Tuesday, April 25, 2017

More on scientific bottlenecks

If you think of it, even during "peaceful times" academia is full of bottlenecks. I was on a job market just 3 years ago, and  I remember this feeling very well: you get trained for some 12 years (feels long!), and now you pretty much have 2 years (feels very short!) to make a jump to the next level (professorship), with something like only 2-3 attempts per year. So about 6 attempts overall! If you don't make it, you are mentally prepared to quit. Because by that time you are probably exhausted, and you are probably in your mid-30s, and you want a family, a place to live, and the clock is ticking.

So a person arrives at this landing pier and waits for a ferry to come, for a job to open, at mercy of random luck of somebody retiring. Somebody who used to teach exactly the courses this new person can teach; exactly in the field they are interested in; and in the region where they are OK to live. They are waiting there, like Frogger on a moving log, with this very limited time to make the leap. Because after that both the guidelines for postdoc employment, and personal patience, and the faith of potential employers would probably run out.

This bottleneck of possibility feels completely ridiculous. I am sure there are great postdocs our there who can teach courses A and B, but we now need somebody who would teach C and D, and be a good teacher, and a good researcher, and be fine with moving to our neck of the woods. If you multiply all these probabilities, you end up with a ridiculously low number of qualified candidates. Call if "fit", or call it "luck", but it almost feels like a numerical problem. A candidate may be great, and the probability of them finding a job may be quite high, but there are only that many years to try, and only that many openings each year. It's a rather cruel system, if you think of it.

Especially considering that postdocs cannot hibernate like bears from one job season to another.

(And even if they could, they'd loose "research momentum" while in hibernation, so it would not have worked anyways).

I'm guessing good mentorship would really make a difference in this situation, as a mentor could help a candidate to understand what part of their CV or application package to boost, how to hone their research talk, how to get "street credibility" if they are applying to an adjacent field (say, a computational neuroscientist to a computer science position). But it seems that most postdocs don't have this mentorship for some reason.

By the way, that's also the main reason I think age-restricted scholarships are evil. It's bad enough that everybody die, and get older, and are scared of missing the Frogger-train. Adding some artificial deadlines to this story, and making people who were on a maternity leave, or changed careers, or served in the army, - making them explain how they are not as old as they seem to be - that's just plain evil.

I guess time to join some support group, and maybe support or mentor somebody somewhere, to pay it forward and dispel the gloom.

Monday, April 24, 2017

Scientific funding

It seems to me that most people don't realize how much science can be hurt by fluctuations in scientific funding. And that's because most people don't realize how slow and vulnerable "scientific process" is.

I mean, if I didn't know better, I'd probably assumed that money to science is like fuel to a car. You give it a bit more gas, you move forward faster. You take your foot from a pedal, the car goes a bit slower. With this logic, a dip in funding would be just a dip. There was a surge during Obama administration, there could be a dip now, not a big deal, right?

Wrong, sadly. The nature of science is that it relies on thousands of individual people acquiring idiosyncratic skills in a quest for some highly fragmented knowledge. It takes about 12 years to develop a professional scientist: 12 years of manual painful nurturing handover from one person to another. It's quite an investment! And only after these ~12 years this person is ready to inherit one thread of  research, leading in one unique direction.

And that's exactly what makes dips in funding so devastating: it would cut through these unique threads and kill them, tear them off, strangling scientific progress. People are not bears: they cannot hibernate with their labs through the funding crisis, to start from the same place in four years from now. They also cannot just start doing everything 10 times slower (and cheaper) as lizards on a cold morning. They either run their labs (paying salaries, breeding animals, pumping air through HVAC systems etc.), or they stop, and this particular thread of research collapses. The running costs are pretty high. And people need to eat and feed families, so without funding they change careers, or move to other countries, but either way they disappear from science. If a limb gets ischemic - it dies.

Therefore a decrease in scientific funding is not at all like trying to save money by not eating out for a month. You can stop eating out, and you can start eating out again; that's not a big deal. But a decrease in scientific funding, for a taxpayer, is more like not feeding their dog for a year, or not paying their mortgage. When in a year you change your mind, the dog is dead, and the house is taken by the bank. And while it's technically possible to get a new house and a new dog, it suddenly becomes insanely more difficult, much more expensive, and takes way too long.

And for a government, to stop paying for science, is not just about not continuing the work of their predecessors, or correcting their plans in some way. It's more like consciously burning everything their predecessors built, in a pyre. Which is thing not unheard of, obviously, but at least in some cases (say, in case of medical insurance) this ritual pyre is at least advertised as such, and people have at least a chance of forming an opinion about it. There is some discourse, some discussion. In case of scientific funding, I feel, this discussion is largely absent, which is particularly troubling.

Another argument for the importance of scientific literacy, I guess.

