R is (according to that study) 500x slower than C. But let's say that we have a language that is just 10x slower than medium-optimized C. In that case, a 100sec. program run spends 78sec. in that language and 22sec. in that compute kernel.

Now imagine that you speed up the language by 2x but have to forego the use of efficient C code. Now, the program would spend 39sec. outside the "kernel" stuff and 110sec. in the stuff that used to be a C library but had to be reimplemented.

Then again, even if you consider a "one language" design such as Cython (where you can write code that's between Python and C, both convenience-wise and performance-wise), performance-sensitive code looks markedly different than straighforwardly writing down a program.

This is why the "two language" design survives, even while you see very usable work in pure-C++ or even pure-Java.