Women in the gig economy: feminising ‘digital labour’

Author: Al James1
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  • 1 Newcastle University, UK
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This article explores the gendered dynamics of labouring on digital labour platforms and gives voice to women gig workers. Millions of women worldwide find work through digital labour platforms, yet remain largely invisible within the expansive digital labour research agenda. The analysis is built from original interviews with 49 women in the UK using a range of popular remote crowdwork platforms (including PeoplePerHour, Upwork, TaskRabbit, Freelancer) to access desk-based, white-collar gig work from home. The article makes three original contributions. First, it widens the analytical focus of the digital labour research agenda to recognise the role of workers’ gender identities and uneven household gender divisions of care in shaping the operation and outcomes of digital labour platforms, in ways that remain ‘hidden in the cloud’. Second, in contrast to widespread celebratory claims that platforms disrupt stubborn gender labour market inequalities, the analysis identifies significant gendered constraints on women’s algorithmic visibilities and abilities to compete for gig work online, alongside multiple health and safety issues among women gig workers undocumented in previous research. Third, in response to these new insights, and based on calls from women gig workers themselves, it sets out a series of new directions for extending this urgent multidisciplinary research agenda.

Abstract

This article explores the gendered dynamics of labouring on digital labour platforms and gives voice to women gig workers. Millions of women worldwide find work through digital labour platforms, yet remain largely invisible within the expansive digital labour research agenda. The analysis is built from original interviews with 49 women in the UK using a range of popular remote crowdwork platforms (including PeoplePerHour, Upwork, TaskRabbit, Freelancer) to access desk-based, white-collar gig work from home. The article makes three original contributions. First, it widens the analytical focus of the digital labour research agenda to recognise the role of workers’ gender identities and uneven household gender divisions of care in shaping the operation and outcomes of digital labour platforms, in ways that remain ‘hidden in the cloud’. Second, in contrast to widespread celebratory claims that platforms disrupt stubborn gender labour market inequalities, the analysis identifies significant gendered constraints on women’s algorithmic visibilities and abilities to compete for gig work online, alongside multiple health and safety issues among women gig workers undocumented in previous research. Third, in response to these new insights, and based on calls from women gig workers themselves, it sets out a series of new directions for extending this urgent multidisciplinary research agenda.

Introduction

Little is known about the gender dimensions of platform-facilitated labor. We should start filling in this void. (Barzilay and Ben-David, 2016: 397)

In the wake of the Great Recession, labour scholars have explored a series of dramatic, digital transformations of work and labour relations accompanying the extraordinary growth of the ‘platform economy’. Underpinning these transformations, internet technologies are used to unbundle production from formal employment, and algorithms to broker, manage and motivate work carried out beyond the spatial and temporal confines of ‘typical’ workplaces by ‘independent contractors’ (Huws et al, 2016). Recent OII estimates suggest that over 163 million people worldwide secure income from paid work through digital labour platforms (Kässi et al, 2021), a five-fold increase over the last decade (ILO, 2021). Platforms act as intermediaries, matching time-starved consumers with a large supply of job-starved workers (The Economist, 2014), whose labour is sold on a one-off, as-needed basis. Work executed through platforms is relabelled ‘tasks’, ‘gigs’, ‘HITs’, ‘services’, ‘rides’ (De Stefano, 2016) and ranges from: on-demand urban service delivery (food, personal transport, courier services); to remote crowdsourced microtasks (often menial and monotonous, requiring some sort of judgement beyond AI capability, such as image categorisation, tagging, content moderation, information finding); to remote crowdsourcing of more complex white-collar tasks, or ‘cloudworking’ (for example, web and software development, sales and marketing, HR, legal, social media management, graphic design, writing and translation, clerical and data entry, and accounting (ILO, 2016)). Gig workers are paid on a project, piece rate, or hourly basis and must supply and maintain their own capital equipment (Stanford, 2017). Platforms route out work tasks for execution, mediate invoicing and payment, set minimum terms of service, and rank worker performance through multiple performance metrics based on requester (client) feedback.

Alternative monikers include the gig economy, on-demand economy, and platform economy – these supplanting earlier enthusiastic terminology around the ‘sharing’ economy (Heeks, 2017; Schor, 2021). Whatever the label, multiple commentators have celebrated digital labour platforms for giving workers access to an international client base with minimal barriers to entry, the ability to generate income quickly, and to set their own work schedules more readily balanced with childcare, family, other work, study or leisure. In short, ‘crowdworkers’ can perform work ‘from anywhere and at any time’ (Rani and Furrer, 2020: 2) – or what Kessler (2018) (quoting Uber’s advertising campaign) summarises as ‘no shifts, no boss, no limits’ (p. 12) (see also Aloisi, 2015; Schwab, 2017; OECD, 2017).

Critical digital labour studies research has, however, critiqued these claims as ‘utopian’, documenting instead the precarity of online gig workers for whom platforms eschew any legal responsibility as ‘employers’. Platform workers are instead designated as self-employed ‘independent contractors’, despite their terms and conditions of work being defined by extensive platform user agreements skewed heavily in favour of requesters and platforms. This power asymmetry underpins pervasive instances of overwork, and wage theft for completed tasks deemed ‘unsatisfactory’ by clients (for example, Felstiner, 2011). And despite hefty platform fees (typically 15%–30% of workers’ wages (Prassl, 2018)), a lack of employee status means a lack of social protection, as platforms bypass legal regulations that would otherwise afford minimum wage protections, unemployment benefits, paid holiday leave, sick pay, parental leave and pensions (Scholz, 2017; Graham and Shaw, 2017). These problems are reinforced by intense competition between workers, with platforms deliberately recruiting an oversupply of labour to reduce worker bargaining power (Cockayne, 2016). This also pushes down compensation for work that is often intermittent with frequent periods of unpaid job search (De Stefano, 2016). Constrained ‘flexibility’ also results from algorithmic ‘behavioural nudges’ encouraging workers to maintain a high acceptance rating of gigs offered, and thereby avoid being suddenly deactivated (Churchill and Craig, 2019) – or ‘fired from a job you never had, by an employer who never employed you’.1

Experiences of gig worker precarity, hardship and struggle are widely documented. However, within this otherwise progressive research agenda women gig workers remain empirically and analytically marginalised, and the gendered dimensions of gig work heavily under-researched (Barzilay and Ben-David, 2016; Churchill and Craig, 2019; Hunt and Samman, 2019; Kasliwal, 2020; Milkman et al, 2021). The majority of our understanding of platform work-lives and digital precarity has come from analyses of men doing gig work, or else studies that lump workers into one apparently genderless mass of ‘digital labour’. This ‘virtual absence of women’ (Gregg and Andrijasevic, 2019) is especially problematic given the celebration of digital labour platforms as disrupting stubborn gendered labour market inequalities and work–family conflicts (for example, Slaughter, 2015; 2016; Manyika et al, 2016; Hyperwallet, 2017; Krieger-Boden and Sorgner, 2018). Exemplifying such claims is the suggestion that:

For professional women, the on-demand economy is already a godsend… women can continue to advance in their careers or at least stay in the game while being the kind of parents they want to be. (Slaughter, 2015: 2)

Such enthusiasm is echoed by platforms themselves, through advertising slogans, imagery and worker testimonies that encourage women to sign up to ‘live your work dream’ (PPH) as part of a ‘new generation of women… building careers that lead to both financial and personal freedom’ (Upwork).

