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

Clément Brébion, Janine Leschke, Pavle Boskoski, Biljana Mileva Boshkoska

Research output: Contribution to conferencePaperResearchpeer-review


This paper 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.
Original languageEnglish
Publication date2022
Number of pages36
Publication statusPublished - 2022
Event20th Annual European Network for Social Policy Analysis Conference. ESPAnet 2022: Social Policy Change between Path Dependency and Innovation - Wien, University of Vienna, Austria
Duration: 14 Sept 202216 Sept 2022
Conference number: 20


Conference20th Annual European Network for Social Policy Analysis Conference. ESPAnet 2022
CityUniversity of Vienna
Internet address


  • Algorithms
  • Job quality
  • Matching
  • Profiling
  • Public employment services

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