Good grief. This page is a disaster. Just because Gilbert Ryle's example of a category mistake involves failing to understand the relationship between the parts and the whole of a university, that doesn't mean that's what a category mistake is ... this page is an illustration of a fallacy of affirmation of the consequent, writ large and magnified.
A category mistake is just what it sounds like it is: "the error of assigning to something a quality or action that can properly be assigned to things only of another category", to quote the dictionary. Thinking that a university is a building or some other component of which universities are comprised is just one type of category mistake.
The point of the story is that the visitor has the expectation that the university is a physical object and not an abstraction.
No, that's not at all the point of the story! Universities are physical entities just as buildings are ... one could make exactly the same sort of mistake by wandering through a building examining the rooms, carpets, beams, hallways, etc. and then asking "but where is the building?" In fact, Ryle's concern was Leibniz's mill: http://lolpluslolishihi.blogspot.com/2014/02/leibniz-mill-category-mistake.html
This ridiculous statement from the article makes Ryle out to be some sort of dualist, completely the opposite of reality and of what his whole book was about! The thesis of the book was that dualism is based on category mistakes of this very sort, claiming that a university is an abstraction, as distinguished from a building. No, the concept of a university and the concept of a building are abstractions, but universities and buildings are physical things, with locations and dimensions ... but you won't find a university by wandering through one looking for one. Somewhat [the analogy is quite limited] similarly (and this is what Ryle was attacking), you won't find the mind by wandering through the brain looking for it, because the mind isn't that sort of thing ... it's a collection of dispositions and capacities. Which are not abstractions, they are real things, but not the sorts of things that light bounces off of. For instance, the ability to understand complex philosophical concepts is a real thing that can be detected and measured. — Unsigned, by: 126.96.36.199 / talk / contribs 07:31, 20 December 2017 (UTC)
Category error vs compositional error
My understanding is that the error described in this page is *not* a category error, but rather a compositional error. The distinction I draw is:
Compositional error - when you assume that properties of a whole or part can be applied to the part or whole respectively without independant support for the idea:
When a company becomes more efficient by reducing employee wages it grows. Therefore, if every company in a closed economy cut its wages the entire economy would grow.
Category error - when you create a category is useless for the type of analysis you want to apply because the spectrum of traits used for the selection contradict the use required in analysis:
If you consider "Inflation" to be the union of "consumer price inflation" and "asset price inflation", then this would be a bad category since these two concepts have opposite characteristics and any theory you develop around one of the two entities will have to have its sign changed to talk about the other.
If you consider "savings rate" to include savings rate of the middle class and savings rate of the wealthy, this is a bad category since the two quantities are based on completely different motivational forces and any prediction you make based on examples of one would be unrelated to the other. A stark example of this is that if you think savings rate helps the economy grow, then you could very easily increase the savings rate by moving some of the tax burden from the wealthy to the poor, which would increase the overall savings rate but decrease the savings rate of the bottom 90%. It is not likely that this is what a sincere requester for "encouraging savings" would have intended.188.8.131.52 (talk) 01:11, 22 February 2018 (UTC)