This article disrupts these claims, through an analysis of the gendered dynamics of digital platform work and the gendered barriers facing women gig workers. New evidence is presented from ethnographic interviews with 49 women in the UK using popular digital labour platforms (PeoplePerHour, Upwork, TaskRabbit, Copify, Freelancer) to access remote crowdwork (commonly in tasks of communications, marketing, business development, HR, office support, web, design, graphics) carried out beyond the public gaze, in the domestic and private spaces of workers’ homes. The majority of these women are parents of pre-school children. The article advances a critical review of masculinist theories of ‘digital labour’ and their limits. Building on an emergent feminist digital labour agenda (see also Richardson, 2018), the analysis examines: women’s motivations for engaging in a diversity of platform work opportunities; and the work–life advantages that women identify from online gig work and management by algorithm. The analysis reveals mutliple contradictions as these women seek to negotiate better work-lives via digital work platforms relative to their former (and sometimes simultaneous) employers. It identifies the powerful role of gender identities and gendered relations of care in constraining women’s abilities to compete for platform work, including gendered constraints on algorithmic visibility across multiple platforms. It also exposes multiple health and safety abuses experienced by female gig workers in ways undocumented in the digital labour research literature.

By exposing the everyday realities of women’s gig work-lives, the analysis demonstrates that digital precarity and algorithmic visibility are gendered in ways which to date have remained ‘hidden in the cloud’ (Gregory, 2018) – and which demand that researchers take seriously the role of workers’ gender identities and uneven household gender divisions of care in shaping the operation and outcomes of digital labour platforms. The article sets out multiple directions to extend this urgent multidisciplinary research agenda.

Humanising ‘digital labour’ theory

The most magic innovation of the app economy is making the female workers it depends on mostly invisible. (Wen, 2014: 1)

The digital labour research agenda is expansive, spanning industrial relations, law, geography, sociology and economics. A major strand of work examines the quality of platform service provision and customer experience, as enabled by a 24/7, global pool of digital labour ‘instantly available’ to customers through smartphone, tablet, or laptop. Workers are narrowly conceptualised as inputs to production, a source of economic value for platform providers and shareholders, ‘humans as a service’ (Prassl, 2018). Efficiency gains for platform clients take analytical precedence over gig worker experience and its participatory benefits (Schwartz, 2018) – a focus on the crowdsourcers rather than the crowdsourced. Commodified units of ‘digitally distributed labour’ (Fish and Srinivasan, 2012) are reduced to their aggregate work histories, task performance, skillsets and reputational scores, through an analytical focus on ‘management labour extraction strategies’ for profit maximisation (Stanford, 2017), and optimisation of worker analytics, workflow design, and quality control so that ‘requesters may better recruit, assess, and/or manage workers’ (Vakharia and Lease, 2015: 4).

In so doing, the personal labour-power of ‘digital labour’ becomes devalued as an ‘infinitely available commodity for on-demand purchase’, that must respond immediately to the whims of consumers (Cockayne, 2016: 75–76). They ‘can be called by clients and customers at a click of their mouse or at a tap on their mobile, perform their task and then disappear again in the crowd’ (De Stefano, 2016: 5). Worker identities are effectively hidden by platform technologies: requesters often ‘don’t realise there is a living, breathing human on the other end of the connection’ (Scholz, 2017: 4; see also Altenried, 2022).2 The limits of this platform-centric approach are summed up neatly by Woodcock and Graham who argue that:

We cannot hope to fully understand the gig economy without also considering the experiences of the workers who support it. Trying to make sense of it without focusing on workers is like studying astronomy without ever looking up at the stars. (2019: 70)

An alternative body of work explores workers’ varied lived experiences of being used as ‘digital labour’. These workerist theories of platform production humanise ‘digital labour’ beyond common abstractions of workers’ skillsets, hourly rate, experience, ranking and/or platform avatar. Instead, this research is concerned to see the making of the platform economy through the eyes of workers (following Herod, 1997); to challenge platform-centric conceptions of the gig economy ‘as something that is done to workers’ (Woodcock and Graham, 2019: 112); and to show that ‘digital labour is everything but ‘immaterial’… it is about human activities that have economic value’ (Scholz, 2017: 6). These studies have advanced rich ethnographic analyses of: workers’ lived experiences of algorithmic management across different platforms (for example, Prassl, 2018; Wood et al, 2019); racial discrimination of platform workers (Ravenelle, 2019; Curran, 2021) including gig workers in the global south serving western requesters (Graham et al, 2017); and gig worker collective organising (for example, Tassinari and Maccarrone, 2020).

In seeking to humanise and make visible the platform workers whose labours collectively enable platform accumulation, however, this project remains partial. A major omission concerns a relative analytical silence around women’s experiences of online gig work and the role of gendered worker identities and gender relations in shaping: (i) the triangular relationships between requester, worker and platform; (ii) who gets access to better paid gigs, and platform capital accumulation; and (iii) crowdworker experiences of precarity (see also Ticona and Mateescu, 2018). We know relatively little about the active, everyday role of women in sustaining the platform economy in practice.

Female analytical exclusions within digital labour research are evident across multiple studies. These include the male-centric focus of recent high-profile studies which have advanced our understanding of gig work-lives, but in which women gig workers are largely absent, including: Moore and Newsome’s (2018) study of UK parcel delivery couriers (only one female home courier); Cant’s (2020) ethnography of Deliveroo riders in Brighton (women riders outnumbered 15:1); and Christie and Ward’s (2019) study of gig worker health. And while other studies identify the proportions of men and women in their survey samples, no subsequent analysis is developed to explore how different gender identities matter in shaping gig work-lives, including: Teodoro et al’s (2014) study of gig workers on TaskRabbit and Gigwalk; and Sutherland et al’s (2020) study of work self-presentation, risk management and client relationships by Upwork freelancers. A similar lack of engagement with gendered social relations of labour is also evident across multiple major commentaries on the establishment and operation of the gig economy, including: Fuchs’ (2014) development of a Marxist theory of digital labour value; Sundararajan (2016) on ‘the rise of crowd-based capitalism’, De Stefano (2016) on the rise of on-demand and crowd-work in the gig economy, and Srnicek (2017) on platform capitalism.

