Via the Wall Street Journal:

In the latest study, Kimmo Eriksson, a mathematician and researcher of social psychology at Sweden’s Mälardalen University, chose two abstracts from papers published in research journals, one in evolutionary anthropology and one in sociology. He gave them to 200 people to rate for quality—with one twist. At random, one of the two abstracts received an additional sentence, the one above with the math equation, which he pulled from an unrelated paper in psychology. The study’s 200 participants all had master’s or doctoral degrees.

Those with degrees in math, science or technology rated the abstract with the tacked-on sentence as slightly lower-quality than the other. But participants with degrees in humanities, social science or other fields preferred the one with the bogus math, with some rating it much more highly on a scale of 0 to 100.

Specifically, 62% of humanities and social science scholars preferred the paper with the irrelevant equation, compared with 46% from a background of mathematics, science and technology.

This is a significant result, and I hope the experiment is repeated and replicated. It is all well and good for humanities and social science scholars to mostly eschew the use of mathematics in their work. But if humanities scholars begin to take work more seriously simply for the inclusion of (faux-) mathematics without themselves understanding the mathematics, then maybe it’s time for humanities and social science scholars to increase their mathematical and statistical literacy so as not to be so easily tricked by faux-mathematical rigour.

And this isn’t just a case of not understanding the equation — it seems like a nontrivial chunk of humanities and social science scholars have quite an inferiority complex. That should be a great embarrassment; there is nothing inherently inferior about the study of the human condition, or its (mostly non-mathematical) tools.

Well-written work — whether in plain language or mathematics — requires comprehensible explanations and definitions, so that a non-specialist with a moderate interest in the subject can quickly and easily grasp the gist of the concepts, the theory, the reasoning, and the predictions. Researchers can use as complex methods as they like — but if they cannot explain them clearly in plain language then there is a transparency problem. Without transparency, academia — whether cultural studies, or mathematics, or economics — has sometimes produced self-serving ambiguous sludge. Bad models and theories produce bad predictions that can inform bad policy and bad investment decisions. It is so crucial that ideas are expressed in a comprehensible way, and that theories and the thought-process behind them are not hidden behind opaque or poorly-defined words or mathematics.

But in this case, I think the only real solution is mathematical and scientific literacy.

On the other hand, prestigious mathematics journals have also recently been conned into publishing papers of (literally) incomprehensible gibberish, so it is not like only humanities and social science scholars have the capacity to be baffled by bullshit.