Lately much ado is being made of the findings of Sean Gourley and his crew regarding power law relationships they’ve found in insurgency-based conflict. For some quick background, go here: http://seangourley.com/ and watch the 7 minute TED video.
Let me be frank. This is another prime example of academics armed with mathematical/statistics based techniques run amok with statistical inference and a naïve belief that it can predict the future.
First, let’s get some perspective. The discovery of power law relationships in conflict is not new. Lewis Fry Richardson discovered a power law relationship between intensity of conflict and the frequency of its occurrence as early as the 1940s. That discovery has been a result in search of a theory ever since. So far, no one has found a satisfying explanation for why the relationship exists, but it has continued to be one of the most robust findings in conflict literature.
Along come Gourley et al, and suddenly the finding is new again. But his group applied the idea to insurgency to see if the relationship exists there as well, and sure enough, it does. But they take the research a little further down the field and discover that the slope coefficient of -2.5 seems to hold as a common value across all tested insurgencies. On its own, this is an interesting finding.
Wired magazine has published some criticisms of the findings of Gourley’s group, and these criticisms center primarily on the quality of the data they used. I don’t find these criticisms to be particularly insightful, mainly because just about any data can be subjected, accurately, to the same criticism. In the vernacular, it’s all crap, but it’s the crap that we have. To really indict the data, one would have to demonstrate that it has a particular bias one way or the other, and that is a challenging task.
No, where Gourley and crew fly off the rails are in the inferences they make from the finding. On the website I pasted above, have a look at the 14 key features...