Such gender-blind treatments of workers contrast with ever finer-detailed typologies of ‘digital work’, including: microwork versus macrowork (Margaryan, 2019); crowdwork versus on demand labour (De Stefano, 2016); low complexity clickwork versus more complex multi-step tasks; geographically tethered (physical) gig work in neighbourhoods versus (virtual) cloudwork fulfilled online (Teodoro et al, 2014; Woodcock and Graham, 2019); requester-initiated versus worker-initiated crowdwork (Howcroft and Bergvall-Kåreborn, 2019); and good gigs versus bad gigs (Wood et al, 2019) – to name but a few! This work is motivated by the recognition that ‘we cannot think of gig work as a single homogenous category’ (Prassl, 2018: 28). In contrast, gender differentiation of the singular category of ‘gig worker’ lags significantly behind.

The origins of these male-centred approaches might usefully be understood as a function of a strong empirical research focus towards on-demand platforms whose highly visible, public-facing workforces are male-dominated. These include platform workers in food delivery, parcel delivery, ride hailing and home maintenance. At the forefront of these associations, one of the largest and most studied platforms, Uber, has an 84 per cent male US driver workforce (Hall and Krueger, 2018) – even higher in the UK at 95 per cent male (Financial Times, 2017). ‘Uber’ has become a generic descriptor for platform models across multiple service functions: ‘Uber for food, Uber for cleaning, Uber for courier services, Uber for grocery shopping… Uber for everything’ (Kessler, 2018: 10; see also Woodcock, 2021: 7). These descriptors reinforce common conceptions of Uber as the gig economy norm. At a deeper level however, these analyses perpetuate long-standing ontological constructions of the economic as ‘male’ (Nelson, 1992; Ferber and Nelson, 2003), in which women’s economic activities continue to be devalued and excluded from what is necessary or essential (McDowell, 2000). In the critical tradition of feminist economy, it is therefore vital that we bring ‘universal’ digital labour theory ‘down to earth and give it a pair of pants!’ (Bordo, 1990: 137).

Platforming female (dis)advantage? learning from female-inclusive studies

An active engagement with women gig workers is timely given the increasing presence of women using digital labour platforms to access paid work. Despite the widely recognised difficulties of accessing accurate large-scale data on the gig workforce,3 multiple surveys have revealed women’s significant presence within the platform economy (Hunt and Samman, 2019). Based on their high-profile European survey, Huws et al (2016) note ‘little gender difference in the propensity to do crowd work’ (p. ii): 53 per cent women and 47 per cent men for weekly crowdworkers. This is consistent with an ILO Survey of 1,259 crowdworkers using Amazon M Turk in the US (Berg, 2016): 52 per cent male, 48 per cent female. Likewise, repeat survey waves undertaken by Ross et al (2010) which identify between 52 per cent and 68 per cent of Amazon M Turkers as female. Applying these figures to the total 163 million platform workers worldwide, suggests that there are over 64 million women online gig workers whose work-lives remain largely ‘hidden in the cloud’ (Gregory, 2018).

Moving beneath these aggregate figures, a select group of female-inclusive studies have analysed gendered patterns of customer feedback, task allocation, and job quality on digital labour platforms and begun to theorise their operation and outcomes in relation to women’s platform remuneration, advancement and algorithmic visibility. A major research focus is how far ‘gig work sourced online [offers] an opportunity to avoid gendered patterns prevalent in traditional workplace organisational structures’ (Churchill and Craig, 2019: 748; Mateescu and Ticona, 2020). Studies have demonstrated female platform disadvantage across different platform service segments. In on-demand transportation, women Uber drivers receive fewer rides through algorithmic allocation (for example, Cook et al, 2018). This disadvantage is theorised in relation to less favourable reviews from riders rooted in gendered stereotypes of worker performance and skill.4 Gender bias in worker evaluations is also identified in remote crowdwork, including TaskRabbit. Based on an analysis of 3,707 worker profiles (42 per cent female), Hannák et al (2017) find that women across 30 US cities consistently receive 10 per cent fewer reviews than men with equivalent platform work experience – again with negative impacts on women’s algorithmic rankings and platform work opportunities. Similar discrimination is evidenced through larger surveys, including Barzilay and Ben-David’s (2016) analysis of 4,600 online taskers’ requested rates and work hours on ‘a global online work platform’, which showed that women’s average hourly requested rates are 37 per cent lower than men’s (controlling for feedback score, experience, work hours and educational attainment) with a need for legal innovations to better protect women gig workers.

As an outcome of online gender discrimination, platform gender pay gaps are evident. A prominent example in outsourced clickwork is Amazon M-Turk, where an ILO study5 has documented women earning on average 82 per cent of male Turkers’ average hourly earnings despite similar levels of educational qualification and weekly working hours (Adams-Prassl and Berg, 2017). Similarly, Dubey et al’s (2017) analysis of 37,599 crowdworkers (19% female) on ‘a popular freelancing platform’, showed that women earn 62–89 cents for every $1 earned by male workers), a pattern evident across multiple job categories (administrative, design, business services, networking management, sales and marketing, writing and translation, software development). Platform pay progression is also shown to be slower for women taskers within this study. Gender inequalities in platform job quality have also been documented in other multi-platform survey-based research by Wood et al (2019). Their survey sample (N=679, 40% female) shows female remote gig workers in the global south receiving lower proportions of gigs with high task complexity than men (Wood et al (2019). Platforms are also identified as perpetuating (rather than challenging) existing domestic gender divisions of labour (Graham et al, 2017; Kasliwal, 2020).

In response to these digital reinscriptions of gender inequality through online labour markets, scholars have begun to theorise emerging forms of female gig worker agency. A study of 2,000 female online gig workers showed that one third of women had done work under a username that kept their female identity hidden to customers and to platform algorithms (Hyperwallet, 2017). Women are also identified as more likely to quit platforms (62% of women quit within 12 months of signup compared to 54% of men) (JPM, 2016).6 Nevertheless, there remains a growing collective agreement that in ‘the ‘gig’ economy… we are witnessing what may be a third generation of sex inequality – Discrimination 3.0’ (Barzilay and Ben-David, 2016: 427).

These are important contributions and together they evidence a growing feminist intervention in studies of gig work, with a particular empirical focus on women gig workers in the global south. However, they remain a drop in the ocean: bibliometric searches by the author identify an expansive gig economy research literature boasting over 9.7 million articles, with female-centred studies accounting for less than 1 per cent of articles to date. In short, ‘research on gender and the gig economy is particularly sparse’ (Milkman et al, 2021: 360).

