Hard and Soft Obscurantism
| Lasse Lien |
I recently attended a presentation by the great social scientist Jon Elster, in which he lamented the state of affairs in social science. Elster has – quite nicely, IMHO – coined the terms hard and soft obscurantism as the main problems. To Elster, obscurantism generally refers to endeavors that are unlikely to produce anything of value, and where this can be predicted in advance. This in contrast to more honorable failures, where a plausible hypothesis turns out to be wrong, leaving much effort without much value.
Soft obscurantism is exactly what it sounds like. Unfalsifiable, impenetrable theories which often proudly ignores standards for argument and evidence that elsewhere constitute the hallmark of the scientific method. Examples are post modernism (Latour), structuralism (Lévi-Strauss), Functionalism (Bourdieu, Foucault), Marxism (Badiou) and psychoanalysis.
But there is a ditch on the other side of the road too. Hard obscurantism refers to mathematical exercises without any tangent to reality, which is useful neither as mathematics nor social science. Another form of hard obscurantism is data mining, or misuse of fancy econometrics, or a combination of the two. Both mathematical games and econometric voodoo give the appearance of “scientificness”, but Elster doesn’t hold his guns about the value created by hard obscurantism either:
“I believe that much work in economics and political science that is inspired by rational-choice theory is devoid of any explanatory, aesthetic or mathematical interest, which means that it has no value at all”
One can of course argue about the size of the size of the total problem, and relative size of each type (personally, I would bet on soft obscurantism as the bigger problem), but the key question is perhaps why obscurantism of either type isn’t gradually rooted out. According to Elster their combined “market share” in the social sciences seems to be growing.