I've only scanned the comments, but the chief reaction seems to be exactly what you want for a scientific approach--people are arguing about the scope and methodology of the study. A paper like this is not some broad-reaching conclusion--it's very specific and based on some potentially flawed methodology. You want people to qualify exactly how specific it is and talk about potential flaws in its approach. That's how you improve the general knowledge.
Also, I suspect there are a couple of reasons such studies are uncommon in computer science. For one, CS isn't really a science; programmers and computer scientists are not trained in the scientific method or experimentation (beyond their general education); almost no CS papers I've read have contained empirical studies. If anything, they are closer to math papers than science papers!
Additionally, this sort of study is basically sociology. (Or something similar.) These sorts of fields are considered a little shady by hard scientists, and CS people tend to empathize more with the latter. I think this explains the immediate attack on methodology.
All that said, having more studies done about these questions would be great. I'm just not sure who's the best to do them. Maybe HCI researchers? I can't help thinking that the really intense PL people I know wouldn't be very interested in doing this.
"Almost no CS papers I've read have contained empirical studies."
You aren't reading the right papers then. At least in Software Engineering, you can't get into the main conferences (ICSE and FSE) without a pretty significant empirical study.
That's a broad brush, and though it's probably a good categorization, I don't find this distinction to be all that useful as a boundary. For instance, the field of artificial intelligence and cognitive psychology branched at one point, so much of my work in cognitive architecture and algorithmic modeling necessitates user studies. One would be hard-pressed to bucket AI into software engineering though. Likewise, in machine learning, I've seen a push from classical data-driven to modern "data-informed" approaches to analyzing these results. Computational linguistics (NLP) and computational narrative are yet additional examples of fields that often requires user studies or other empirical data.
More to the point, the distinction of what is and isn't computer science has become even more blurry in the research community because research in itself has become more inter-disciplinary. There seems to be little to gain from attempting to "bucket" research into distinct taxonomies.
Also, I suspect there are a couple of reasons such studies are uncommon in computer science. For one, CS isn't really a science; programmers and computer scientists are not trained in the scientific method or experimentation (beyond their general education); almost no CS papers I've read have contained empirical studies. If anything, they are closer to math papers than science papers!
Additionally, this sort of study is basically sociology. (Or something similar.) These sorts of fields are considered a little shady by hard scientists, and CS people tend to empathize more with the latter. I think this explains the immediate attack on methodology.
All that said, having more studies done about these questions would be great. I'm just not sure who's the best to do them. Maybe HCI researchers? I can't help thinking that the really intense PL people I know wouldn't be very interested in doing this.