Statistical profiling of unemployed jobseekers The increasing availability of big data allows for the profiling of unemployed jobseekers via statistical models

Statistical models are better in predicting an outcome (such as long-term unemployment) than a lottery. Such models can hence help Public Employment Services to identify factors associated with long-term unemployment and to identify groups at risk. However, a policy maker cannot just define an outcome variable at the start of the project and walk away: a continuous dialogue between data analysts, policy makers and caseworkers is very important. Indeed, throughout the process, normative decisions are to be made: profiling practices misclassify many individuals, and they can reinforce existing patterns of discrimination.

Publication year:2021

Accessibility:Open