The Science of Writing: Part I: The Very Basics

As I mentioned in my last post, I’ve been thinking of doing a series on how my scientific training has helped me with my writing.  But I realized that before I could just start blathering away about it, I needed to first go over exactly what it is that scientists do all day, since most people have no idea.  In the next post I’ll go over the career path a scientist takes in order to become a professor, since its fairly proscribed and I think not well understood in general.

But first, what exactly does a scientist do all day?  Since most people’s last exposure to science is from high school (maybe college for some), and is limited to a classroom and not a working lab, it can be pretty difficult to understand exactly what might keep a scientist occupied all day.  One could say “doing experiments”, but these usually aren’t the kind of experiments you may have done in a classroom lab.

Before I go any further, I should make the disclaimer that all of my personal experience comes from working in biology labs, and I have no working knowledge of what happens in chemistry and physics labs.  And of course, that reminds me that I should do a whole post on the hierarchy of scientific disciplines and science snobbery, but we’ll get to that later.  Much later.
So if you are curious about what goes on in anything but a biology lab, do not take this as gospel.

So what does a scientist do all day?  Well, there are probably three main things that take up most of a scientist’s day to day routine: experiments, data analysis, and research.

We’ll tackle the experiments part first.  Most scientists do not swan in each morning (or afternoon) and just decide to do whatever experiment takes their fancy that day.  Most of the experiments have been very carefully designed to fit into a framework of a larger question.  And most experiments you will be doing over and over again, in order to gain enough data points to analyze and to confirm the reproduceability of a result.  In all honesty, the work you will be doing for an experiment will be time consuming, repetitive, and kind of dull.  And that’s assuming that the experiment even works.  if your troubleshooting a process that isn’t working, you can add frustrating to the list as well.

In this respect, science is like pretty much any other job.  You do not have exciting breakthroughs with every experiment.  What’s more likely to happen is that you get a result that you think might be exciting, try to repeat it, and then get your hopes crushed when you realize that it was just an experimental error.  No, in real world science, everything moves forward in the tiniest increments, and those increments have to be confirmed and reconfirmed before you can get excited about them.

That leads us to data analysis.  It’s not enough to just do the experiments; you have to quantify the results (often in multiple ways) and then analyze the data statistically.  Basically, this means spending a lot of time at the computer quantifying data, inputting data, and crunching numbers.  Or spending time staring at the computer trying to figure out the best way to do all of that.  Data analysis is where you finally see if all your hard work at experiments is finally paying off.  Did those weeks of carefully repeating that experiment pay off, and you finally have a significant result?  Or is the statistical analysis showing that you just wasted a whole lot of time proving nothing?

When you’re presenting your work to other scientists, you won’t be detailing the weeks you’ve spent doing experiments.  Instead, you’ll be highlighting all of the data analysis you’ve done, and how it proves the point you want to make.  Some scientists love doing experiments, and will do experiment after experiment and put off the data analysis until they can’t any longer.  (This was me.  Probably because data analysis could be so heartbreaking in the end.)  Others love it, and prefer it to doing experiments.  We call these people “theoreticians”.

Finally, the last big part of a scientist’s day to day grind is spent doing research.  And when I say research, I don’t mean doing experiments.  The research I’m referring to involves reading journal articles in which other scientists have published their research.  Lots and lots of new scientific papers come out every week, and you’re expected to know backwards and forwards all the ones that are relevant to your very specific field.  You are also expected to be familiar with papers that may not be directly related to your little corner of the research field, but have a broader general scientific impact.  Basically, you need to closely read everything in your field, and read things outside of it as well.

Since reading a scientific paper isn’t like skimming a novel, all this reading can be time consuming.  The prose is difficult and dense, you have to look carefully over the figures to interpret the data, and you need to understand how they performed their experiments and their data analysis.  Basically, you need to go over the paper with a fine tooth comb in order to determine if the effects they report are real, if they are large effects, and if the data they’ve presented supports whatever model they present in their discussion.  If it doesn’t support their model, why not?  Can you come up with a better one?  What do these results mean for your research?  And so on.  Reading a scientific paper is a very close reading combined with some very critical thinking

This came out much more long winded than I’d intended, but hopefully you now have something of an idea of what generally takes up a scientist’s workday.  It’s really not that much different from any other job, in that a lot of it will be drudgery, a lot will be enjoyable, and some will be in between the two extremes.  Next up for this series, I’ll go over the career ladder that a scientist takes from being a lowly undergrad to the pinnacle of being a tenured professor.

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