Mapping Wage Theft with Data Science

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    Author
    Kariotis, T; Howe, J
    Date
    2021
    Source Title
    Pursuit
    University of Melbourne Author/s
    Howe, John; Kariotis, Timothy
    Affiliation
    Melbourne School of Government
    Metadata
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    Document Type
    Scholarly Contribution
    Citations
    Kariotis, T. & Howe, J. (2021). Mapping Wage Theft with Data Science
    Access Status
    Access this item via the Open Access location
    URI
    http://hdl.handle.net/11343/260513
    Open Access URL
    https://pursuit.unimelb.edu.au/articles/mapping-wage-theft-with-data-science?utm_campaign=pursuit&utm_content=Mapping+wage+theft+with+data+science_Headline&utm_medium=email&utm_source=pursuit_weekly_digest
    Abstract
    Wage theft is almost 'normal' in some industries, but hard to detect. Predictive algorithms can help regulators and give workers an edge.

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