More than some gendered ‘varieties of platform labour’ approach that offers female nuance to earlier masculinist studies (or worse still, treats women gig workers as a separate sociological debate best left to feminist scholars), much remains to be done to bring female worker praxis to the very heart of ‘mainstream’ gig economy research and theorising. In order to feminise ‘digital labour’, it is vital that we build on recent studies to explore: the gendered material circumstances, everyday realities of work, structural constraints, and economic injustices for women online gig workers; and how these differently combine to perpetuate female online labour market disadvantage across different platforms and service segments. Several major research questions sit at the heart of this feminist digital labour agenda. How do the motivations, and everyday lived experiences of women with young families using online work platforms compare with those already documented in major (male-focused) platform labour studies? What work–life advantages do digital labour platforms offer women over previous employment roles held? What are women’s experiences of being managed by (and excluded from) platform algorithms? What are the common challenges that women have experienced on digital labour platforms, including health and safety? How do those experiences vary between women from different demographic backgrounds? And hence, what does an engagement with women, and gender relations, tell us about the opportunities and challenges of online work platforms, that previous research rooted in a masculinist lens of analysis has not? This article offers one response to these urgent questions from the UK context, concerned to advance more inclusive and ‘alternative imaginations of platform-mediated work’ (Van Doorn, 2017: 900) through new engagements with women, gender relations, social reproduction and work–family conflict.

Researching women as ‘digital labour’: methods and evidence base

This research engages with women crowdworkers in the UK, recognised as a major centre of Europe’s gig economy, and home to an estimated 5 million online gig workers (Huws and Joyce, 2016). To explore the complex decision-making processes, contradictions and work–family trade-offs that characterise these women’s everyday gig work-lives, the research employed a qualitative approach: in-depth semi-structured interviews were carried out with 49 women between January and August 2018. The majority of participants were recruited by listing the interview as an advertised paid task on PeoplePerHour (PPH). PPH is a prominent site that is well established with a large and active user base, whose design is representative of a large class of digital labour platforms focused on desk-based white collar work. PPH describes itself as ‘a community of curated freelance talent available to work for you remotely at the click of a button… 1.4 million active members globally’. Previous estimates suggest two thirds of users are UK-based (Green et al, 2013).

Task ads were placed across PPH’s key task categories: web development, design, video photo & audio writing, admin, marketing & PR, business support, social media, creative arts, mobile, translation, search marketing, extraordinary, software development. Interviews were prepaid at £25 (and held in escrow by the platform to build trust), and set above the average hourly rate of PPH taskers, after PPH fees, within the limits of the project budget.7 Task ads were regularly reposted, because anything older than three days was typically assumed to have been filled. Task ads were also placed on Upwork, Freelancer and Fiverr, but these proved less successful. However, due to workers holding multiple registrations across multiple platforms, this PPH mode of recruitment yielded 49 women active across 24 different digital labour platforms,8 with an accumulated experience of 141 years using platforms to access gig work, and combined monthly incomes from digital labour platforms of £38,405 after fees in the previous month. The majority of participants were white women (two women of colour) between 24 yrs and 44 yrs old, with dependent children (91 children total, over half pre-school age), and living in households with male partners in full-time paid employment outside the home. These women are also well qualified – two thirds hold undergraduate degrees, and one fifth postgraduate degrees.

Interviews lasted one to two hours, and typically were carried out through the platform video meeting function. The interview guide focused on: worker demographics and household situation; platform entry; platform work history; platform pay; daily/weekly work routine; work–life conflict; positive outcomes and negative experiences of platform working; lived experiences of algorithmic management; childcare impacts on what, how, where, when, and with whom platform work is done; platform advancement; support structures and suggestions for platform redesign. Research participants were also questioned on their ‘before-and-after’ experiences of platforms compared with previous employment, and any significant work–life discontinuities. After each interview, positive feedback was left on the platform as a means of enhancing each participant’s profile. The interviews were transcribed through secretarial support. Analysis was carried out through detailed coding and cross-comparison of coded transcripts to draw out key themes, commonalities of experience and sources of difference to build theory iteratively. Member checking was also used to gauge the credibility of evolving theories. The polyvocal style of write-up deliberately incorporates the voices of women gig workers, who have to date remained ‘invisible’ within digital labour research (Mateescu and Ticona, 2020).

Analysis: Women labouring through digital platforms – getting in and getting on?

There has been little research to date on… the gendered experiences of gig work. This lack of knowledge critically limits the ability of policy-makers. (Hunt and Samman, 2019: 1)

Women in this study offer an impressive breadth of services through multiple digital labour platforms, including: digital marketing, communications, social media management, accountancy, legal services, voice over work, transcription, web development, HR support, virtual assistant, content writing, translation, proof reading, copy editing, graphic design, eBay store management, bookkeeping, market research, and database management. In contrast to low complexity microtask ‘clickwork’, these workers are hired on an hourly or project basis to complete more complex tasks. Over half of the research participants engaged in online gig work alongside part-time employment as an income top-up. Most women completed 15–35 hours of platform work per week, around 20 per cent of which is unpaid job search and bidding) – with pay rates typically £15 per hour (ranging from £7 to £40 per hour), contributing between 19 per cent and 100 per cent of total household income. The analysis explores these women’s motivations for turning to online labour platforms, their experiences of using online work platforms compared to their previous formal employment, and their abilities to compete for gig work in practice. In seeking to expand the narrow terms of masculinist debate within the digital labour literature yet further, the analysis also highlights urgent issues of female health and safety not documented in previous digital labour studies.

Why do women use digital labour platforms?

In documenting workers’ motivations for using digital labour platforms to access paid work, previous studies of male gig workers have identified: greater work autonomy and freedom, use of unproductive downtime, extra cash to make ends meet, access to a global pool of customers, and help in paying for living expenses (for example, Felstiner, 2011; De Stefano, 2016; Berger et al, 2019). Indeed, online gig work has been understood by some commentators as a positive choice (for example, Kaufmann et al, 2011; Jäger et al, 2019). While some of these same motivations were also identified by women in this study, they contrast with additional drivers that include: burnout, personal illness, failure of own business, disillusionment with the corporate world, redundancy, workplace bullying, separation from partner, and in one instance, the stress of previously working five part-time jobs in combination. These negative factors fly in the face of commentaries which portray platforms as a positive choice for women. Crucially, women’s testimonies also identify drivers rooted in uneven gender divisions of reproductive labour, in ways that are not commonly identified within the digital labour research literature (but which are highly familiar to feminist scholars).

First, workers identified the role of motherhood and majority responsibilities for childcare in prompting their turn to online gig work (see also Graham et al, 2017: 147; Berg et al, 2018: 69; Churchill and Craig, 2019; Milkman et al, 2021). This group of factors includes new mothers using platforms to top up inadequate maternity pay. Several participants had not received statutory maternity pay (90 per cent of average weekly pay for the first six weeks, then £140.98 per week for a further 33 weeks) due to redundancy close to childbirth; others due to their previous temporary contract. In other cases, as self-employed gig workers some participants also did not yet have the track record of National Insurance contributions required for the alternative full-rate maternity allowance.9 Their reduced rate maternity allowance (£27 per week for 39 weeks) was identified as inadequate because ‘I was in a position where I was suddenly on a fraction of my weekly earnings, it was difficult’. Platforms were also identified as a potential means to help cover childcare costs in the absence of state provision, or else to enable greater temporal flexibility of paid work around school hours and school term times, with many participants citing a mismatch between employer-provided annual leave and school holidays, which ‘are hard because you only get five weeks holiday a year but there’s eleven weeks school holidays’.

