Count me in

It's been a hectic couple of weeks at the university, and there has been little time for writing. Or, rather, there has been too much writing, and a body can only use a keyboard for so many hours a day.

Which is another way of saying that if you wonder where the posts are, they went into methodology papers. Science stuff, you know.

One of the recurring themes in my particular course is that the distinction between qualitative and quantitative science really does not make sense any more. There are different paradigms, to be sure, but the dividing line is not between qual and quant, and they can more often than not be combined to create new insights about various things. It is somewhat counterproductive to think of these things as completely separate entities which only rarely interact, when they do in fact interact more often than not. It is also counterproductive to get into arguments about whether one is better than the other, when the simple truth is that sometimes there is a need for the one and sometimes the other.

Which, to be sure, is a very sociology thing to say. But it rings true.

Here is something to mess up the categories. Imagine a thousand deep interviews, conducted at length, with follow-ups as needed. Imagine then that the results of these interviews are (through some procedure of quantification) condensed into a series of graphs. Would that be a qualitative or quantitative study?

If your thought process is "I wish we had those kind of resources", you are ahead of the game.

Here is another category-disturbing thought. When designing surveys, a traditionally quantitative endeavor, the aim is usually to get some numbers out of it. But in order to ensure that the numbers actually mean anything, a lot of thought has to go into the questions. The respondents only have the words on the questionnaire to work with, and thus those words have to be crafted very carefully to avoid confounding factors. This is a task that requires a non-trivial amount of careful attention, empathy and understanding. In order to get something quantitative out of the ordeal, a qualitative approach has to be baked into the process.

Then there is the whole thing with getting people to actually answer the darn things. Turns out just handing them out willy-nilly is less effective than one might think.

A third category-bender is, surprisingly enough, what has happened in physics. As the units of analysis have become smaller, we run into non-trivial limitations of the hardware used to measure things. On the one hand, this is countered by building ever larger instruments (atom smashers take up a surprisingly large space). On the other hand, this is also countered by admitting that subatomic processes simply do not make sense to human beings, and the admission that we will have to think long and hard about this in order to even know what we are knowing.

As the common refrain among physicists goes: it does not make sense, you just get used to it.

These three examples might be interpreted as arguments for the supremacy of the qualitative method. But that would be to try to answer the wrong question. Determining whether one is better than the other is slightly beside the point if you will end up using both of them anyway. What is more interesting is what it means that this distinction is insufficient in describing the actual work of actual scientists, and what other line of thinking we might replace it with.

To be sure, we have interesting times ahead of us.