Raghu Parthasarathy points me to this post and writes:
I wrote after seeing one too many talks in which someone bases boolean statements about effects “existing” or “not existing” (infuriating in itself) based on “p < 0.05” or “p > 0.5”. Of course, you’ve written tons of great things on the pitfalls, errors, and general absurdity of NHST [null hypothesis significance testing], but I’m not sure if you’ve ever called out the general error of “binary” thinking, and how NHST enables this.
In reply, I pointed him to these old posts:
Your second link contains a very interesting sentence, that “We live in an additive world that our minds try to model Booleanly.” Often, when people criticize science, a common complaint is that science and scientists want to see complex issues as “black and white.” However, science that’s done well doesn’t do this, as you’ve written many times—it recognizes and quantifies uncertainty, complexity, and all the rest. One could argue that the “our” in “that our minds try to model Booleanly” is the view not of the non-scientist lay-person, nor of a “good” scientist, but rather that of a naive scientist who hasn’t moved beyond the simple textbook picture of science that we teach people at young ages.
I replied that I do think it’s a human tendency to understand things as Boolean, maybe because such rules are simpler to remember and compute.
To which Raghu responded:
You’re probably right. There must be some interesting psychological / anthropological / historical work out there on when people (either as individuals or culturally) start to, at least sometimes, adopt continuous rather than binary measures of causes & effects.