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      Gigified Knowledge Work: Understanding Knowledge Gaps When Knowledge Work and On-Demand Work Intersect

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          Abstract

          Online freelance platforms can transform knowledge work. However, 'gigification' also presents challenges, including how freelance workers can access and work with knowledge, which prior research has not examined. Through a qualitative interview study, we identify disparities in how freelancers who work for enterprise companies are able to utilize knowledge as part of their work, when compared with traditional employees of similar organizations. We examine how 38 knowledge workers (21 freelancers, 17 employees) deploy knowledge, work skillfully and mobilize resources to meet knowledge needs. We find that both employees and freelancers understand their own ability to act knowledgeably as a dynamic, collaborative, negotiated and emergent accomplishment. However, for freelancers, the dynamic dimensions of knowledge work - such as helping others see the meaning and value of their work, and creating ties between their work and the enterprise - are only minimally-legitimized and minimally-supported by organizing structures and tools. We present our results as 'knowledge gaps', and propose design recommendations to reduce these gaps and consequently make on-demand knowledge work more effective and sustainable.

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          Reflecting on reflexive thematic analysis

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            Is Open Access

            Good Gig, Bad Gig: Autonomy and Algorithmic Control in the Global Gig Economy

            This article evaluates the job quality of work in the remote gig economy. Such work consists of the remote provision of a wide variety of digital services mediated by online labour platforms. Focusing on workers in Southeast Asia and Sub-Saharan Africa, the article draws on semi-structured interviews in six countries (N = 107) and a cross-regional survey (N = 679) to detail the manner in which remote gig work is shaped by platform-based algorithmic control. Despite varying country contexts and types of work, we show that algorithmic control is central to the operation of online labour platforms. Algorithmic management techniques tend to offer workers high levels of flexibility, autonomy, task variety and complexity. However, these mechanisms of control can also result in low pay, social isolation, working unsocial and irregular hours, overwork, sleep deprivation and exhaustion.
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              Social Capital, Intellectual Capital, and the Organizational Advantage

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                Author and article information

                Journal
                Proceedings of the ACM on Human-Computer Interaction
                Proc. ACM Hum.-Comput. Interact.
                Association for Computing Machinery (ACM)
                2573-0142
                March 30 2022
                April 07 2022
                March 30 2022
                : 6
                : CSCW1
                : 1-27
                Affiliations
                [1 ]Microsoft, London, United Kingdom
                [2 ]Aarhus University, Aarhus, Denmark
                [3 ]Microsoft Research, Cambridge, United Kingdom
                [4 ]University College London, London, United Kingdom
                Article
                10.1145/3512940
                37360538
                19104d42-a5c4-4e4c-be14-63dcffd34625
                © 2022
                History

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