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Refugee resettlement + big data

Refugee resettlement: Using data to improve the system

How big data can improve outcomes for resettled refugees

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Director of Innovation Strategy, International Rescue Committee
Chief Innovation Officer, International Rescue Committee

The United Nations predicts that 1.4 million people globally will need resettlement in 2019. That’s only a fraction of the world’s 25.4 million refugees and 68.5 million forcibly displaced people. And yet only 100,000 people—of the 300,000 people deemed in need—were resettled last year.

Given the scope of the world’s displacement crisis, why is refugee resettlement important? What are the challenges facing the international resettlement regime today, and how can we better facilitate resettlement and integration in the United States and around the world?

Jeremy Weinstein is a professor of Political Science at Stanford and co-director of the Immigration Policy Lab (he was also Displaced host Grant Gordon’s PhD supervisor). In this episode, Weinstein sits down with Grant and Ravi to discuss the origins and objectives of the UN resettlement program, the United States’ approach to refugee protection, and how we can use big data to improve refugee employment outcomes.

Most people fleeing conflict zones seek shelter in neighboring countries; Turkey, for instance, hosts 3.6 million Syrian refugees, while Lebanon hosts nearly one million. Weinstein affirms that humanitarian assistance to those states supporting the largest numbers of refugees is not enough. The United States must maintain its commitment to resettling refugees, both to provide opportunities to a highly vulnerable population and to demonstrate solidarity with the global refugee protection regime. Resettlement is essential to maintaining partnerships between “the neighboring states and others that are further removed from the crisis but invested in an international system in which we have cooperation with respect to managing threats like these.”

Jeremy Weinstein, professor of Political Science at Stanford and co-director of the Immigration Policy Lab.

The key to making resettlement work, Weinstein affirms, is to help refugees acquire skilled jobs that enable them to increase their earnings. Analyzing historical resettlement data, his team at the Immigration Policy Lab found important synergies between refugees’ individual characteristics—English language facility, for instance—and the characteristics of the locations in which they were resettled. They developed a matching algorithm that improves refugee employment outcomes in the United States by roughly 40 percent. “If refugee resettlement agencies...could take those synergies into account when they allocate people to places,” Weinstein argues, “you could actually generate significant gains in the likelihood that individuals are employed at almost zero cost.”

Weinstein discusses the potential risks entailed in algorithmic decision-making, how matching programs can take refugee preferences into account, and what the United States might learn from the Canadian resettlement model. Canada’s private sponsorship program “takes advantage of the power and motivation and passion of citizens who...want to throw their arms open and welcome people,” he says. Such a model would be “very consistent with American history and the role of voluntary organizations and and communities.

“The frailty of the international protection regime for refugees is very much on display and it’s been on display since the large migration from Syria in this decade.”

How can we convince more countries to increase their resettlement numbers so we can get closer to that 300,000? For Weinstein, the challenges lie in addressing the financial constraints that limit resettlement, encouraging the U.S., Canada, and European countries to maintain their historical leadership of the resettlement system, and thinking about how to generate empathy for refugees within host nations. A key challenge for all of us, Weinstein says, “is to reclaim space for tolerance and understanding, and in the absence of that, the refugee resettlement problem is going to be difficult to solve.”

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Related Resources

Trump Has Undercut U.S. Refugee Resettlement. Here’s One Way to Restore It — Jeremy Weinstein and Jeremy Ferwerda, Foreign Policy

Improving Refugee Integration Through Data-Driven Algorithmic Assignment — Kirk Bansak, Jeremy Ferwerda, Jens Hainmueller, Andrea Dillon, Dominik Hangartner, Duncan Lawrence, and Jeremy Weinstein, Science

Resettlement at a Glance (2018) — United Nations High Commissioner for Refugees

(Un)welcome: The State of Refugee Resettlement in America —  International Rescue Committee

Refugee Admissions and Resettlement Policy —  Congressional Research Service

The World’s System for Resettling Refugees Benefits the United States —  Denis McDonough and Ryan Crocker, Foreign Policy

Understanding the Algorithm Meant to Help Refugees Get Jobs Fast —  Natalie Sikorski, News Deeply

Opinions and views expressed by guests are their own and do not reflect those of the International Rescue Committee.