I thought I would have to finish by August of 2009. Afer talking to my major proffessor today, it is clear I need to be pretty much done by May of 2009.

My department's commencment is May 23rd 2009, and I plan to walk then, if at all possible. I won't actually be finished at that point, but I will be finished enough to convince my faculty persons that I can file my disertation before the end of summer. My wife's graduation from UC Davis is mid-June 2009. That summer I will finish my dissertation, then we will pack up our lives, take the cat's to my sister's house, and fly to Germany.

That seems like a lot to accomplish in one year.

Yikes.

Whither hence?

My PhD is preparing me to be an expert in evolutionary demography.

The question is, what does one do with such expertise? There are maybe ten researchers in the world with a focus on evolutionary demography. How likely is it one of them will need a post-doctoral scholar when I need a post-doctoral position?

You want fries with that?

So many data, so little time.

I first met Jerram Brown in 1999, when I was a senior at Bennington College. My adviser, Betsy Sherman, had been his student many years earlier. I was about to graduate from college and he was about to retire from a very long and extremely successful career in exactly the part of biology I was interested in. For the previous 30 some years he had been studying the behavior, ecology, demography and so forth of the Mexican Jay. I asked him about the possibility of working for him, but I was too late, his retirement plans were gathering momentum. He officially retired in 2002.
When I graduated, I went to work for Glen Woolfenden, who had an almost as long-term study of a very closely related bird, the Florida Scrub-Jay. Glen and Jerram, for reasons I don't know, had some sort of tension between them, and I had no further contact with Dr. Brown's group.

Looking through the program of the Animal Behavior Society Meeting I just attended, I was very excited to see that Jerram Brown would be momentarily be coming out of retirement to accept a distinguished researcher award and deliver a plenary address on his work. That talk was the last morning of the conference, and it turned out far more interesting than even I had suspected.

His data set on the Mexican Jays is shockingly extensive. In addition to the multi-decade highly detailed demographic data, he has an enormous number of ancillary data sets, many of which he had never gotten around to publishing, because he had not found any theoretically important question they could be used to answer. But as he heaped data upon data, I came to realize something. These data he had gathered because he could, rather than because he had a particular question in mind, were potentially exactly the data one of my advisors, Ron Lee, needed to test some of his hypotheses on the importance of intergenerational transfers of resources (in this case food) to the evolution of longevity and sociality. Dr. Brown had records of >26,000 individual food transfers, including who was transferring, to whom, how old each one of them was and how they were related to each other. My heart started thumping. I had to get Jerram's data and Ron's theoretical framework and analytical prowess together. But most scientists jealously guard the data sets they spent their lives gathering. And Ron is already terribly busy with far too many projects, would he even be interested?

Then Dr. Brown said, as part of his planned talk, something I have never heard any scientist say before, even though we probably should all say it sooner or later, "I will gladly turn over my entire dataset to anyone who can make good use of the data." There was a loud gasp. It was me, but not only me, several people gasped. He may as well have said, "I will turn over all this gold ore I have spent my life mining to anyone who can smelt it."

Immediately after his talk, I went up to speak to him. I shook his hand, told him that I was a former student of his former student (in case it helped) and began to tell him about Ron and his work. Another fellow, a Dr. Ha, came up and said that he would like to apply for NSF funds to hire a post-doc to work with Dr. Brown to make sure the data set is preserved and made available. He said that if Ron were involved, this would increase the chances of getting the funding, as NSF would want to know the data would be put to good use.

With some trepidation, I emailed Ron and told him all this. He wrote back almost instantly saying it sounded like a great opportunity, and he would love to join this collaboration, but would want, "some more junior researcher with more years of research ahead of him/her" to be involved, and suggested that I was the "leading candidate."

So this all raises the very real possibility that I may be spending a couple of years immediately after my doctorate applying Jerram Brown's data to Ron's hypotheses (and perhaps a few hypotheses of my own). I haven't yet figured out if this is something I actually want to do, and would be able to accomplish, but the prospect is very exciting all the same.

The Draft

I spent my first few years as a graduate student taking classes, applying for funding, working on projects that didn't work out, teaching and similarly not producing papers. In the world of academic science, publishing papers is pretty much everything, which means that career-wise I was accomplishing pretty much nothing. In the last week I and my collaborators have finished first drafts of two papers that should be quite publishable once they are polished up a bit. And boy, does that feel good.