I don't know whether an editor or the writer himself is to blame, but the headline pretty much contradicts the article's thesis: that because network techniques are not tested in accordance with normal scientific method, the claims of their proponents are unverifiable and ultimately such techniques will be limited by their inability to prove or explain the phenomena they seem to expose and may even be dismissed as a high-level form of paraeidolia.
Here's a prediction of my own, one that I'm willing to put to the test: if complex systems researchers don't get serious about the scientific method, their field is going to fizzle out, if not crash and burn.
Doesn't sound too worried about the future of 'proper' science, does he? I think he's right, insofar as non-scientists are deeply suspicious of any kind of modeling (see the climate change debate for example), so using controls, double-blinds, and so on are the best way to advance this empirical technique.
There's a huge potential flaw in your prediction: you assume that the true efficacy of the techniques they use will determine the survival and popularity of the research techniques. In the cases indicated, the people deciding whether to continue funding the research are not scientists who understand causal relations worth a damn, and they're very susceptible to spin (in the political sense of the term "spin", of course).
The saddest thing about it is that I'm positive there's something to the theories involved, but they're being squandered by people more interested in the popular appearance of success than they are in true efficacy -- possibly because they ego-identify with the successes of their pet projects, and ensure that they don't pay enough attention to the right factors to recognize the difference between appearance of efficacy and true efficacy.
Perhaps I missed this in the article, but in what "cases" are the people deciding whether to continue funding complex systems research not scientists?
My guess is that a majority of the research into complex systems is funded by the NIH and the NSF. Both of which make funding decisions largely based on the opinions of other scientists.
I don't know whether an editor or the writer himself is to blame, but the headline pretty much contradicts the article's thesis: that because network techniques are not tested in accordance with normal scientific method, the claims of their proponents are unverifiable and ultimately such techniques will be limited by their inability to prove or explain the phenomena they seem to expose and may even be dismissed as a high-level form of paraeidolia.
Here's a prediction of my own, one that I'm willing to put to the test: if complex systems researchers don't get serious about the scientific method, their field is going to fizzle out, if not crash and burn.
Doesn't sound too worried about the future of 'proper' science, does he? I think he's right, insofar as non-scientists are deeply suspicious of any kind of modeling (see the climate change debate for example), so using controls, double-blinds, and so on are the best way to advance this empirical technique.