News Finding: The algorithm takes into account a variety of factors that resettlement agencies usually don't, from age to English proficiency to the size of the immigrant community from a refugee's country in any given location.
Paper Finding: In Switzerland, for example, we find that the ability to speak French (i.e., among French-speaking African refugees) results in a larger payoff for refugees assigned to Frenchspeaking cantons than for those assigned to German-speaking cantons ( fig.
News Context: But what kind of life that will be largely depends on where they end up. The algorithm takes into account a variety of factors that resettlement agencies usually don't, from age to English proficiency to the size of the immigrant community from a refugee's country in any given location. But by weighing in specific details about the refugees and the communities where they are headed, the algorithm can place them where their skills are the most marketable.
Paper Context: This indicates that there are synergies between places and people; certain characteristics will make a refugee a better match for a particular location. In Switzerland, for example, we find that the ability to speak French (i.e., among French-speaking African refugees) results in a larger payoff for refugees assigned to Frenchspeaking cantons than for those assigned to German-speaking cantons ( fig. A separate model was fit for subgroups of refugees assigned to each location, thus yielding different models for each location and allowing for the discovery of refugee/location synergies.