Charli highlighted the recently published work of Sean Gourley in Nature on the patter of frequency and magnitude of attacks in insurgencies, so I wanted to cross-post my critique of this work to initiate a discussion here at Duck.
The cover story of this month’s Nature features the work of a team of researchers examining the mathematical properties of insurgency. One of the authors is Sean Gourley, a physicist by training and TED Fellow, and this work represents the culmination of research by Gourley and his co-authors—a body of work that I have been critical of in the past. The article is entitled, “Common ecology quantifies human insurgency,” (gated) and the article attempts to define the underlying dynamics of insurgency in terms of a particular probability distribution; specifically, the power-law distribution, and how this affects the strategy of insurgents.
First, I am very pleased that this research is receiving such a high level of recognition in the scientific community, e.g., Sean tweeted that this article “beat out ‘the new earth’ discovery and the ‘possible cancer cure’ for the cover of nature.” Scholarship on the micro-level dynamics of a conflict is undoubtedly the future of conflict science, and these authors have ambitiously pushed the envelope; collecting an impressive data set spanning both time and conflict geography. Bearing in mind the undeniable value of this work, it is important to note that several claims made by the authors do not seem consistent with the data, or are at least require a dubious suspension of disbelief.
In many ways I reject the primary thrust of the article, which is that because the frequency and magnitude of attacks in an insurgency follows a power-law distribution this somehow illuminates the underlying decision calculus of insurgents. Without belaboring a point that I have made in the past, the observation that conflicts follow a power-law is in no way novel,
and I am disappointed that the authors failed to cite though I am encouraged that the authors did cite the seminal work on this subject (thank you for pointing out my errata, Sean). The data measures the lethality and frequency of attacks perpetrated in the Iraq, Afghanistan, Peru and Colombia insurgencies, but the connection between this and the strategy of an insurgent is missing.
The authors’ primary data sources are open media reports on attacks; therefore, their observation simply reveals that open-source reporting on successful insurgent attacks follows a power-law. There are two critical limitations in the data that prevent it from fully answering the questions posited by the authors. First, there is some non-negligible level of left-censoring, i.e., we can never attempt to quantify the attacks that are planned by insurgents and never carried out, or those that are attempted by fail (defective IEDs, incompetent actors, etc.). Although they do not inflict damage, these attacks a clearly byproducts of insurgent strategy, and therefore must be present in a model of this calculus. Second, while the authors claim to overcome selection bias by cross-validating attack observations, this remains a persistent problem. Consider the insurgencies in Iraq and Afghanistan; in the former most of the attacks occurred in heavily populated urban areas, garnering considerable media coverage. In contrast, Afghanistan is largely a rural country, where the level of media scrutiny is considerably lower, meaning that media outlets there are inherently selective in what they report, or most reports are generated by US DoD reporting. How do we handle the absence of attack observations for Afghan villages outside the purview of the mainstream media?
The role of the media is central to the decision model proposed by the authors, which is illustrated in the figure above. Again, however, this presents a logical disconnect. As the figure describes, the authors claim that insurgents are updating their beliefs and strategies based on the information and signals they receive from broadcast news, then deciding whether to execute an attack. For lack of a better term, this is clearly putting the cart before the horse. The media is reporting attacks, as the authors’ data clearly proves; therefore, the insurgents’ decision to attack is creating news, and as such insurgents are gaining no new information from media reports on attacks that they themselves have perpetrated. Rather, the insurgents retain a critical element of private information, and are updating based on the counter-insurgency policies of the state—information they are very likely not receiving from the media. The framework presented here is akin to claiming that in a game of football (American) the offense is updating their strategy in the huddle before ever having seen how the defense lines up. Without question updating, in football both sides are updating strategy constantly, but it is the offense that dictates this tempo, and in an insurgency the insurgents are on offense.
This interplay between an insurgency and the state is what must be the focus of future research on the micro-dynamics of conflict. From the perspective of this research, a more novel track would be to attempt to find an insurgency that does not follow a power-law; but rather a less skewed distributions, such as the log-normal or a properly fit Poisson. Future research may also benefit from examining the distribution of attacks in the immediate or long-term aftermath of a variation in counter-insurgency policy. After addressing some of the limitations described above, such research might begin to identify the factors that contributed to why some counter-insurgency policies shift the attack distribution away from the power-law. The key to any future research; however, is to connect this to the context of the conflict in a meaningful way.
Again, congratulations to Sean and his team, I hope their piece will initiate a productive discussion in both academic and policy arenas on the methods and techniques for studying the micro-dynamics of conflict.