Today, I came across an article and, because it hit so close to home, I decided to share it here. Full article can also be accessed here.
Blocked
I find writer’s block to be quite a fascinating thing.
It’s really a great reason for an author to be not-writing (read reason as excuse). And the best part is, it is considered a valid one, too. It’s the exact reason I am not writing a blog post every day.
In fact, it’d be pretty great to come up with terminologies for every kind of block that a PhD student might face. Like the “lab-experiment-block” or the “reader’s-block”. Or just plain old “work-block” that could fill in every time we don’t feel like working.
However, I do think even the far-better-evolved excuse of writer’s block would stop working so well for me once I start writing my PhD thesis (like everything else in science that doesn’t work).
Anyway, the other day, I was listening to this podcast “No Such Thing (As Writer’s Block)“. It tells, among other things, the routine of Isaac Asimov, the big sci-fi writer. He got up early morning, sat down and wrote… whether or not he felt like it. Every day.
Writing daily is a little daunting. I have given it a try in the recent past, and well, you can write daily if you want to, but you surely wouldn’t be producing your best work every day. Some days, yes, but not every day. However, statistically speaking, if you write something daily, then you increase your chances of producing something worthy at least some of the days.
Just as doing science daily is a little daunting, and somewhat demotivating if you are not seeing immediate results at least some of the times. But every experiment that you run, adds up, whether it was a failure or moderately successful. The more you put in, the better chances you have of seeing patterns.
Although you can sometimes get lost in “the cloud”, as this professor notes in this rather interesting TED Talk (that you might want to listen to if you are in science, or a problem solver in general).
Buried Under Literature
I recently learned I could get updates on recently published research of my particular field by creating alerts in Google Scholar.
After “learning” this, I realized I had to have it. What was I doing, did I want to get out of my hole after four years of my PhD and realized I didn’t know where the world was going? That was not the way to go.
I should know what the current trends are in my field, where the research is going, and how many people (and which groups) are publishing work that is identical to my own (also so that I can send them hate mail if they publish something I was just about to submit).
So I did that. I followed some of the most notable names in my field, created alerts for their works, and also for articles related to their expertise. Breezy easy. I now just had to follow through.
The thing is, if you have very famous people, they seem to be publishing something every other day (probably some kind of “you become famous, you publish more, you become more famous, you get published even more” infinite loop). And the mails I receive every other day have something from a couple to around ten or eleven titles. But of course, if you have related people in your alerts, then some papers are obviously going to overlap.
Now I am blindly downloading papers I know I’m not even going to read half of – there are lots of interesting titles that I would like to get to know more, but then again, they are not related to the “core” of what I’m doing, and having so much to read already ensures that I’m probably never going to read most of them. But that does not deter me from the simple act of saving all pdfs to my downloads folder, with arbitrary, unintelligible titles, further decreasing the probability of me ever reading them, or even knowing why I downloaded them in the first place.
The only fear I have, is downloading the same paper more than once. I do not want to have it so that I read a paper twice, despite all my precautions, because I apparently had two copies ( one of which did not land in my “Read” folder after I’d read it).
I do not want to waste my precious time on a single paper, time that I could have easily wasted elsewhere, in more fun manner.
Sigh. I should now get back to my other form of wasting time, cataloging all literature in my computer to see if I have a second copy of something lurking in my hard drive (I seem to only have downloaded papers in the past four months rather than reading actual literature).
Very Superstitious
Scientists are the last kind of people you’d expect to have superstitions.
But it’s fairly true – science comes with its own set of superstitions.
Which, if you are new or entirely foreign to the science world, wouldn’t make sense at first. But trust me, as you start delving deeper in there, everybody (or so I think) starts developing some strange set of beliefs that have no reasonable explanation.
For example, you have been trying something that has not been working for you, and you are baffled. It seems to work fine for all those other research groups that have a research publication out on the same topic every couple of months. So it definitely works, but what in the world are you doing wrong?
Then you either realize yourself that it must be your “handling”, or you talk to someone who is doing this already and they tell you something particular they do when they do it (in other words, it must be your handling). So you start doing some ritualistic “prep” steps before you begin the process (nothing creepy like animal sacrifice or the kind, but more related to some general lab washing protocols, or how many gloves you should set aside for a protocol, or some equipment settings).
So now, if it works, it was due to this “new” thing, although it doesn’t make any sense why that should have affected the procedure to such a great extent, if at all.
And if it still doesn’t work, then no idea why it didn’t. But congratulations, you have still added a dubious step to your protocol, which you are not sure of, but that’s how it is done, so that’s how it is going to be for all future generations of researchers (and let’s keep it, because it is “good” practice, after all).
So in a science lab, you’ll probably find lots of things that have no logic. People do specific things because they believe that if they don’t wash their slides exactly 4 times, in the right sequence, for the exact amount of seconds, then 11 steps later, they’d discover it didn’t work – again (and well, we are methodical). Or they have procedures that seem to have this seasonal dependency on what month they are being done in (which, again, is not related to position of stars in the sky or if Mars is in retrograde or not). And of course, if that machine is not starting up, drat! That’s because it’s Friday. It’d be fine on Monday.
When you are working in areas that you don’t know anything about, when you are wandering into the unknown (that is the whole point of getting a PhD: to add something new to the knowledge existing in the world), then it sometimes becomes an emotional need to hold onto some explanation before we find out the real one.
So we develop theories on why something isn’t working. We make links where none exist. And this is where we are supposed to be good at, too, because ultimately, on the verge of discovery, this exact habit comes into play, when a reason finally clicks into place for some phenomena that’s been defying all explanations so far.
And in the world of science, some things do work without you knowing why. And often, that’s just how it is (until someone writes a paper about it).
That Doesn’t Work
For the last four months, my PhD has accumulated into wonderful experiences of “okay so that doesn’t work”.
Which is good, because every time one thing doesn’t work, there’s one thing less to discover that doesn’t work, getting you one step closer to the thing that does work.
So you have this recipe/procedure/protocol that you need to optimize, or get the best out of. You start off with rather good energies, thinking the most it will take you is, what, three weeks? It seems pretty simple. You’ll easily find the best way to do it in that much of time.
As you try on and on, you realize there are so many factors and parameters that are affecting the whole process. And to get to the best possible option, you will need to twiddle with all of those (ALL of those, one at a time. And then of course you have to make sure that once you are checking one factor, something else doesn’t meddle in and give you some kind of false positive or negative).
But…
… Do you even have all the options jotted down? There might be more. There must be something you are missing.
… What if option G was the best recipe? It did give some results but you probably went ahead trying H, I, J, K, L because you may discover something better (there might be no “better”, but you’ll need to find that out for yourself, now, won’t you?).
… Would “better” pass off as “best”? What even is meant by “best-possible recipe/procedure/protocol”? Is there a “better” than what you are considering “best”?
After everything, you end up with lots of data, most of which is just proof of how, mostly, it doesn’t work (if you are lucky, it may be otherwise). Obviously, there’s always a chance that nothing is going to work. And it might be some time before you realize that you need to change the whole game plan.
I mean, a PhD is like life in real time. So you want to learn about life, go get a PhD: It will teach you things in a couple years that you might take decades to learn otherwise.