Gender: Gender interacts with all of the core elements introduced in the platform livelihoods experience framework, particularly access, earnings, flexibility, and professionalism. Some studies report gender differences in engagement rates and earning by different livelihood types. But some go much further, unpacking the multifaceted, culturally and contextually embedded reasons behind these observed differences. Whether due to extra household responsibilities or societal/familial  expectations about what kinds of jobs or roles women might take, several barriers in access to capital, sexism, freedom of movement, access to ICTS, and safety are described.  A few studies probe further, exploring much of this is unique to platform work, or to work in general. We suggest it is useful to view evolutions in the gendered experience of work as intertwined with the systems though which that work can be done.

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As platform livelihoods become more widespread in the Global South, research attention has begun to disaggregate and explore dynamics by gender. Gender interacts with all of the core elements introduced in the platform livelihoods experience framework, particularly Access to Work & Markets, Earnings, Flexibility, Inclusion, Health & Safety, and Objectivity and Professionalism.

One approach has been just to try to assess the relative proportion of men and women engaged in platform livelihoods. An early and consistent finding in microtasking is that there are far more men than women involved in it (Berg 2016; Rani and Furrer 2019; Berg et al. 2018); an exception might be on some explicitly prosocial or progressive microtasking websites like Crowdflower (Lehdonvirta 2016). The skew toward males is also quite evident in ridesharing/driving (Zollmann and Wanjala 2020; Limpin and Sison 2018; Mare, Chiumbu, and Mpofu 2020; Geitung 2017). One study of motorcycle taxis in Kenya claims to have found literally only one female driver active at that time on the platform. “The reaction from most of my male customers is at first they fear that I might get them into an accident, worrying that a woman can’t drive a boda,” she shares (Gachoka and Winiecki 2020). Similarly, Chen’s (2018) study of more than 8,500 drivers in China include only 4% women (Chen 2018). The skew isn’t universal; it seems less difficult to find female Airbnb owners, at least in one study in Mexico (Ruiz-Correa et al. 2019), and of course, some labor platforms in home care services and beauty work actually skew toward women workers. In Kenya, however, with one of the main platforms in that area rotating out of consumer-focused household cleaning, Zollman and Wanjala (2020) found “few platforms offering flexible work opportunities for women without high levels of education.” 

Another approach probes observable differences in the type of work, work patterns, or even the amount of pay available to men and women. This work is easiest to do on microtask freelancing platforms where surveys are easy to administer and large datasets are available. For example, one study observed women communicating 9% less frequently than men online during tasks (Wood, Lehdonvirta, and Graham 2018). Another suggest that while 64% of men reported solving complex problems, only 41% of women said the same thing; similarly, men were twice as likely to take on high-skill tasks than women in the sample. Male respondents were more likely to undertake tasks that were highly skilled, with 50% undertaking medium- or high-skilled tasks, against just 25% of women (Wood et al. 2019). One study suggests men advance more quickly than women in freelancing (Dubey et al. 2017). Harkening back to our discussion about the interconnectedness of flexibility, availability, and earnings, another study explained and observed difference in wages between men and women to a difference in working hours8:4 hours for men vs. 7.8 for women (Muhindi 2019)

These service-level observations, though useful, only tell part of the story. One of the advantages of the type of qualitative and analytic work surveyed in this review is its ability to get behind the numbers and ask why. As is often the case with discussions of gender, these differences are multifaceted, culturally and contextually embedded, and crosscutting.

One of several unique and valuable contributions in Gray and Suri’s “ghost work” are the links they make to the history of piecework: work done at home, bit by bit in the predigital age. They draw a line from 19th century women and girls, “assembling matchboxes boxes for pennies a pop” (2019, xix) through 1990s medical transcription and BPO work. It is with that long view that the intersection of gender, flexibility, availability, and earnings becomes both more visible and more complex. They offer extended anecdotes of two women in India, each wanting to work and contribute to the family, each happy for the income, but neither interested in working outside the home. 

