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Scientific Article details

Title Make our communities better through data: The moral economy of smart city labor
ID_Doc 37902
Authors Burns, R; Welker, P
Title Make our communities better through data: The moral economy of smart city labor
Year 2022
Published Big Data & Society, 9, 1
DOI 10.1177/20539517221106381
Abstract Smart cities are now an established context in which data and digital technologies shape urban politics. Despite increased scholarly focus on algorithmic governance, smart cities and their data production still heavily rely on human labor, raising questions about how that labor is recruited and the implications of different recruitment strategies. In this paper, we illuminate the relations and practices mobilized to recruit the labor required to produce, analyze, and enact data that (re)produce smart cities. We argue that smart cities recruit such digital labor by producing and circulating moral values and sentiments to claim that such participation is a social good. In this article we draw on a 6-year ongoing project in Calgary, Canada to explore how these "moral economies" underwrite smart city ecosystems. We explore three projects related to data and digital labor in the Calgary smart city: a wearable technology collaborative project, a civic hacking group, and the community social media platform Nextdoor. We suggest that moral economies of smart cities signal a new juncture between urban planning and profiting from data, with the potential for creating new socio-political risks. These moral economies signal a shift toward a "new spirit of capitalism" in which labor is managed through indirect persuasion rather than direct compulsion and mandate.
Author Keywords Smart cities; open data; hackathons; moral economy; political economy; digital labor
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Social Science Citation Index (SSCI)
EID WOS:000811737900001
WoS Category Social Sciences, Interdisciplinary
Research Area Social Sciences - Other Topics
PDF https://journals.sagepub.com/doi/pdf/10.1177/20539517221106381
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