It sounds like you missed the point. The point of the article was that a lot of PL research is focused on non pure SE problems/domains. That is, a large part o

It sounds like you missed the point. The point of the article was that a lot of PL research is focused on non pure SE problems/domains. That is, a large part of the argument was that only a very small amount of PL research is about designing languages that are intended to be used as programming languages in the software engineering sense of the term. The article gives a myriad of examples of PL researchers who have contributed novel results to non-PL fields of Computer Science by applying PL techniques. In these cases, PL researchers are solving open problems in other areas of Computer Science, such as checking properties of software-defined networks or adaptive Bayesian inference. In these two cases, these are areas where PL researchers applied PL techniques to open problems that other subdisciplines were already studying, and came up with novel and competitive/superior solutions. In these cases, the "purely software engineering"-oriented metrics/goals mentioned in your post are irrelevant -- the scientific contributions of the PL research exist and can be evaluated independently of the software engineering implications of the work. The language is the methodology, and isn't necessarily intended for use in software engineering.