Tuesday, April 4, 2017

Diversity statements and academic freedom

Some scholars (?) from Oregon have recently published a manifesto that calls "Diversity statements" that are now required for all newhires in the Oregon State University a violation of academic freedom. Does not it sound curious? Diversity statements violate academic freedom. That's surely something new!

Here's where I read about it:

And here's the full version of the "report" (essentially, a manifesto):

In short, the logic goes as following: Diversity statements invite people to comment on some sensitive topics, such as gender equality, LGBT issues, racial politics, and so on. Presumably, if a person does not share left-wing values, they won't be able to write a "smashing" diversity statement, and thus will be discriminated against. And that would be a violation of academic freedom.

On the surface it sounds kind of logical, but at the same time I feel it is as divorced from reality as it can possibly get. Diversity statements are not supposed to be an expression of one's agenda, neither political nor philosophical. A diversity statement generally serves two rather modest purposes:

1. It allows the candidate to present some of their redeeming features that are traditionally not put on a standard academic CVs, and that are hard to quantify, but that make them a more interesting person. Maybe they had an unusual period in life, a unique experience, some curious background. Anything that makes them less of a cookie-cutter clone of a perfect student. For the hiring committee, these unique experiences are a promise of some flexibility, at intellectual and personal level, and an opportunity for strategic team-building. It's nice to know that as a team we'll be able to better represent the complexity of the world around us; that we are not a set of 12 identical twins that will hate each other within a month! This makes the "Diversity statement" pretty much the only part of the application package where one can spin their personal story, that could otherwise be perceived as a weaknesses, as a strength. For example, you went to grad school really late because you were doing something else for 10 years, and now you have fewer publications behind your belt? Here's your chance to explain that. There are probably other people around that can relate to this story, so it would be helpful to have a prof on the team who knows how this side of life works.

2. Perhaps more importantly, the diversity statement is an opportunity for the candidate to show that they thought about issues of inclusiveness in the classroom, and have at least some ideas, even if rudimentary, about ways in which students may be different; how it can affect their education, and what can be done about it. Nobody is perfect, everything is highly personal, and I am quite convinced that by definition there is no "perfect" diversity statement, but it's an extra opportunity to guess whether the candidate is thinking about these issues at all. Whether they are humble of heart, ready to change if needed, and are driven by kindness. What you don't want is to hire somebody who only believes in tall athletic brunets (or short nerdy blondes, it doesn't matter what profile we are talking about), and is only prepared to work with this type of students. Hiring a person like that would be a huge disservice to the students.

What I am trying to say is that the bar is pretty low. One: be a human. Two: be ready to change, and try to be kind. That's the crux of it; the rest is a commentary.

Moreover, most diversity statements I've seen were written so poorly that writing a passable one should be a really low bar. Gosh, they are usually even worse than teaching statements! And teaching statements are always bad, even in a teaching school; probably because teaching is a trade with little theory, and lots of experience and art aspects to it, which makes it hard to write a meaningful one-pager about these things. But while teaching statements are always pretty bad, diversity statements are even worse. On this background, any thinking human who is not completely evil should be able to do a decent job.

Which brings me to my last point. Actually, as I think of it now, it should not be too hard to write a good diversity statement even if you are covered with tattoos of red stripy star-covered elephants and yellow hissing snakes from toes to shoulders. Because ultimately this whole concern about right thinkers not being represented in academia is a concern about diversity!! (They don't use the word diversity in the "report", as I guess it would have been too ironic, but that's what they actually seem to mean when they say "academic freedom"). A person who can relate to conservative students, and who can describe that kindly and thoughtfully, would be a great asset on any team. They just need to stay practical and write about teaching and work, and not about their treasured philosophy. (Because if they work in political science or gender studies, they can write about it in their research statement, and if they don't - it's irrelevant, exactly for academic freedom reasons). Just think about inclusive classroom, and how you'd make sure that you make your students succeed even if they are tall nerdy red-heads or whatever. Concentrate on topics of outreach, transcending political boundaries, and building a welcoming, constructive atmosphere. And it will be fine.

tldr: It's a non-issue and straw-man argument; diversity statements are useful, easy to write, and don't violate academic freedom.

Wednesday, October 19, 2016

What is the best possible grade?

What is the best possible grade a student can possibly get in a course? The answer seems to be obvious: it is an "A", or maybe "A+", right?

But imagine a student with 4.0 GPA. Would not it mean that this student did not challenge themselves enough? That they took courses that were too simple for them, like CalcI when they ought to have taken CalcII? Would not it mean that they never struggled with the material? Arguably, if you are smart, the easiest way to get a 4.0 GPA is to always pick courses a notch lower than your current level. Then you will surely shine, like a superhero among normals.

