Long abstract:

The “datafication” of migration management can also benefit refugees. Re:Match provides an example applying rights, tech, and research to the issue of refugee relocation. We matched and relocated 78 displaced Ukrainians from Poland to six German municipalities from April to September 2023. Relocation was determined by refugees accepting assignments from Pairity’s matching algorithm, which accounts for refugees’ needs and preferences in relation to city services, characteristics, and reception capacity.

Algorithmic matching serves several important functions: it centres refugee preferences, capacities, and needs; limits bias; rapidly assesses large datasets; and suggests best possible matches for whole populations given scarce reception resources. Match data also provides baseline metrics to understand relationships between match quality, programme satisfaction, and refugee integration.

Outcomes show high refugee and city satisfaction, including increased preparedness for, and fit with, local circumstances. The participatory approach begins with informed consent; combines granular city data and refugees’ preferences to increase agency; improves relocation quality; and provides better integration potential. Relocation through matching algorithms can mobilize large datasets for faster, better matches, consider refugees’ needs and preferences, and give cities foresight and input rather than reacting to arrivals.

Our presentation highlights core pilot findings, arguing that Re:Match is scalable across the EU by providing evidence and venues for solidarity and responsibility-sharing as envisaged in the EU’s Voluntary Solidarity Mechanism. Re:Match Phase 2 (February - December 2024) will expand on pilot outcomes to relocate refugees from frontline states to regions and municipalities interested in tailored relocation mechanisms.