Selecting the Suitable Job Quality Items in Profiling and Job Matching Algorithms for Public Employment Services

Publikation: Working paperForskningpeer review

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This report takes its starting point in the lessons learned from first generation statistical profiling systems in Public Employment Services (PES) and the sociological vision of labour market integration and good-quality work. Commonly job quality is not considered in statistical profiling, instead exit to any type of employment is modelled. We discuss and operationalize the multi-dimensional concept of job quality with a view on whether and how job quality items can be integrated into a tool computing the probability of exit into good jobs. Importantly, we also consider whether such items can be used in more advanced visualization platforms providing the unemployed and job seekers a snapshot of their labour market options. The aim of the report is thus to translate the findings from work package 1 on the sociological-led user vision into job quality dimensions and items (variables) that can be measured either with register data or with European survey data and which can then be integrated in the development of our HECAT platform in work package 3.
Antal sider36
StatusUdgivet - 2020
NavnDeliverables from HECAT - Disruptive Technologies Supporting Labour Market Decision Making


  • Algorithms
  • EU survery data
  • Job quality
  • Matching
  • Profiling
  • Public employment services