Which is curious because from behavioral studies in animals and humans we know that we learn best when we fail in about 50% of the cases. It maximizes information transfer, and so maximizes learning. It is surely very uncomfortable, even humiliating, and it would surely make you question your place in science if you fail on every other attempt, but curiously, all other aspects being equal, that's when you would have learned best.

I obviously don't suggest that we make students fail in every other assignment (it's not middle ages anymore, and we just don't have the mental and emotional preparedness for it), but to learn they should fail at least every now and then. Which typically, for an honest and hard-working student, corresponds to a grade of A minus. Maybe even B plus.

Does not it suggest that grades are useless though?

Anecdotally, it seems to be the case. When I grade objectively, on a rubric with fixed thresholds, I see that non-specialists (students of different majors) and prodigies (students who take senior-level classes in their sophomore year) typically get about half a grade lower than similarly hard-working majors and seniors respectively. But is not it silly? They surely learn more, and in a way the very fact that they take harder courses than they are expected to speaks of their resilience, enthusiasm, and brilliance. But it's not reflected in the grade (although I can comment on it in a recommendation letter).

And if it is silly, what should I do? Just give all sophomores a boost of half a grade? This would not seem fair. Grading on "effort"? I don't think it is possible to grade the effort objectively; some people would just suffer silently, and also it would send a wrong message to students. I have no good solution here, but sure it is an interesting question.

And at least at the personal level I can tell that if I needed to hire an assistant, I would probably always prefer an A minus student to a straight-A student, as A minuses just seem to be more persistent and / or adventurous.

Friday, September 16, 2016

Research / teaching balance

This semester I meant to keep Fridays (one day a week I don't teach) for research exclusively, and resist the urge to catch up with teaching prep work on Fridays. But lo and behold, it took me exactly 3 weeks to relapse. The first week went well: I was writing a research paper. The second week was fine as well, but I had to come in on Saturday for a few hours to catch up with other work. But the third week came, and I'm defeated, at least temporarily. I need to rework a lecture that failed last year (the one about normal distribution - hard topic to conceptualize), write some lab assignments, and so on.

Don't get me wrong, it obviously get easier with time: it seems that had I stuck exactly to my previous year lesson plans, I could have saved about half a day, maybe a day worth of time every week. But I am trying to rework both courses, to make them better: to introduce more group work and primary literature in my intro, and to move the emphasis away from probability theory and towards data presentation in my biostats class. And it means prep work, and weekly firefighting.

Now, here's an interesting blog entry (from 2011, but relevant and very well written) about what it takes to get a tenure in a major research university:


It may seem like a non-sequitur, but actually it's intimately related to the existential threat of research Fridays. The question is: how should I balance research and teaching, in an ideal world? Is research only for vacations and weekends, or is it possible to do it during the week? And also, should it be possible, from the administration point of view, thinking in their shoes? Should we (the people, the faculty) encourage a more even split between teaching and research? We are a teaching college, but an aspiring one: we are a SLAC, as in "Small Liberal Arts College", but we want to become a SLAC as in "Selective Liberal Arts". We are trying to boost our profile, and it means that while teaching takes most of our time and effort, surprisingly, it is research that mostly comes up during tenure evaluations. I mean, if you are bad at teaching, you are fired. But once you are good, or at least decent, everybody just shift to weighing and assessing your research. Is it sustainable? But is it ambitious enough? Are you stretching too thin? Or maybe too narrow? Too many collaborations? Too few? Too little work with students? Too much student work? There are many dimensions to assess, and many considerations to balance.

In a way, it came to me as a surprise that our tenure discussions are actually not that far from that in a major research university, at least in spirit. Granted, we can collaborate with our former advisers, we can be third authors, and the expectations for productivity are much lower; perhaps as much as 5-10 lower (depending on what weight you ascribe to collaborative papers). But the criteria themselves become more and more research-oriented.

There are aspects of this shift that are worrying. For example, I don't quite like the shyness with which the older tenured folks refuse to set clear criteria for the publication record. The reasons for this shyness are actually good and valid: in a small college the same group of people has to discuss publication records of a computer scientist (all conferences), theoretical physicist (all arxive), molecular biologists (typical paper has 30 pages and 12 figures), and synthetic chemist (typical paper has 2 pages and 2 figures). It's hard to come up with clear criteria when every single case is so unique. Yet it is a bit annoying, as in theory this flexibility can be used both to save a case, and to sink it.

But at the same time, there are upsides here as well, and not just because I personally like research. Perhaps the most curious one is that with research emphasized so strongly, our tenure goals are now not that far, in terms of CV building, from job search goals for a person who suddenly decides to leave for another institution. So in way now we can try to just "be successful" as potential job candidates. If we are successful, we'll probably get tenure as a collateral, but if for some reason we won't, we'll still have some decent chances of finding another job. It feels that in a teaching-only college there would be a stronger fork here, a bigger difference between tenure goals and job search goals. In our case it's not that bad, which makes the situation less risky.

