Early Warning Systems May Help Predict Potential Refugee Crises
COLUMBUS, Ohio -- When natural disasters like hurricanes or floods threaten, experts can usually give people early warnings so they have time to prepare.
Now social scientists are working to develop similar early warning systems that can forecast political and social disasters that are sometimes deadlier and more costly than natural calamities.
In one new model, researchers have identified some of the important factors that may predict refugee migrations within a country or from one country to another.
Refugee migrations are not random occurrences -- they stem from political and social problems that can be predicted, said Craig Jenkins, a professor of sociology and a researcher at Ohio State Universitys Mershon Center for International Security.
We think it is as important to predict refugee migrations as it is to predict hurricanes.
Jenkins developed the model with Susanne Schmeidl from the Swiss Peace Foundation in Bern, Switzerland. The model will be published this year as a chapter in the book Preventive Measures: Building Risk Assessment and Crisis Early Warning Systems (John Davies and Ted Gurr, editors; Rowman and Littlefield, 1998).
Using 1971-1995 data from the United Nations and other sources, Jenkins and Schmeidl identified both long-term, root causes of refugee migrations as well as the more immediate factors that sparked the crises.
They found that the major root causes included weak governments, long-standing ethnic antagonisms and inequality, and poverty linked to economic dependence on other countries. Large migrations were often immediately preceded by some type of generalized violence: civil wars, genocide or politicide in the affected countries, or foreign military interventions.
One unexpected finding was that population growth and density in a country was not related to refugee crises. Many policymakers have argued that population pressure is one of the central sources of humanitarian crises, but we didnt find that, Jenkins said. It may be a general symptom of less-developed countries, but not of crisis-prone countries in particular.
Although most of the factors associated with refugee problems are not surprising, Jenkins said there has never been a systematic effort to collect all the relevant data and use it to forecast -- and possibly prevent -- social or political disasters.
The United Nations and various humanitarian agencies currently do international monitoring to predict when and where disasters will occur, Jenkins said. But they use the information mostly as a crisis management tool, to plan for dealing with the disasters.
We hope to develop warning systems that are more complete and accurate so that we can identify potential trouble spots long before they erupt and possibly prevent problems from occurring, he said.
Of course, compared to forecasting a hurricane, there is a much larger margin of error when youre trying to predict forced migrations. But were taking small steps that may eventually help us prevent or at least mitigate some of these social and political disasters.
There is a huge need to predict and prevent refugee problems, according to Jenkins. In 1970, there were about 14 million people worldwide who were displaced from their homes, either to other countries or within their own. By 1990, that number had skyrocketed to 39 million. The number dropped slightly between 1990 and 1995.
Jenkins said he is now working to improve the model in order to make it more accurate. One avenue he is exploring is identifying the factors that lead to political meltdown in a country. Political instability and violence in a country often lead to refugee problems.
The need for humanitarian early warning is great, he said. Once political violence has broken out, its usually too late to de-escalate the conflict. We need to develop better information on the root causes, especially inequalities and ethnic problems. And we also need better information about conflict escalation and the factors that immediately precede refugee migrations.
This research was supported in part by the National Science Foundation, Ohio State University, the Mershon Center for International Security, The Ameritech Foundation and the Centre for Refugee Studies at York University in Canada.#