Closely related, a second set of motivations are barriers and penalties within women’s previous employment. These include denial of a flexible working request seen as too costly and an administrative burden; being sidelined after returning from maternity leave; a lack of employer support for illness (both personal, and of dependent child); and what some participants simply described as ‘bad bosses’. Participants also articulated multiple experiences of having being turned down for promotion, of being told their skills were outdated in the wake of maternity leave, bad job interviews, and widespread perceptions that such barriers faced in previous jobs would be less apparent on digital work platforms. Indeed, many women had experienced a combination of these factors:

‘The interview was held a week after my caesarean and I still made it, but it was very evident I had been passed over because I was a mum (interestingly by a female boss who just didn’t see that women should ever put their children first). Then I had a couple of comments from another boss about coming back full-time. One comment was, ‘he’s six months old, cut the umbilical cord!’ and I was like, ‘Hang on a minute!’ So, I just thought, I could push harder and do more with my own work at home, platforms like Fiverr’.

More than the need to accommodate childcare with one’s own paid work, a third set of motivations is evident around accommodating a partners’ full time employment outside the home, again in ways largely undocumented in the digital labour literature. The majority of participants were members of dual earner households, typically with male partners in full-time paid employment outside the home (in two cases, men were also online gig work freelancers).10 As part of this, online work platforms were also hailed as offering income opportunities for women following a non-self-motivated relocation to a new town or city as a trailing spouse in support of a partner’s new job, in which their own professional networks had become devalued.

In combination, these motivations demonstrate how these women continue to ‘maximise the household utility function’ (Gramm, 1975; compare Gray and James, 2007), in ways that enable them to accommodate paid work and a majority responsibility for childcare around their partner’s work, and to enable more time with children. This set of motivations is defined relationally around family and households, divergent from the individualised motivations articulated in previous digital labour studies, in which workers’ wider families and households are undocumented. In the majority of cases women research participants assumed the majority responsibility for childcare within their households; this is rooted in gendered identities of being ‘a good mother’ that invokes a strong everyday presence in everyday child rearing not expected of ‘good fathers’ (Hardhill and van Loon, 2016). Thus while digital labour platforms are enabling a greater flexibility of paid work around childcare, they do nothing to challenge deeper social constructions of motherhood which position women as primary caregivers. In other words, online gig work might be understood as reinforcing gender inequalities of care, rather than reducing them.

Significantly, these findings echo previous research on self-employed ‘entrepreneur mothers’ engaged in ‘family-driven entrepreneurship’ (Ekinsmyth, 2011; McKie et al, 2013; McGowan et al, 2012; see also Carrigan and Duberley, 2013; Foley et al, 2018). This in response to uneven gendered divisions of household labour, motherhood penalties, barriers and frustrations within paid employment, difficulties of finding childcare arrangements to match days and times of their employment, and difficulties of negotiating flexible working arrangements – this work itself building on decades of research that examines female entrepreneurship as a response to glass ceiling constraints (for example, Buttner and Moore, 1997; Mallon and Cohen, 2001). While recent commentaries have warned against conceptualising platform workers as ‘entrepreneurs’ due to platform constraints on worker agency – with taskers bearing all the risks of entrepreneurs but rarely having any control over the means of production and distribution (Graham and Shaw, 2017) – it is important that digital labour scholars engage with this parallel body of work. Platform work for many of these women is seen ‘not as an opportunity, but as a functional necessity’ (Foley et al, 2018: 313). This is further evidenced by the use of monies earned through platform gigs including: rent, mortgage payments, payments to ex-partner for their equity share of the house, weekly food shop, paying off debt, petrol, car payments, childcare fees, new boiler, children’s clothes, school shoes, children’s extracurricular activities, household income top-up, everyday living once all bills are paid, home improvements, driving lessons, holidays. Or as one participant neatly summarised ‘I think that we are using those platforms only because we have to’.

Digital labour platforms as female advantage?

Claims around the advantages that digital labour platforms offer women have centred on: greater personal autonomy over work hours and work place, greater flexibility of paid work around childcare, and increased financial independence (for example, Slaughter, 2015; Manyika et al, 2016; Hyperwallet, 2017; compare Shade, 2018; Howcroft and Rubery, 2019). Extending the scope of these advantages beyond those identified in previous digital labour studies, participants also explained how platforms had enabled them to gain access to an international client base beyond the immediate local area, including those overseas whose real time demands for evening working fit better with some women’s time schedules around childcare and home schooling. Likewise, the role of platform work in giving back a sense of self-esteem, especially in the face of previous failed job applications subsequent to having children when multiple participants had been told that their skillsets were now dated. In this way, the benefits of gig working were articulated beyond the narrowly financial. Barriers to entry on platforms were identified as lower, with multiple participants also having been encouraged by the platform dashboard to advertise a wider range of skills than they thought they had, and which requesters subsequently hired them to do. Reinforcing this confidence boost, participants also welcomed the regular requester feedback over previous job roles:

‘Some of the client feedback I’ve had is amazing. There’s clients that come back to you again and again. If you’re sitting in an office job, you don’t know how your performance is until you have your appraisal. You just feel like you’re part of a machine. As if you’re not a valued employee. Whereas if you’re working on a freelance basis, with your own clients who you’ve managed to source yourself online, then yeah, definitely more rewarding.’

In light of these benefits, participants were asked to respond to the claim that ‘online gig work is a godsend for women’ (Slaughter, 2015). In all but two cases, participants were highly sceptical, identifying platform work not as a long-term solution, but as a stop-gap until children are old enough to go to school, and positioning the benefits of platforms as part of a more nuanced reality of gig work for women gig workers. In common with previous research, negative experiences of platform work evident in this study include: free trial labour and unpaid tasks deemed unsatisfactory (but which were then subsequently used by the requester); frequent periods of unpaid job search and bid time; limited support from platforms in event of any disputes; and service agreements skewed in favour of requesters over workers. Crucially however, they also pointed to a series of gendered constraints on their abilities to compete for online gig work, which have not been identified in previous studies, and which in combination undermine claims that digital labour platforms offer some form of fundamental challenge to stubborn gendered labour market inequalities (for example, Krieger-Boden and Sorgner, 2018):

‘Today I was writing a proposal and somebody was asking about the availability between May and August. So, I put May to July, 20 hours, August reduced availability. So, obviously, I did not say I cannot work at all’.

