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100			_aCameron, Lindsey D. _959539
245			_aThe making of the “good bad” job: How algorithmic management manufactures consent through constant and confined choices
260			_aAdministrative Science Quarterly
300			_a69(2), Jun, 2024: p.458-514
520			_aThis research explores how a new relation of production—the shift from human managers to algorithmic managers on digital platforms—manufactures workplace consent. While most research has argued that the task standardization and surveillance that accompany algorithmic management will give rise to the quintessential “bad job” (Kalleberg, Reskin, and Hudson, 2000; Kalleberg, 2011), I find that, surprisingly, many workers report liking and finding choice while working under algorithmic management. Drawing on a seven-year qualitative study of the largest sector in the gig economy, the ride-hailing industry, I describe how workers navigate being managed by an algorithm. I begin by showing how algorithms segment the work at multiple sites of human–algorithm interactions and how this configuration of the work process allows for more-frequent and narrow choice. I find that workers use two sets of tactics. In engagement tactics, individuals generally follow the algorithmic nudges and do not try to get around the system; in deviance tactics, individuals manipulate their input into the algorithmic management system. While the behaviors associated with these tactics are practical opposites, they both elicit consent, or active, enthusiastic participation by workers to align their efforts with managerial interests, and both contribute to workers seeing themselves as skillful agents. However, this choice-based consent can mask the more-structurally problematic elements of the work, contributing to the growing popularity of what I call the “good bad” job.- Reproduced https://journals.sagepub.com/doi/full/10.1177/00018392241236163
650			_aAlgorithmic management, Workplace consent, Labor process theory, Gig work, Gig/on-demand economy, Digital platforms, Front-line service workers, Uber, Lyft. _948935
773			_aAdministrative Science Quarterly
906			_aLABOUR
942			_cAR