You are still misunderstanding me. The
set of computable reals given by Turing's definition is exactly the same as the set of computable reals given by the modern definition.
However, under Turing's definition there is no algorithm that can uniformly compute addition or multiplication! This has nothing to do with whether the set of computable reals is closed under those operations (although it is, of course - this is an easy exercise, no need to cite a paper).
I'll be more formal. Let us say a Turing machine A is a "Turing-real for x" if A outputs the successive digits of x when run. Then consider the following problem: given two Turing-reals A for a and B for b as input, output a Turing-real for a+b.
It turns out this problem is incomputable!
On the other hand the same problem but for the modern "approximation-reals" is computable, a marked improvement.
The lack of computable addition and multiplication is the flaw in Turing's definition. This is well known stuff - there's even a discussion of it on the Wikipedia page for computable reals. The fact that you keep bringing up orthogonal issues, like closure of the computable reals and the distinction between a Turing machine coding for a real and the real itself, makes me think that you might be missing the crux of the matter here.