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Beyond the Walls: Patterns of Child Labour, Forced Labour, and Exploitation in a New Domestic Workers Dataset

Author

Listed:
  • Zoe Trodd

    (Rights Lab and School of Politics and International Relations, University of Nottingham, Nottingham NG7 2RD, UK)

  • Catherine Waite

    (Department of Zoology, University of Cambridge, Cambridge CB2 1TN, UK)

  • James Goulding

    (Rights Lab and Business School, University of Nottingham, Nottingham NG7 2RD, UK)

  • Doreen S. Boyd

    (Rights Lab and School of Geography, University of Nottingham, Nottingham NG7 2RD, UK)

Abstract

The new Domestic Workers Dataset is the largest single set of surveys ( n = 11,759) of domestic workers to date. Our analysis of this dataset reveals features about the lives and work of this “hard-to-find” population in India—a country estimated to have the largest number of people living in forms of contemporary slavery (11 million). The data allow us to identify child labour, indicators of forced labour, and patterns of exploitation—including labour paid below the minimum wage—using bivariate analysis, factor analysis, and spatial analysis. The dataset also helps to advance our understanding of how to measure labour exploitation and modern slavery by showing the value of “found data” and participatory and citizen science approaches.

Suggested Citation

  • Zoe Trodd & Catherine Waite & James Goulding & Doreen S. Boyd, 2024. "Beyond the Walls: Patterns of Child Labour, Forced Labour, and Exploitation in a New Domestic Workers Dataset," Societies, MDPI, vol. 14(5), pages 1-28, May.
    • Handle: RePEc:gam:jsoctx:v:14:y:2024:i:5:p:62-:d:1388324
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    References listed on IDEAS

    as
    1. Sheldon X. Zhang & Michael W. Spiller & Brian Karl Finch & Yang Qin, 2014. "Estimating Labor Trafficking among Unauthorized Migrant Workers in San Diego," The ANNALS of the American Academy of Political and Social Science, , vol. 653(1), pages 65-86, May.
    2. Chloe Brown & Anna Daniels & Doreen S. Boyd & Andrew Sowter & Giles Foody & Siddharth Kara, 2020. "Investigating the Potential of Radar Interferometry for Monitoring Rural Artisanal Cobalt Mines in the Democratic Republic of the Congo," Sustainability, MDPI, vol. 12(23), pages 1-20, November.
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