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Who cares? Platform Work and Low-income home service work in the digital economy

Who cares? Platform Work and Low-income home service work in the digital economy


Wifak Gueddana, Teaching Fellow Digital Economy and Society, King’s College London Kendra Briken, Chancellor Fellow, University of Strathclyde Miranda Hall, Researcher, the New Economic Foundation

Division to which this work belongs:

Sociology & humanities


Who cares? Platform Work and Low-income home service work in the digital economy


Digital Labour (Scholz, 2012) blurs the lines between, work and leisure, waged and unwaged work. It is a form and an outcome of the microdivision of labour and the establishing of transnational markets for selling parcels of users’ attention varying from labour-intensive creative inputs to low-effort work that amounts to anything than a distraction, i.e. puzzles, hits, clicks or microtasks, which flow all through the growing number of crowdsourcing, content farm and e-lancing websites (Ross 2013). This latest form of management Taylorism is deskilling, dispersing and depriving workers of any knowledge about the nature of the process to which their labour contributes to, to the point that workers often may not perceive their interactive input as work (Ibid). In this paper, we argue that platform work, often described in the context of food delivery (Deliveroo), transports (Uber), home and domestic care (; TaskRabbit) could be seen as an extension of digital labour; this similarly to the latter, relies on the impossibility of distinguishing between working- and life-time and on a deeper individualisation of industrial relations that make workers the sole bearers of the risk inherent to bad working conditions (Gregory 2019), lack of employment protection (De Valeiro 2019) and low wages (i.e. workers often spend more than 20% of the time searching, training and reviewing clients in addition to performing jobs). Furthermore, our focus here is on multi-sided online markets and gig workers in the home care and domestic services who are drastically underrepresented in the scholarly discourse on gig work. This is centred around a few unicorns that are male dominated (e.g. Uber and Deliveroo); yet women represent the majority of the gig workers (Huws 2017) and the care and domestic services, where BAME women make up the majority of gig workers, are in particular one of the most vulnerable sectors prone to platform take-over. Based on that, we try to understand how care platforms came to reproduce the rigid gendered and unequal labour markets where the hidden work of migrant and BAME women in low-income home service sectors remains invisible, undervalued, underpaid and under-protected. To do that, we start by acknowledging that care work is the quintessential example of ‘invisible work’; yet workers do not choose to remain invisible; in this sense, invisibility is not a state of being, it is a politics of power that renders people more or less seen (Gray 2009). What home and domestic care platforms make invisible shapes the lives of workers, their work conditions and entitlements (Ticona et al. 2018). Platforms promote transparency, and professional standards by educating clients who employ elderly carers and nannies to act as legal employers and use the electronic payment system; yet they equate visibility with professionalism (Ibid). Paradoxically, website features encourage individuals to take on all sorts of work arrangements and records logs of transactions that are equal to paid time and not real working time. By doing so, care and domestic services platforms make workers and working conditions invisible, shaping the value of labour and the performance of workers in ways that normalise their precarity and infra-structure bad work, long working hours and low-wages. Furthermore, platform logs of transactions are increasingly used to measure the growth and scope of the gig economy. This is causing research to remain essentially platform-centric, while the working practices, and conditions of the real platform workers are under-characterized, and their protection lagging behind. In this pilot study we focus on alternative sources of evidence that are not collected by platforms (e.g. Uber transactions, Amazon users accounts, etc.). Particularly, we use a selection of forums such as SubReddit communities,, and the forum of to collect posts and participants profiles. We then use topic modelling to develop a topology of topics across communities and we use visualizations to map participants’ interactions inside and across forums. By using data science methods combined with an interpretative analysis, we seek to provide rich qualitative insights about emerging work practices, coping tactics, tools and support strategies that contribute to our understanding of platform work and ultimately digital labour.