About

Despite decades of regional harmonisation and international jurisprudence, the chance of receiving asylum for people from the same country or groups still varies significantly across Nordic and European countries. For example, in 2018 Somali applicants thus had an 8% chance of receiving asylum at the first instance in Denmark, against 34% in Norway and 48% in Sweden. Vice versa, 99,5% of Eritreans were granted asylum in Denmark, compared to 89% in Norway and 83% in Sweden. These variations are not unique to the Nordic countries and have led to repeated accusations describing legal decision-making as “refugee roulette,” and the EU Dublin system establishing where asylum applications should be processed as an “asylum lottery.” States have similar expressed concern that differing recognition rates may lead to secondary movement and “asylum shopping” between different Nordic or EU countries.

The Nordic Asylum Law & Data Lab draws on unique access to large datasets of Nordic asylum case law from Denmark, Sweden and Norway, and an interdisciplinary team spanning law, computer science and medicine. We aim to produce novel approaches to answering two fundamental questions in refugee research: What factors shape the production of national asylum decisions? and Why do asylum outcomes across similar cases differ so much from one another? Asylum decision-making (also called refugee status determination) is a complex process revolving around not only law, but also inter-subjective assessments of applicants’ credibility and the import of medical and other forms of evidence. Consequently, the asylum process often appears as “black boxed” to both applicants and scholars and little is known about how different aspects interact and shape outcomes.

By creating a better understanding of the factors shaping asylum outcomes the Nordic Asylum Law & Data Lab aims to contribute to basic science as well as to inform ongoing policy processes and public discourse. Migration law is moreover a field set to be fundamentally reshaped by computational technologies. We aim to ensure that research informs these ongoing processes while simultaneously raising important critical questions about how new technologies are implemented and the inherent risks of (re-)producing bias or discrimination.