Participants pointed to a series of gendered constraints on their abilities to remain visible within the algorithms that platforms use to route out tasks, list eligible taskers to requesters, and enable differential gig work opportunities. Platform algorithms use worker reputational data combining feedback from previously completed tasks, frequency of gigs completed, responsiveness to clients, and other performance metrics (see also Wood et al, 2018). One participant explained the significance of algorithmic visibility, and the anxiety involved in ‘staying up’:

‘The other day actually, this broke me. PeoplePerHour emailed me and said, “Because you didn’t reply to this person… we’re going to drop your ranking for two weeks.” I was like, that’s really bad because this is my income. This isn’t a joke. This is me paying for my rent. This is me paying for food, paying for uniforms. I was like, you can’t drop me out of the algorithm because people won’t find me and I won’t be able to get any work… that is a big deal if people can’t see my profile… this is my livelihood. There’s a massive pressure to keep your ranking high.’

In terms of ‘dropping out of the algorithm’, and ranking lower in requester search listings, women identified the role of unequal gender divisions of childcare in constraining their abilities to take on platform work with a regularity that meets the workflow thresholds needed for ongoing visibility within the algorithm upon which future workflows are predicated. This included childcare constraints on the types of gig that workers feel able to bid on (inability to commit to higher paying more lucrative jobs that require quick turnaround, and/or long periods of uninterrupted working) (see Wood et al, 2019). Some workers list these family constraints publicly on their platform profiles. Others choose not to, instead turning down some gigs over others, where the scope of tasks clashed with demands of childcare:

‘Some jobs, they need this by a certain time this afternoon and I can’t juggle, I can’t take it because I know I won’t be able to deliver. I can’t juggle the kids, I have to keep an eye on them, so I wouldn’t take that which is a shame… It doesn’t work around me. It’s not suitable for me.’

These problems are reinforced by constraints on the timings of when many women gig workers are physically able to search for gigs, or reply to potential clients:

‘You are automatically not earning as much money if you are a working mum, because you’re working more limited hours… you potentially have to take more time out; look after someone else; you’re not necessarily always able to take the highest paid projects because you’re not necessarily able to commit to the hours they involve; you’re not necessarily on hand to reply to messages instantly. A lot of these platforms, I do think, have quite unrealistic demands of how quickly you can reply to things. Fiverr, for instance… I think I had a two-hour response time, but they were saying that wasn’t good enough – that I should be replying more or less instantly. Which is a ridiculous situation.’

‘Obviously if you’re sat playing with your baby, you probably don’t have your phone necessarily on you. You’re not looking at your messages. So, you’re not going to be replying instantly to things. You can even be ranked in order of how fast you’re replying to messages. So, I think while it’s a problem probably for everybody who uses these sites, I think it does probably affect mums or working parents more, who are trying to juggle both things. Because you can’t be on the sites twenty-four seven’.

In more extreme cases, these constraints led to a loss of clients due to childcare clashes with scheduled client meetings. Other participants also identified a loss of clients during pregnancy as clients anticipated a potential drop off in their ‘quality of service’ and tasker responsiveness:

‘Clients – just as I say – when I told them I was pregnant, just vanished into the ether, so… they’re long gone. But, it does feel like a bit of a regression, because I spent obviously time building up – over a year building up clients – and then quite a lot of them are now gone. I’ve now got to do it all over again.’

Reinforcing these challenges is the common observation that ‘when I went off on maternity, my ranking dropped… So, I really suffered’. Participants also pointed to gender inequalities for hard-won reputational data capital (Van Doorn and Badger, 2020) and female gig worker outcomes in the wake of relationship breakdown. Stark examples included the consequences of a post-divorce surname change back to a worker’s maiden name. The platform denied her request to change the name on an existing user profile and instead required her to build a new profile. In effect this undermined hard fought work history, feedback scores and reputational capital built up over several years – and this in a way not asked of male gig workers undergoing the same sad shift in personal circumstances:

‘I’d like to change my name because I’m divorced but I can’t because that field’s locked out… I can change everything else on my profile. Obviously, I can change my skills, I can change my photo, I can change my “about me” section. I can add photographs and certificates and things, but I can’t change my name… I’ve changed my name with my bank and my mortgage and things like that, but I can’t do it on my work platform.’

While some participants identified platform advancement over time (doing fewer gigs per week yet earning more money through higher paying gigs and repeat clients), others pointed to the combined effect of these various constraints on their abilities to work up through various badges of honour that platforms bestow based on feedback and experience, which give workers a higher visibility within the algorithm, and hence visibility to potential clients. Likewise, impacts on the pay levels that women are able to achieve through online platforms. Participants described how their net income on platforms is effectively reduced relative to workers without childcare commitments, and male gig workers with children cared for by their female partners. Some women have increased their hourly fee to offset the costs of childcare needed in order to enable them to engage in platform work in the first place. However, they also recognise that setting these hourly rates ‘to make gig work pay’ make them less competitive relative to other taskers without childcare responsibilities. For other women, the costs of childcare significantly outweigh their total earnings from gig work, or at best just to break even.

In this way, workers pointed to the fundamental role that their gender identities and gendered responsibilities of care have in shaping their algorithmic visibilities and abilities to compete for gigs online, in ways that undermine celebratory claims around platforms as challenging gendered labour market inequality (for example, Krieger-Boden and Sorgner, 2018). Indeed, these challenges of competing for platform work and maintaining algorithmic visibility are reinforced by other largely undocumented problems concerning the health and safety of women working on digital labour platforms.

Platforming female well-being?

Ongoing constructions of ‘digital labour’ as an abstract commodity mean that gig workers’ experiences of health and safety don’t feature highly in platform-centric accounts. The legal classification of taskers as ‘self-employed independent contractors’ also means that platforms bear no responsibility for providing paid sick leave or maternity leave. Previous workerist studies have begun to document a series of health issues among gig workers, that include anxiety, stress, fatigue, repetitive strain injury and COVID-19 (for example, Howard, 2017; Christie and Ward, 2019). But within this small body of work, issues of female health and safety are absent. Participants outlined some of the wellbeing issues that they face as women engaged in gig work through digital labour platforms, which were common among multiple women in this study, and in ways undocumented in the expansive digital labour research literature.

Identified problems included the health challenges of doing platform work while pregnant, as workers seek to build up savings by taking on additional work:

‘During the bulk of the pregnancy – from August through to March – I was taking on extra work at that point and try and make sure I could save as much as I could in the meantime. Mostly working some evenings. In some cases, it just meant working a bit longer – working through lunch. Things like that. It varied from time to time. But, yes, I did quite a bit of work in the evenings during that time. I didn’t do so much at the weekends, just because I was exhausted by that point. But, yes working evenings; workings slightly longer days – things like that.’

‘I’d take the time off in the day and then as soon as my husband gets in, that’s it: I’m working for the night. I did it when I was pregnant – you’re working and you’re already tired. You’ve already done a whole day of either work or looking after a child and that’s real time when you should be able to put your feet up and relax a bit and then you’re starting a day’s work again.’

