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 that define a successful insurgency. You don’t really have to read past the first one to see that the train derailed itself before it even left the station. Can you say Mao? How about Tamil Tigers? Shining Path? The “Man-body” feature is an exception to the history of insurgency, not a feature of it.
This sort of inference exemplifies the danger of completely decontextualizing the math from the reality. But it also amply demonstrates the weakness of utilizing descriptive tools to try and predict the future, as so far all of the predictions that this group have made have failed to pan out (see the video for an admission thereof).
Power law relationships are descriptive, not causal. They don’t actually tell us anything other than what an equilibrium condition may actually look like. And that’s really the strength of the work that Gourley has done. If the -2.5 slope coefficient truly is a robust finding, it can provide us with a metric against which we can judge success or failure of particular policy actions. It can also serve as a reality check for game or simulation runs, provided we keep in mind the descriptive nature of the math.
If we can take findings like this one and then contextualize them in terms of other models such as Violent System Theory or other constructs, we might make some headway in understanding how we can interdict a hostile environment successfully. But the inferences drawn by Gourley and his cohorts are not only wrong, they are dangerous, as they stand a good chance of getting American soldiers killed if improperly applied in reality.
Social science academia needs a good dose of humility concerning its own evaluation of the usefulness of mathematics and quantitative tools where human behavior is concerned. If academics like Gourley continue to be taken at their word without frequent and lethal doses of skepticism about the applicability of the tools used to draw inferences, the lesson in humility will be learned at very high cost in human lives.