Five chunks of career advice from Dan Pink

Daniel Pink is a keen observer of the changing workplace and its implications for the way we think about, and train for, our careers. His A Whole New Mind describes the challenges and opportunities in the transition from an “information age”-based economy to a “conceptual age”-based economy.

Now, in The Adventures of Johnny Bunko Pink has created a comic full of advice for college graduates as they prepare to enter the world of business. It is a joy to read. The manga illustrations of Rob Ten Pas give one a new appreciation of this art form. It is also meant to be digested in one sitting, and there is enough good stuff that, upon completion, you feel as if you’ve just eaten a tasty bag of nacho cheese Doritos, only to discover they are 0-fat and full of protein.

Get yourself a copy and pass it among your colleagues. It ought to spur some healthy conversation. Below the fold, I translate some of Johnny Bunko’s life lessons to the world of grad school, with a wee bit of commentary.

The grad school challenge: balancing diversity and depth

Last spring, Carlos Martinez del Rio visited our program. After one discussion, I asked (as I am wont to do) if he had any advice for beginning graduate students. I recall at the time many of the faculty nodding, and some of the students looking at Carlos, looking at each other, looking at Carlos again, then looking down at their notes, slowly transcribing.

I might be mistaken, but I could have sworn I heard the muted buzz of molars grinding.

His remarks, and my commentary, below.

Will you earn your Ph. D.?

An interesting post from the political science blog The Monkey Cage. Some folks at Syracuse University looked for the best predictors of graduate student success in their Economics program, using as data the records of their past students.

The upshot: the best predictor of passing comps: your GRE scores, having an M. A. degree, and having an economics major.

However, the best predictors of completing the Ph. D. program were different. They combined something very concrete–a student’s preparation in mathematics, with something far more intangible–the strength of their research motivation, as gleaned from the personal statements in their application to grad school.

My take, for what’s it worth.

In most programs, your written and oral comprehensive exam tests your mastery of a set of material, and, indirectly, the work habits that allow you to teach yourself.

But there is a reason grad school is often described as a process of transformation from someone who reads to someone who is read.

Because the second hurdle is the ability to design, and analyze novel research. This takes a mastery of logic (and mathematics is, at its heart, logical calisthenics) and a stubborn drive to see a project through. Those students who work on mastering the literature, but avoid the often lonely process of designing, collecting, and cranking methodically through data and manuscripts, risk the scarlet ABD of academia–All But Dissertation.

We’ll be spending some time in the upcoming posts working on your analytical chops. But in the meantime, don’t skimp on math. Even if your dissertation never requires matrix algebra or integration and differentiation, studying math trains your mind to think clearly.

Keep your writing on schedule

Research as a second language has a nice review of the concisely titled How to write a lot.

The money quotes:

Its basic argument is that if you write on a schedule, rather than according to whim, you will be more productive and happier as an academic writer.

and

Writing projects (even whole writing careers) too often go off the rails when writers abandon their schedule and start waiting for inspiration. Or they never get started because they never consider the question of exactly when they will put all their great ideas into writing.

and, the de-mystifying

Silvia takes great pains to make academic writing seem like an ordinary, non-existential activity. “Academic writers,” for example, “cannot get writer’s block”.

This is wonderfully true. Granted, there are days when you are “on fire” and days when the mind is sludge, the hands cramp, and the heebie jeebies multiply.  On the former days you compose the Introduction and Discussion–easily the most literary parts of a scientific paper. On the latter days, work on your Materials and Methods, draft a figure, even type in your references.

Just write…every….day.  The currency of academia is still publications. And you want to leave grad school with pocket full of cash…

5 essentials for that committee meeting

Congratulations. You now have five academics that have agreed to mentor you as work toward your degree. Although not usually the most socially adept barnacles on the rock, academics expect to occasionally find themselves dragged from their lab benches, their desks, and their comfy “thinking-chairs”, to work with you, as a group, to advise you on your path. Here are a few tips to make the meeting go smoothly.

Eight reality checks for new grad students

Graduate school is not your undergraduate education on steroids. It is a transformative journey in which you spend most of your waking moments training yourself to think and act like a scientist. Along the way you have many mentors and guides, not least of which are your fellow graduate students, the vast literature, and fussy, know-it-all blogs.

But your advisor is undoubtedly the partner most responsible to help guide your way, protect you from egregious political crap, steer you from some mistakes (you will find ways to make enough the way it is) and basically give you the time and space to transform yourself. The advisor’s role is complex and may best be described as your academic parent.

This realization is hard for some, particularly those who just spent some pretty harrowing years discovering both the joys of puberty and that their parents were batshit crazy. But just as every set of parents is different, advisors come in every stripe. The problem is, it is often not clear at the outset what you are getting yourself into. The more considerate, literate, (and, by definition, not batshit crazy) professors go out of their way to lay out their expectations early on. These vary, obviously, but the most basic advice is timeless.

