News Finding: Location Actual With algorithm 1 0% 75% 2 0% 4% 3 0% 10% 4 0% 15% 5 0% 36% 6 6% 62% 7 6% 59% 8 9% 39% 9 9% 54% 10 17% 20% 11 21% 52% 12 21% 47% 13 24% 43% 14 25% 47% 15 26% 31% 16 26% 41% 17 28% 12% 18 29% 41% 19 29% 42% 20 31% 70% 21 31% 65% 22 32% 46% 23 38% 35% 24 40% 76% 25 40% 42% 26 48% 71% 27 48% 58% 28 48% 69% 29 50% 48% 30 50% 40% 31 50% 86% 32 52% 44% 33 56% 58% 34 62% 69% 35 93% 62%
  
  In Switzerland, the algorithm would have increased refugees' employment chances to 26% from 15%.
Paper Finding: Various mapping functions can be used.
News Context: In the US, chances of finding work rose to 50% with the algorithm, for the median refugee. Location Actual With algorithm 1 0% 75% 2 0% 4% 3 0% 10% 4 0% 15% 5 0% 36% 6 6% 62% 7 6% 59% 8 9% 39% 9 9% 54% 10 17% 20% 11 21% 52% 12 21% 47% 13 24% 43% 14 25% 47% 15 26% 31% 16 26% 41% 17 28% 12% 18 29% 41% 19 29% 42% 20 31% 70% 21 31% 65% 22 32% 46% 23 38% 35% 24 40% 76% 25 40% 42% 26 48% 71% 27 48% 58% 28 48% 69% 29 50% 48% 30 50% 40% 31 50% 86% 32 52% 44% 33 56% 58% 34 62% 69% 35 93% 62%
  
  In Switzerland, the algorithm would have increased refugees' employment chances to 26% from 15%. Canton Actual With algorithm OW 0% 40% TI 4% 32% FR 4% 15% LU 7% 18% VS 7% 14% VD 8% 8% BL 11% 12% AG 11% 21% GE 13% 23% ZH 15% 7% BE 16% 35% JU 17% 21% SG 17% 28% SH 20% 51% UR 20% 48% ZG 20% 61% GL 22% 42% BS 25% 25% NE 25% 11% SO 25% 64% GR 29% 64% NW 29% 45% SZ 29% 18% TG 30% 33% AR 33% 46%
  
  Here's roughly how the algorithm works: The process starts with a series of models trained to predict where a certain type of refugee is likely to fare best based on previous cases.
Paper Context: 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. Various mapping functions can be used. Our preferred case-level metric was the predicted probability that at least one refugee in the case would find employment at the location in question.