While women and men do ghost work roughly the same number of days and hours per week, they differ in how they spend their time. Overall, men are more likely to do ghost work during the nights and weekends, and women are more likely to do it during the day and less on the weekends…. Women are more likely to do ghost work when their familial and household responsibilities permit. Men, on the other hand, are more likely to do ghost work in the evenings and on weekends, after they have fulfilled their outside-the-home work responsibilities…. There are two ways to interpret the gendered labor of on-demand work platforms and the value that women derive from this kind of work. The first view might celebrate on-demand jobs as opportunities to free women up to have it all, imagining that on-demand work is the answer to the working woman’s dilemma of needing to leave the home to earn an income. The second view sees this work as perpetuating traditional expectations of women to handle both full-time family obligations and the workload of more formal employment. (Gray and Suri 2019, 109–10)

Indeed, this duality is reflected in other studies gathering perspectives from women around the world, across several of the distinct categories of platform livelihoods. Some attention focus on variants of the second shift of extra household responsibilities so many women face (Hochschild and Machung 1989), making it difficult to take early morning gigs outside the home for a home services platform in Kenya (Zollmann and Wanjala 2020), or to do freelancing in the evening (Melia 2020; Wood et al. 2019). Malik et. al (2020, 10) quote a participant in Pakistan:

Cultural constraints are particularly strong for women workers, some of whom have openly reported culture as a problematic factor for them even joining the freelancing industry…. “It is not like this that women are not capable. They have the responsibilities of many domestic chores. They have to cook after attending a freelancing class; she has to wash the clothes of the whole family as it is in our culture etc.” 

Others examine barriers erected independently of children and families, instead of around society’s expectations about what kinds of jobs or roles women might take. This linked to the inclusion element we described elsewhere. These include access to capital (Malik, Nicholson, and Heeks 2018), services (Gupta 2020) and MSE creation (Kabanda and Matsinhe 2019), where they might stay or move (Zollmann and Wanjala 2020), sexism (Genesis Analytics 2019) or even what kinds of devices they might be able to access. This is why in some sub-Saharan countries, the gap participation in gig work mirrors the gap in device ownership and access (Onkokame, Schoentgen, and Gillwald 2018). It’s an admittedly difficult line to tread, between acknowledging how prohibitions on movement and safety (as discussed in the health and safety element), may be reflective of real differences in risk and vulnerability confronted by women in some settings, be it time of day, transportation on off-hours, domestic workspaces, etc. (Kiarie, Singh, and Obiko 2020), with the overhang of paternalism and concurrent misplacement of the responsibility of staying safe on women as opposed to making places safe for everyone.  

Most importantly for this conversation, it’s important to tease out how much of this is unique to platform work, or to work in general. On this last dimension, a few studies (McAdam, Crowley, and Harrison 2020; Raval and Pal 2019) look at how the affordances and constraints offered by platform livelihoods change the terrain of gender and work. Notably, Raval and Pal (2019) listened to women working in a particularly challenging situation, platformed beauty work in India, to offer reflections that again illustrate elements of the duality, and “temporal architectures of power and value production.”

We flip [the] formulation to look at working class female gig-workers in India, the others whose movement and work is primarily anchored to the domestic sphere and for whom, the opportunity of platform-based gig-work appears as a socio-cultural opening more than an economic one. In highlighting these contextual priorities and harking back to our findings where the mention of “apps,” “company” and digital helped working-class women protect their dignity and bodies, we want to call for future work to seriously take up the non-economic considerations for gig-work. The politics of workplace respectability, as it relates to technology, is a critical part of what we see here. The ability of the technological artefact to transform the perceived acceptability of work that is unchanged in its actual function speaks to the agency the technology has in this setting. The service delivery enabled by the technological artefact helps the creation of a new “professional” subject who blends seamlessly into the meta narrative of a modern entrepreneurial society. We propose that the “better than (other work)” articulation of gig-work by workers is not false consciousness but rather, a recognition of the non-economic. (Raval and Pal 2019, 14)

Perhaps it is reasons like this why other studies found that women value flexibility and the chance to work from home, (D’Cruz and Noronha 2016; Berg et al. 2018, 20), or that freelancing is well-supported by family members (Bandaranayake et al. 2020). In lieu of anything clear-cut or deterministic, it is important to make distinctions between the gendering of work and the gendering of platform livelihoods; in other words how “gendered labor relations shape and limit emerging forms of digital labor” (Jack, Chen, and Jackson 2017), and how [platform] “labor processes are intertwined with economic and social capital and gender relations, gender norms and patriarchal expectations” (Gupta 2020). In this sense, the studies here from throughout the Global South will be important contributions to a growing worldwide discussion on gender and platform work (Howcroft and Rubery 2019; Schoenbaum 2016; Dubey et al. 2017; Morell, Megías, and Espelt 2020).


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