Toward exploring these issues, I present below just such a “Manifesto of Expectations” (repeat to yourself, “It’s all about M.E.”). The author is a colleague who wishes to remain anonymous. I will respect his wishes, save to say that his short-lived career as a left tackle for the Golden Buffaloes was plagued by scandal, not all of which was his responsibility. What follows is some pretty frank (and dead-on) advice. It is lightly edited (MK: and annotated) toward removing the author’s frequent and rather strained metaphors to offensive line play.

5 essentials for your grad school survival kit

Welcome back all. I hope your past few months were productive and restful. I had a blast.

When I was thinking about easing back into the blogging thing, I thought it good to return to first principles. And what could be more first principlish than a set of fives–the first five things a grad student should add to her psycho-social-survival kit as she walks through those ivy-covered doors. So here goes…

The learning curve: a psychological hurdle to creativity

In our second installment from a podcast by Ira Glass, we learn about the steep learning curve in becoming a professional storyteller. One consequence is that you learn to recognize good work sooner than you learn to do good work.

This is a huge insight into one of the great banes of graduate student existence. You are a grad student because someone has recognized your raw talent, because you have a latent barometer for distinguishing good science from bad, and because you have a passion to do good work. Yet unless you are extraordinarily lucky, your first efforts, your second efforts, your third efforts, will be pretty bad. And the painful fact is that you will recognize it as not very good because, as Glass points out, you have good taste.

Remember that this is a common dilemma in mastering any creative skill. If you don’t have the tenacity and the work habits, it will grind you up.

But if you fight through it, and resolve to apprentice yourself to the task, you will move forward. As Gideon said in some earlier comments, you have to immerse yourself in grad school, absolutely drown in it.

Also, note Glass’s little diversion on how you speak to your audience. You don’t underline every third word for its emphasis (i.e., the “BBC voice”). Speak with the tones and inflections as if you were telling a story to friends around the table.

5 steps to building your scientific muscle

One of the basic variables of behavioral ecology is the GUT (Giving Up Time)–the amount of time an organism spends at one activity before quitting to do something else. The optimal solution to calculating an organism’s GUT is simple in principle: you quit one task when the opportunity costs–the costs of ignoring all the other stuff you could be doing–exceed the benefits of what you’re doing now.

That rodents are able to do these calculations with ease is a subject of much resentment among the scientists that study them.

But when do you stick with a project for the long haul? And what can you expect for all the effort? How do you avoid being an active participant in, gulp! an exercise in futility?

One answer is staked out in a recent article in the NYT summarizing the research of Andre Ericsson and colleagues. These are psychologists who study the correlates of expert performance. In other words, what does it take to get really, really, good at something? As their work is summarized in a 918 page tome, and I’m a wee bit behind in my reading the way it is, I will summarize the summary.

…the best way to learn how to encode information meaningfully, Ericsson determined, was a process known as deliberate practice….Deliberate practice entails more than simply repeating a task — playing a C-minor scale 100 times, for instance, or hitting tennis serves until your shoulder pops out of its socket. Rather, it involves setting specific goals, obtaining immediate feedback and concentrating as much on technique as on outcome.

and…

“I think the most general claim here,” Ericsson says of his work, “is that a lot of people believe there are some inherent limits they were born with. But there is surprisingly little hard evidence that anyone could attain any kind of exceptional performance without spending a lot of time perfecting it.” This is not to say that all people have equal potential. Michael Jordan, even if he hadn’t spent countless hours in the gym, would still have been a better basketball player than most of us. But without those hours in the gym, he would never have become the player he was.

So before we get into a knicker-twist over genes versus the environment, the message of this work seems to be that if you want to get really good at something, you have to practice, practice, practice.

But genius = good genes x workaholism.

To me, the more interesting issue relevant to this blog is the question: What sort of deliberate practice, focusing on technique and not outcome, would make one a good scientist?

An artist may paint the same bridge over and over, a dancer may practice her Tai Chi, a guitarist will work on progressions until their spinal. But what should a young scientist do over and over, focusing on the skill and not the outcome? Sure, each profession has a skill set (for me, its fixing tiny ants on tiny triangles of paper attached to stainless steel pins, so as not to immerse said ant in a sarcophagus of Elmer’s Glue)

But what intellectual practice makes you a better scientist? Here are my fives for today:

Flowcharts, how do I love thee?

I haven’t used flowcharts much in my teaching or research, but this may change soon. First, there is this marvelous mashup of flowcharts with web pages to teach copyright law. Biologists have long used keys to simplify identifying critters, but I can easily imagine using flowcharts to teach, for example, the experimental results that would allow you to identify different kinds of population regulation.

Perhaps the real utility of flowcharts for graduate students may lie in the underused but powerful practice of Strong Inference. SI endorses building a logic tree when planning your research so that each experiment tests as many different hypotheses as possible. The end result is that each experiment produced maximum bang for your research buck. I am seeing more and more flowcharts in the NSF grants I review.

How would you flowchart your dissertation research?

Finally, flowcharts are effective ways of detecting patterns in otherwise seemingly inscrutable behavior.