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    Encoding Race, Encoding Class

    Indian IT Workers in Berlin

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    Author(s)
    Amrute, Sareeta
    Collection
    Knowledge Unlatched (KU)
    Language
    English
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    Abstract
    In Encoding Race, Encoding Class Sareeta Amrute explores the work and private lives of highly skilled Indian IT coders in Berlin to reveal the oft-obscured realities of the embodied, raced, and classed nature of cognitive labor. In addition to conducting fieldwork and interviews in IT offices as well as analyzing political cartoons, advertisements, and reports on white-collar work, Amrute spent time with a core of twenty programmers before, during, and after their shifts. She shows how they occupy a contradictory position, as they are racialized in Germany as temporary and migrant grunt workers, yet their middle-class aspirations reflect efforts to build a new, global, and economically dominant India. The ways they accept and resist the premises and conditions of their work offer new potentials for alternative visions of living and working in neoliberal economies. Demonstrating how these coders' cognitive labor realigns and reimagines race and class, Amrute conceptualizes personhood and migration within global capitalism in new ways.
    URI
    https://library.oapen.org/handle/20.500.12657/59765
    Keywords
    Social Science; Emigration & Immigration; Social Science; Sociology; Social Science; Anthropology; Cultural & Social
    ISBN
    9780822361176, 9780822361350, 9781478091875, 9780822374275
    Publisher
    Duke University Press
    Publisher website
    https://www.dukeupress.edu/
    Publication date and place
    2016
    Grantor
    • Knowledge Unlatched
    Imprint
    Duke University Press
    Classification
    Migration, immigration and emigration
    Relating to migrant groups / diaspora communities or peoples
    Sociology
    Social and cultural anthropology
    Rights
    https://creativecommons.org/licenses/by-nc-nd/4.0/
    • Harvested from KU

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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