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  1. Statistical profiling of unemployed jobseekers
    the increasing availability of big data allows for the profiling of unemployed jobseekers via statistical models
    Autor*in: Van Landeghem, Bert G. M.; Desiere, Sam; Struyven, Ludo
    Erschienen: February 2021
    Verlag:  Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), Bonn

    Statistical models can help public employment services to identify factors associated with long-term unemployment and to identify at-risk groups. Such profiling models will likely become more prominent as increasing availability of big data combined... mehr

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    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DSP 128
    Fernleihe:
    keine Fernleihe

     

    Statistical models can help public employment services to identify factors associated with long-term unemployment and to identify at-risk groups. Such profiling models will likely become more prominent as increasing availability of big data combined with new machine learning techniques improve their predictive power. However, to achieve the best results, a continuous dialogue between data analysts, policymakers, and case workers is key. Indeed, when developing and implementing such tools, normative decisions are required. Profiling practices can misclassify many individuals, and they can reinforce but also prevent existing patterns of discrimination.

     
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/260717
    Schriftenreihe: IZA world of labor ; 2021, 483
    Schlagworte: statistical profiling; long-term unemployment; benefit exhaustion; labor market discrimination
    Umfang: 1 Online-Ressource (circa 9 Seiten), Illustrationen