Quantity & Quality

Last week I wrote about what I consider to be an inordinate amount of trust in monetary instruments (see “Nothing is Certain but Death and Taxes“). This week I will follow up with a consideration of something that also seems to be trusted religiously: the specter of science.

I have long since been stupendously amazed at this quasi-religion — and I have little or no doubt that it is truly a matter of belief (if not even something like blind faith). Very few people have an adequate understanding of how science works, the scientific method and stuff like that.

I will spare you (and myself) the effort of trying to clarify such issues once and for all. Instead, let me try to draw your attention to one quite widespread notion that is based on a related misunderstanding of science. This is the very well-known (and therefore widely believed valid) distinction between “hard science” vs. “soft science“. Quite similar to the term “social media”, these terms are bandied about all over the place … yet I doubt they have been adequately defined anywhere. My experience with the term “social media” is that when I ask people to define the term they are usually completely baffled — and then they answer “facebook” or “twitter” or something like that. Just to clarify: If I were to ask someone to define the concept “planet”, then the answers “venus” or “mars” would not be adequate (these are merely examples of planets, they do not define the concept).

I have a vague hunch that many people view the nebulous distinction between “hard science” and “soft science” as roughly analogous (and perhaps even equivalent) to the distinction between quantitative statistics and qualitative statistics (by the latter term I predominantly mean “nominal”-level data, and perhaps also research methods such as the widely popular “case study”).

As I wrote a few years ago [1], I am rather skeptical about such muddy distinctions. Long before I became interested in scientific methods (and the so-called “scientific method” — as if there were actually something like a scientific Bible engraved in stone or at least clay tablets, or maybe a golden figurine of Archimedes bathing in a tub of water), I became familiar with the concept of GIGO (“Garbage In, Garbage Out”), a term which ought to be more widely recognized with respect to so-called “big data”. Today, many things beyond body parts are measured with rulers, tape measures and many more contraptions which will spit out numerical output streams and data streams streaming whatnot mind-numbing numbers.

What is commonly overlooked is the simple fact that numbers do not inherently refer to anything. It is only in combination with unambiguous operational definitions that such quantitative data become meaningful in any way. If I were to say “I saw a dozen examples”, then it would be completely meaningless without answering the question: “Examples of what?”