Protecting Low-Wage Workers From Exploitation: A Mapping Study of Wage Theft Laws in the 40 Largest US Cities.

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Title: Protecting Low-Wage Workers From Exploitation: A Mapping Study of Wage Theft Laws in the 40 Largest US Cities.
Authors: Lee, Jennifer J., O'Connor, Maggie, Shen, Jiahui
Source: American Journal of Public Health. Apr2026, Vol. 116 Issue 4, p492-501. 10p.
Subjects: Wage laws, Government policy, Theft, Social determinants of health, Descriptive statistics, Longitudinal method, Labor laws, Medical coding, Public health, Industrial hygiene
Geographic Terms: United States
Abstract: Objectives. We measured key features of local and state wage theft laws in the 40 largest US cities to assess the added value of local legislation and to create scientific legal data for use in evaluating the health impact of wage theft laws. Methods. We adapted standard policy surveillance methods to collect and code local and state minimum wage and nonpayment of wages theft laws from January 1, 2010, to April 15, 2023. Results. Compared with state laws, local wage theft legislation was proportionally more likely to contain features that facilitated worker complaints and to provide flexible enforcement tools. Only 4 of the 40 largest cities were totally preempted from enacting local wage theft legislation. Conclusions. Local wage theft laws provide an opportunity for innovative mechanisms to support complaint filing and enforcement. More cities could enact wage theft laws without preemption concerns. Public Health Implications. Ensuring that low-wage workers are fairly paid is important to health and health equity. Our research provides scientific legal data for use in evaluating the health effects of these widely applied protections. [ABSTRACT FROM AUTHOR]
Copyright of American Journal of Public Health is the property of American Public Health Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Protecting Low-Wage Workers From Exploitation: A Mapping Study of Wage Theft Laws in the 40 Largest US Cities.
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  Data: <searchLink fieldCode="JN" term="%22American+Journal+of+Public+Health%22">American Journal of Public Health</searchLink>. Apr2026, Vol. 116 Issue 4, p492-501. 10p.
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  Data: <searchLink fieldCode="DE" term="%22Wage+laws%22">Wage laws</searchLink><br /><searchLink fieldCode="DE" term="%22Government+policy%22">Government policy</searchLink><br /><searchLink fieldCode="DE" term="%22Theft%22">Theft</searchLink><br /><searchLink fieldCode="DE" term="%22Social+determinants+of+health%22">Social determinants of health</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Longitudinal+method%22">Longitudinal method</searchLink><br /><searchLink fieldCode="DE" term="%22Labor+laws%22">Labor laws</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+coding%22">Medical coding</searchLink><br /><searchLink fieldCode="DE" term="%22Public+health%22">Public health</searchLink><br /><searchLink fieldCode="DE" term="%22Industrial+hygiene%22">Industrial hygiene</searchLink>
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  Data: Objectives. We measured key features of local and state wage theft laws in the 40 largest US cities to assess the added value of local legislation and to create scientific legal data for use in evaluating the health impact of wage theft laws. Methods. We adapted standard policy surveillance methods to collect and code local and state minimum wage and nonpayment of wages theft laws from January 1, 2010, to April 15, 2023. Results. Compared with state laws, local wage theft legislation was proportionally more likely to contain features that facilitated worker complaints and to provide flexible enforcement tools. Only 4 of the 40 largest cities were totally preempted from enacting local wage theft legislation. Conclusions. Local wage theft laws provide an opportunity for innovative mechanisms to support complaint filing and enforcement. More cities could enact wage theft laws without preemption concerns. Public Health Implications. Ensuring that low-wage workers are fairly paid is important to health and health equity. Our research provides scientific legal data for use in evaluating the health effects of these widely applied protections. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of American Journal of Public Health is the property of American Public Health Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.2105/AJPH.2025.308351
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      – Code: eng
        Text: English
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        Type: general
      – SubjectFull: Government policy
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      – SubjectFull: Theft
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      – SubjectFull: Social determinants of health
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      – SubjectFull: Descriptive statistics
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      – SubjectFull: Longitudinal method
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      – SubjectFull: Labor laws
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      – SubjectFull: Medical coding
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      – SubjectFull: Public health
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      – SubjectFull: Industrial hygiene
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      – SubjectFull: United States
        Type: general
    Titles:
      – TitleFull: Protecting Low-Wage Workers From Exploitation: A Mapping Study of Wage Theft Laws in the 40 Largest US Cities.
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            NameFull: Lee, Jennifer J.
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              M: 04
              Text: Apr2026
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              Y: 2026
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