When it comes to prosecuting human rights violations, one major challenge is establishing how extensive those violations were in the first place.
The worst cases of mass atrocities often occur in the contexts of civil wars and protracted insurgencies, neither of which are great research environments. As a result, political scientists and policy researchers are often left only with multiple, fragmented datasets. The situation is akin to Rumi’s parable about blind men touching an elephant — each dataset offers a glimpse of the overall picture of what happened, but none give the whole thing.
So how do we best use what little information we do have?
One of the best methods in that regard is called “multiple systems estimation”, or MSE. The technique is probably best known for being what Patrick Ball, the founder of HRDAG, used to document the war crimes of Slobodan Milosovic.
MSE is still relatively arcane. However, last week Ball posted a great introduction to several new implementations of MSE:
This is a semi-technical introduction to estimating undocumented events by using multiple, intersecting datasets. This approach is called “capture-recapture” or “multiple systems estimation” …
The point of MSE is to use multiple, partial lists of a population to estimate the total population. The method depends on the integration of the lists, in which records that refer to the same elements of the population (called “co-referent” records) are linked in clusters.
If you know a bit of R and are interested in human rights and foreign policy, do yourself a favor and take a quick walk-through of Ball’s post.
In case it’s not obvious: one reason I’d love to see MSE get more traction has to do with ISIS and Syria. If there’s ever to be full reckoning of ISIS’s war crimes (much less Assad’s), it will only happen through the methods that Ball and others have pioneered.
UPDATE: I should have known! Turns out Foreign Policy recently ran a piece by Ball on how to best document Assad and ISIS’s war crimes.