Underpinning these identified problems, participants explained the origins and outcomes of limited maternity leave support for women gig workers, as a function of their ‘self-employed independent contractor’ status – with multiple women turning to gig work soon after giving birth to top up inadequate statutory maternity pay (SMP). These experiences were often contrasted with having had a previous child under maternity leave arrangements in previous employment, in which work ended several weeks prior to the due date: in several cases, women had worked ‘right up until my due date (to avoid losing all my clients)’, and then returned to platform work within six weeks of giving birth, as a means of maintaining income in the absence of employer or state support, and retaining clients, but with negative impacts on their parent–child relationship, plus stress and anxiety. Indeed, in one extreme case:

‘Technically, I didn’t have any maternity leave. I worked basically almost as soon as I’d had [daughter]… it wasn’t so horrendous, because she slept a lot, but it was very tiring. She was in my office and I’d nurse her, and you know, be talking to people on the phone. But it is difficult, because you need to be able to bond with your children, but of course, when you don’t work, you don’t get paid.’

These concerns are consistent with a larger study by the UK’s first GP on-demand platform GDPQ, founded by a team of doctors who had witnessed ill health and work-related stress among self-employed new mothers, but which typically remained hidden within private homes. In their 2017 survey of 104 women using platforms to access work as ‘self-employed’ new mothers: 59 per cent admitted to suffering mental health issues caused by being forced to work immediately after giving birth, with negative impacts on the health of these mothers and their ability to bond with their new child (GDPQ, 2017). In some cases in this later study female gig workers are postponing future plans for children until they are back in secure formal employment, because: ‘we’re basically just scraping by and no more. … it’s made us think twice about having any more’.

Additional problems also extend beyond maternity, in the form of uneasy interactions with clients and potential clients. Multiple platforms require workers to include a headshot in worker profiles. Participants described the hassle of buyers using digital labour platforms as ‘an extension of Tinder’. Experiences ranged from ‘people sending messages saying, “Hello, lovely lady”, nothing really sexually overt but just awkward’ to having ‘had men comment on my photo, he wrote back saying something like, “I must say, that’s a very attractive photograph.” For fuck’s sake! And I think he might have said something like, “It’s not PC to say.” Well, just don’t say it, you idiot!’ Worse examples include the abuse of female taskers’ contact information, by male requesters:

‘I actually had a customer last year, I was put off freelancing for a little while because of this. I had a customer that knew I got home from work at 5pm, would ring me at 5pm, I’d be on the phone to him for an hour, an hour and a half every evening. He knew I had a child. He’d always be calling and I wouldn’t answer. Then I’d get emails straightaway, “Are you not interested? Shall we not pay you this month?” I found that very uncomfortable. Also, he was a man, he had my address because my invoices were there and I didn’t feel safe. He also had my mobile number so I ended up having to block him on my mobile, block him on my landline, block his texts on my phone as well. Then for a few days I was living in paranoia that he was going to turn up here. That’s awful. No one should have to feel like that.’

‘I’ve seen a few strange job requests, like people wanting you to write stories about masturbating or something like that, that’s obviously just some kind of creep… I’ve reported a couple of jobs. That’s why I don’t use the platforms so much anymore.’

Compare these experiences with the widely used advertising slogan from PPH: ‘Our mission is to empower people to live their dream’ (!). In another case, one participant of South Asian background had previously found work through TaskRabbit, with one uncomfortable task to cook for a single male client in the evening, alone in his flat, hired to impress his clients with ‘authentic’ home-cooked food:

‘Going in to people’s homes, that someone you might find a bit intimidating I mean there’s the possibility for something untoward to happen, that is always at the back of my head. Because of that, I wasn’t getting the tasks that worked with my availability, so they basically penalised me for not having enough tasks, because there’s like a certain standard that you have to maintain in order to continue on the platform.’

Adding a new gendered dimension to the kinds of ‘bad gigs’ identified in earlier studies (Wood et al, 2019), these gig work experiences were made worse by feelings of extreme isolation, a lack of employee status and all the protections that would otherwise bring, and lack of a manager in the flesh to turn to. These experiences matter, given the recognition by multiple participants of the typical gendering of tasker–requester relations being ‘most of the people that I do work for are men’, or else that ‘every person I’ve worked with in freelancing, every person who’s hired me has been a male – I’ve never been hired by a woman’.

This is a set of female digital health and safety issues on which platform user agreements are silent, and on which the digital labour literature has said very little.11 Indeed, this is also a set of worker health issues which the UK government’s Health and Safety Executive are currently unable to intervene with, despite their growing interest in women and gig work. At a December 2019 presentation of these findings to the UK HSE HQ in Liverpool, representatives explained how home-based platform workers are outside HSE’s remit because of their lack of formal employee status, and because they work outside of employer-sanctioned workplaces.

Feminising digital labour, future research directions

Despite their major role in generating economic value for platform developers and requesters across thousands of platforms worldwide, women remain marginalised within platform economy research. As part of an emergent feminist digital labour agenda, this article has built on recent studies to show how an explicit engagement with gendered relations of labour, and uneven gender divisions of care opens up new worker-based understandings of ‘digital labour’. The original analysis has identified women’s varied motivations for turning to digital labour platforms, new work–care ‘flexibilities’ achieved, and gendered constraints on workers’ abilities to compete for gigs and to remain visible within platform algorithms. The analysis also highlights urgent issues of female health and safety commonly experienced on platforms, but largely undocumented. As such, the analysis raises questions around the much-heralded ‘gender inclusiveness’ of work platforms relative to mainstream employment, and the need for platforms to assume responsibility to maintain, sustain and reproduce gig workers (beyond simply maintaining investor profits (Van Doorn and Badger, 2020)):

‘The platforms I don’t want to give too much credit because they are not doing it to empower women, they are doing it to exploit a gap in the market. They are taking money from people who have no other choice and yeah, I resent that they are capitalising on the fact that women are the ones who are expected to forgo their career in order to take care of a family. And they are saying, we will provide you this option where you can have the best of both worlds, but we are going to profit nicely off it. I guarantee it’s run by men.’

The analysis points to a potential digital reinscription of stubborn ‘analogue’ gendered labour market inequalities; and forces us to question the extent to which digital labour platforms genuinely challenge long-standing gendered labour market inequalities and exclusions. Once the novelty of the sophisticated artificial intelligence, platform architectures, and digital algorithms used to govern these women’s work-lives is acknowledged, the constraints of motherhood and care on women’s patterns of job search, working hours, pay and labour market advancement are far from novel – at least to feminist scholars. Indeed, these constraints have been brought into greater relief during COVID-19 lockdown, with homeworking women more likely to be interrupted by childcare than men in dual-earner households, and increased gender inequalities in paid work hours (Andrew et al, 2020; ILO, 2020).