And in practice it means: publications, publications, and some more publications. No popular books no textbooks, minimal service. Teaching should be good, but pedagogy related publications, conferences, grants and projects are more important, as they are more objective and more visible to outsiders.

That's the plan.

Wednesday, September 14, 2016

Thoughts about tenure evaluations

It is the season of pre-tenure and tenure evaluations in my college, and all faculty are encouraged to write "testimonies" for their colleagues who are up to evaluation. These testimonies are supposed to be used for the tenure and reappointment discussions, one way or another. I wrote a few as well, and now I'm wondering whether I should also send them directly to the people in question; those who are about to be evaluated.

There are some strong arguments in favor of sharing the evaluations openly and directly. Most importantly, my evaluations are actually very positive, and I think that we humans generally don't get nearly enough praise in life. It's all competition, benchmarking and impostor syndrome all the time. So maybe it would be nice for them to read something good about their teaching and research, for a change. Especially in this relatively stressful time when the meetings are about to happen that will (supposedly) decide their fate for nearest few years, and that they won't be able to attend. Also arguably it is useful to receive some real open feedback every now and then. Of course, they will receive the "evaluator's report" a few months later, but most probably not a single row of my original testimony will be quoted in this final report, or maybe half a sentence at most. Supposedly, testimonies are somehow "integrated" and "summarized" in the evaluation document by the evaluator, but not more than that.

On the other hand, one could argue that if you send nice letters directly to people, you forever wave a possibility of writing a negative letter. Or actually not writing a letter when you are torn or indifferent. Because you would not probably share a negative letter, yet if you are known as a "sharer", but don't share anything next time, the person would infer that the letter was probably negative. That's the whole reason people use secret ballot voting to begin with. Also, I am kind of concerned that some of my praise may be not to the point, as I don't quite understand some of the aspects of other people's scholar work. What if I'm praising them for things that are not actually relevant in their own eyes? Who knows, different disciplines are different... At a risk of sounding paranoid, is it possible to inadvertently "damn by praise" - not even because it is faint, but because it is somehow idiosyncratically not to the point?

For now I don't quite know what to do. Maybe I'll toss a coin really. I really like the idea of transparency and clarity, but at the same time there is a good reason tenure votes are always done by a secret ballot. I am not sure there is an ideal solution, but I am wondering what an optimal solution could be.

Tuesday, August 23, 2016

Advice to computational postdocs: apply to math and CS jobs

If you are a computational neuroscientist, and would like to teach, consider marketing yourself not only to neuro and psych departments, but to math and computer science as well.

Why? Because I'm looking at our place, and how we totally struggle to get good candidates in both computer science and applied math. I guess the cynical way to put it is that both fields are so incredibly useful these days that any person who is skillful in them, and who can also teach (which implies good management and interpersonal skills), can probably find jobs in the industry with much higher salaries. And with similar levels of enjoyment. Either way, the fact seems to be that applied math and computer science are understaffed, despite the high demand from the students. During job searches, for each decent job application we get in computer science, we get 10 applications in psychology, even when the research topics are actually quite comparable.

In practice it means that a good postdoc or grad student in computational neuroscience can at least triple their chances of landing a great TT job if they create two more sets of application documents: one tailored for applied math jobs, and another - for computer science. And while it may seem scary, it's actually pretty easy to do.

Let's give it a close look. In a SLAC, faculty typically teach 4 types of courses:
  1. Intro courses (something every major needs to take in lower college)
  2. Core courses (something every major needs to take in upper college)
  3. Fancy stuff (electives of various kinds)
  4. Crazy fun (like math for lit majors, or computer science for historians)
Basically, if you apply to math or CS dept as a neuroscientist, you need to make them know that you can teach all types of courses from this list, plus establish some "street credibility", so to say. Type (1) is never a problem: it would be "calculus I, II" in math (every computational person can do it), or intro to object-oriented programming in CS. You can do it. Type (3) is also easy: it would be what you do for a living, as a researcher, or maybe some one-two fields nearby; something like modeling, numerical computation, big data analysis, dynamical systems, machine learning, methods in Bayesian statistics, or something like that.

Which means that basically you just need to invent one crazy fun course (which should be relatively easy; just draw inspiration from your hobbies and side interests), and to convince the committee that you can teach core courses: something like linear algebra, differential equations or vector calculus in math; or data structures, algorithms, and discrete math in CS. That is a bit harder, but once you cover some of these courses (one may be enough), you are fine!

Now just reword your research statements accordingly, to compensate for the relative lack of "appropriate" education in these fields, and you are golden. You can apply to 3 times more positions than a straight neuro person would apply, and you would compete in a market with a much higher demand and lower supply, boosting your success rates.