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Care Workers' Wellbeing in Data-Driven Healthcare Workplace: Identity, Agency, and Social Justice

Yuling Sun, Xiaojuan Ma, Silvia Lindtner, Liang He

2023Year
15Citations
8Top-tier citations

Abstract

This paper zooms in on a particularly precarious and largely invisibilized group of care workers: middle-aged and less-educated female migrant workers from rural China. Drawing from a mixed-methods study, we specifically examine how the extensive use of data-driven technologies impacts care workers' wellbeing in the workplace. Our findings suggest the extensive use of data-driven healthcare technologies are eroding care workers' workplace wellbeing, especially their sense of identity, agency, and perceived justice. Specifically, in the data-driven workplace, care workers are treated as a servant to data, instead of a human with agency and knowledge. They are no merely care workers who provide various care services for care receivers, but also data workers, whose practices and agency are greatly limited by data. This aggravates preexisting hardship of care workers, and reproduces new social injustice. We suggest CSCW researchers and practitioners take into account how pre-existing social structures shaped the designs of socio-technological systems, and reconceptualize the paradigm of "data-drivenness" for more just and ethical data-driven healthcare technologies.

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