It is therefore imperative that digital labour researchers engage with an expansive feminist literature on work, and build productive research partnerships with feminist scholars – as part of an enlarged gig work research community, that also includes women gig workers, in conversation with platform developers. As part of this engagement, women’s suggested changes to platform management and design might usefully inform the next grading round in the Fairwork Foundation’s Platform Labour Standards Rating System (Graham et al, 2020), to evidence platforms’ advanced ‘practical measures to promote equality of opportunity for workers from disadvantaged groups, including reasonable accommodation for pregnancy’. The point is that platforms’ claims to be ‘gender inclusive’ say nothing about the problematic terms and conditions under which women are able to earn on platforms once ‘included’, including risks to female health and safety, a lack of employer-provided pregnancy and maternity support, and the ineligibility of many women gig workers for statutory maternity pay.

In response to these new insights, and based on suggestions from women gig workers themselves, there emerge several major directions to extend this multidisciplinary research agenda. First, large-scale survey work should compare the incidence of the various motivations, experiences, constraints and needs identified here across larger regional and national cohorts of women. This should also compare female worker experiences between different digital labour platforms (including female-managed cooperative platforms), between women with different prior work histories and childcare responsibilities, between workers in households solely dependent on platforms for income versus those seeking household income top-up, and between different cities. Second, we need new longitudinal work history research that documents changes in women online gig workers’ experiences over time, including advancement on platforms, and changing online gig work-lives in relation to key changes in lifecourse (for example, pregnancy, childbirth, children starting school) and shifts in partners’ employment status. Third, future comparative work must examine how gender intersects with other axes of social difference (class, race, age, ability and sexuality) to generate different platform worker outcomes, and between women using gig work platforms in different national welfare regimes – is there a similar need for women to turn to online work platforms in other national contexts, as a means to top up maternity pay, and to achieve a better reconciliation of paid work and childcare? Fourth, in the absence of widespread trade unionisation of gig workers, research is needed on the individual and collective strategies and tactics that women are developing to reduce precarity on gig work platforms, to resist and challenge structures of algorithmic constraint, improve platform incomes, and determine better conditions of work. What changes would women make to the ways platforms are organised and managed in ways that would improve their everyday work-lives and encourage them to continue using digital labour platforms? And how might such improvements increase platforms’ abilities to recruit and retain women’s skillsets, knowledge, and expertise in mutually beneficial ways? Finally, future work should explore the uneven geographies of these gendered challenges among male primary caregivers, and the ‘flexible’ work–life benefits of digital labour platforms for male gig workers ‘going against the grain’ in assuming a greater share of childcare responsibility. Much remains to be done.

Notes

1

Antonio Aloisi on Twitter 19 August 2020; see @_aloisi 19 August 2020 https://twitter.com/_aloisi/status/1295977005071175680?s=21.

2

Platforms including Amazon M Turk allocate workers an alphanumeric ID identifier upon registration, which renders them invisible to requesters, and anonymises the underlying social relations of labour (Bergvall-Kåreborn and Howcroft, 2014: 218).

3

The constraints on accurate large-scale secondary data on online gig workforces are well documented and stem from: different survey definitions of ‘gig workers’ which undermine comparability and aggregation; gig work not meeting standard labour force survey definitions of employment; some gig workers also engaged in part-time employment; platform work not consistently reported to tax authorities; platforms’ reluctance to disclose workforce data; gig workers registered on platforms but inactive; and workers registered across multiple platforms simultaneously.

4

Gig worker complaints of gender bias in patterns of customer feedback, is a strong theme evident across multiple gig worker chatrooms including: Upwork Sucks, Fiverr Forum and others.

5

Based on an ILO survey of 564 home-based US crowdworkers (48% female).

6

Survey by JP Morgan of 240,000 platform workers across 42 different platforms.

7

The ethics of paying interviewees are complex. I followed the example of QMUL colleagues researching low-income workers in compensating participants for their time (Wills et al, 2009). The alternative unpaid interview scenario might rightly be regarded as wage theft. Initial fears of selection bias (for example, higher earning workers less willing to engage) proved unfounded, with typical hourly earnings in the participant sample extending to £40/hr. Multiple high earners donated their interview fee to Women’s Aid and saw their engagement with this research as much more important than just ‘the next gig’. To avoid workers tailoring their answers in favour of a higher task rating, and to even up lopsided power relations in the client/tasker relationship, all participants were given maximum feedback ratings regardless of interview content and quality.

8

Platforms used to access paid gig work by women in this study include: Fiverr, Copify, Spare5, Part Timers, PeoplePerHour, Freelancer, Appen, Tomedes, Upwork, YunoJuno, WeLikeToWork, WorkIt, TimeEtc, Guru, Consus, E-lance O desk, Bark.com, WeWillWork, Etsy, Freelancer Near Me, ByDay, Take Note, and Taskrabbit.

9

To be eligible for the UK’s full maternity allowance as a self-employed person, workers need to have paid Class 2 National Insurance for a minimum of 13 of the 66 weeks before their due date.

10

This motherhood role/support for a male partner took on particular significance for one female participant of Muslim background with four children. I am keen to engage more women of colour in the next phase of this research to extend these insights further.

11

See Milkman et al (2021) as an important exception.

Funding

This research was generously funded through a British Academy Mid-Career Fellowship (2018–19, MD170018), entitled ‘Digital Work-Lives and Gender Inclusive Growth in the “Sharing Economy”’.

Acknowledgements

Many thanks to all of my research participants who gave their time to this research, and whose personal work-lives are documented in this article. Thanks also to the editor and two anonymous referees (although I think I know who you are!) who really sharpened this final draft. Earlier versions of the article were presented at the University of Edinburgh 2018, University of Zurich 2019, Warwick Business School 2019, and CERIC/Leeds Business School 2020 – thanks to the audiences at all of these events for their critical feedback and encouragement. The research has also benefited from conversations with Karen Gregory, Harry Weeks, Adam Badger, Kate Hardy and Lauren Wilks.

Conflict of interest

The author declares that there is no conflict of interest.

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    • Export Citation
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    • Export Citation
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    • Export Citation
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    • Export Citation
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    • Export Citation
  • Hunt, A. and Samman, E. (2019) Gender and the Gig Economy: Critical Steps for Evidence-based Policy, Working Paper, London: Overseas Development Institute.

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    • Export Citation
  • Hunt, A., Samman, E., Tapfuma, S., Mwaura, G., Omenya, R., Kim, K., Stevano, S. and Roumer, A. (2019) Women in the Gig Economy: Paid Work, Care and Flexibility in Kenya and South Africa, London: Overseas Development Institute.

    • Search Google Scholar
    • Export Citation
  • Huws, U. and Joyce, S. (2016) Size of the UK’s “gig economy” revealed for the first time, FEPS, http://englishbulletin.adapt.it/wp-content/uploads/2016/02/crowd-working-surveypdf1.pdf.

    • Search Google Scholar
    • Export Citation
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    • Export Citation
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    • Search Google Scholar
    • Export Citation
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