Calculating Coups: Can Data Stop Disasters? | Think Africa Press.
In March 2012, junior officers stage a coup in Mali, throwing the country into disarray. A year later, rebels oust the government of the Central African Republic (CAR), paving the way for widespread violence that has made refugees out of a quarter of the country’s population. And at the end of the year in December, an internal political conflict in South Sudan’s governing party and army escalates into a full-scale civil war, killing ten thousand or more.
These conflicts differ widely in almost every aspect, apart from the sense of surprise and helplessness that they instilled in the international community. Mali was lauded as a democratic role model before some soldiers took power almost by accident. The French government, for decades the kingmaker of the Central African Republic, confessed to being taken blindsided by the speed and viciousness with which the conflict escalated. And in South Sudan, the regional organisation IGAD struggled to respond to the conflict, finding themselves unprepared and at odds over how exactly to proceed.
In all three cases the surprise greatly limited the influence of the international community, which if better prepared could not only have intervened earlier and more effectively but could perhaps even have taken pre-emptive measures. This unpreparedness was even more of a shame because in all three cases, the outbreak of conflict had been predicted by statistical models…
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