Article author here. Agree with your first para, so the above has me puzzled, a bit.
Would you please expand: what impressions do you think the article gives, that are misleading? (And if possible: what do you see or hear that makes you think they are misleading?)
You place so much emphasis on dismantling the 10x claim (writing an entire book about it) rather than software research in general, that an observer might reasonably be left with the impression that there's something more "mythy" about that claim than others. If so, I'd say that's misleading.
Folklore isn't ipso facto false. If folklore gets repeated as persistently as 10x does, I'd say that speaks weakly in its favor. (Please note that I said "weakly".) Because of this, I don't think it's irrational to continue to favor that view, even after debunking those studies. For one thing, the opposite claim is even less supported by data. For another, it fits loosely with my experience and that of others I talk to. Experience in the field may not be controlled measurement, but that doesn't make it rational to dismiss it.
I do think there's something to the 10x claim about individuals; I think interaction between individuals is even more important—100x, one might metaphorically say—and that question is even less amenable to formal study. I doubt that we'll ever see convincing quantitative results on either of these things. Building teams will remain an art, and folklore and myth are the stuff that art is made of.
"Leprechauns" is by no means entirely about 10x developers.
In it I also tackle things like the "exponentially increasing cost of bugs" claim, the Cone of Uncertainty, the "software crisis", the successive mythical reconstructions of the Waterfall bogeyman, the limitations of the "empirically based software engineering" movement and specifically the problem of discipline envy.
If it had only been the 10x thing that turned out to be ill-supported I wouldn't have gotten my knickers all atwist. My beef is precisely that when you look closely most of software engineering looks awfully like pseudoscience.
This article is, in a way, Chapter 1 of the next book, in which I'd look beyond "academic" myths, and try to confront a broader picture of how the software community thinks about itself, and how that perpetuates some of the problems we've been bitching about for decades. (And some of these problems turned out to be non-existent; other very real ones barely rate a nod from academia. That is also part of the problem.)
I may have asked you this before, but do you know of any finding in the research literature that you don't consider pseudoscience? The only one I know of that might come close is research on code size. I've heard that the literature on code inspections is good, but that may just be another myth.