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Shake That Moneymaker: Insights from Montreal’s Uber Drivers

Le mirage Uber : excursion ethnographique auprès de conducteurs et conductrices montréalais-es
Rabih Jamil et Yanick Noiseux


Cet article présente les résultats d’une ethnographie des conducteurs d’Uber à Montréal. Il s’appuie sur le cadre conceptuel de la « centrifugation de l’emploi vers les marchés périphériques » de Jean-Pierre Durand (2004). Il propose une critique du modèle d’organisation du travail qui promet « de bons revenus » et prétend créer un environnement de travail « flexible » et « sans patrons ». L’article met en lumière les caractéristiques essentielles - précarité, le contrôle du marché et la subordination à l’application - qui structurent les routines de travail quotidiennes des conducteurs et révèlent un double processus « d’accumulation par dépossession » (Harvey,2004. D’une part, leur déprolétarisation les dépossède de toutes sortes de protection ou de tout pouvoir de négociation. D’autre part, comme les conducteurs sont obligés de donner à l’entreprise un accès inconditionnel pour exploiter efficacement leurs propres actifs (voitures/téléphones/connexion Internet), ceux-ci sont dépossédés de la valeur de leur « travail mort » incarné dans leurs propriétés privées désormais monétisées (Kenney et Zysman, 2016), exploitées et consommées dans le cadre du processus de production de la valeur par Uber.

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1. Introduction

  • 1 In his research, Vili Lehdonvirta (2016) argues that Microwork emerged as ways to “compensate the s (...)

1In the neoliberal era, as elsewhere in Canada and so-called developed countries, the labour markets in Quebec have undergone a structural transformation. It is now characterized by hyper-competitiveness, the weakening of social protection measures, an increased difficulty for workers to organize collectively and technological shifts that impact the quantity and quality of jobs available (Drache et al., 2015). In this brave new world of work (Beck, 2000), clear boundaries between the firm and its surroundings are disappearing and a centrifugation dynamic is propelling jobs towards highly segmented, casualized and precarious peripheral labour markets (Durand, 2004; Noiseux, 2014). In this context, the emergence of the gig economy has come to embody one of the most iconic avatars of this dynamic of flexibilization, codification1 and deskilling through platform-based precarious working arrangements (Lehdonvirta, 2016). Before its upsurge, as candidly stated by the founder of a Crowdflower which is known as one of the world’s biggest platforms of micro-task outsourcing: [I] t was very difficult to find someone, sit them down for ten minutes and get them to work for you, and then fire them after those ten minutes. But with technology, you can actually find them, pay them a tiny amount of money and then get rid of them after you don’t need them anymore (Marvit, 2014).

2That being said, the type of employment relationship and labour market dynamic in the gig economy is not entirely new. The use of subcontractors, temping agencies and/or independent (or so-called independent) work has been on the rise for at least 40 years in Quebec (D’Amours, 2006). The term “gig” itself has long been used by musicians, while its deleterious implications regarding job conditions and collective organization were already being discussed as early as 1906 (Commons, 1906). In this sense, the questions and issues raised in the scientific literature on self-employment and non-standard/atypical work (Bernier et al. 2003; Chaykowsky, 2005; Cranford et al., 2005; D’Amours, 2009; Noiseux, 2014) are thus pertinent when we attempt to contemplate the gig economy. In addition to the obvious contention around the “tiny amount of money” as a central feature associated with gig work, and more broadly around the application of minimum labor standards;  the issues of capital-planned workers’ atomization (Bourdieu, 1998), crumbling job security (Standing, 2011), maladapted social security schemes (Boucher and Noiseux, 2018) and difficulties regarding collective organization (Silver, 2003; Fine, 2006; Milkman, 2014) in late capitalism are also well discussed. The precariat (Standing, 2011) and the expansion of the working poor contingent (Shipler, 2005; Ulysse, 2006) thus existed before the birth of the so-called sharing economy based on the app-driven crowdsourcing of precarious gig-jobs. On the other hand, new debates are coming to the fore about working arrangements’ specificities in the gig economy. The increasingly shorter duration of contracts on which the gig economy is reliant has reached unprecedented limits: zero-hours contracts (Freedland et al., 2015). This might account to the time taken to travel from Point A to Point B for Uber drivers or the time spent on a “human intelligence task” for Amazon Mechanical Turk workers. The algorithmic disciplining (Aneesh, 2009), not new in itself but promoted as the main management tool in the gig economy, leads to new forms of domination using behavioural science to push alienation into new territories (Scheiber, 2017). We may also wonder how these new forms of employment are blurring the boundary between work and leisure, or between labour and “playbor” (Cherry and Aloisi, 2017), thus transforming the very meaning we give to work (Ferrer Connil, 2017). Finally, even if this is far from exhausting all the questions raised, one may wonder what the impacts of a gig economy are, in which the worker no longer only sells his labour. He/she is requested to grant the application the right to freely exploit the productive force of his/her personal assets (car, phone, bike, empty room or even rented apartments). This is not to undermine the worker’s alienation from their own data produced during their working hours and then captured, processed, codified and generated as a new commodity owned by the platform organization. In the case of Uber, workers’ data, until now, represents a key input in the rationalization of the overall production process and critical for their market dominance. The latter has been the subject of an increasing amount of research works (both conceptual and empirical) aiming at understanding the determinants of its organizational model as well as the capitalist mode of value production (Srnicek 2017; Tucker 2017). Other works investigated the daily working conditions of the drivers (Rosenblat and Stark, 2016; Wells and al., 2017), the algorithmic management (Lee M. and al., 2015; Mohlmann and Zalamnson, 2017) and the drivers’ reclassifications as “partners” (Prassl and Risak, 2016; Cherry 2016).

3In this paper, which presents the results of an ongoing ethnography of Uber drivers in Montreal and builds on the extensive literature on the gig economy; we draw on Jean-Pierre Durand’s “job centrifugation dynamic” (2004) conceptual framework and offer a critique of Uber’s business model, which promises “good money” and claims to create a “flexible” and “no-boss” work environment. We intend at deconstructing the Uber narrative by exposing its central features (precarity, market control scheduling and app-subordination) which structures drivers’ daily work routines. This will allow us to reconsider the Uber model, not so much as a new trend, but mainly as an accentuation of the job centrifugation dynamic, which exacerbates its deleterious effect on earnings, social protection, job security and the ability to control the labour process. The article is structured around four parts. Following this introduction, the second section outlines the methodological choices used in the fieldwork. The third section provides a contextualization of the Uber model of organization within the history of labour market fragmentation, the fissuring of workplaces and the centrifugation of the worker towards peripheral labour markets. It also provides a snapshot on the precarity of the working poor in Quebec. The fourth section will be detailing our findings.

2. Methodology

  • 2 Rabih Jamil conducted the fieldwork.
  • 3 As we initiated the research in the summer of 2016, when Uber was still operating illegally in Mont (...)
  • 4 As a result, we shifted our methodological framework towards conducting ethnographically inspired i (...)
  • 5 Their method included the creation of paid tasks to reach out to active workers operating on the Me (...)

4The results presented in this article proceed from an ongoing ethnographic work conducted in relation to Uber-drivers, which began in the summer of 20162. Following a series of six preliminary semi-structured interviews with drivers operating in the Province of Quebec3, we grasped the need to acquire a more in-depth understanding of the relational context embedded within the Uber model4. These interviews inquired about the employment history of the drivers, their motives to operate on the Uber platform before it was legalized, their revenues, the inter-drivers’ dynamics as well as their interactions with the app. This exploratory phase was critical to familiarize with the drivers’ community and developing our initial understanding of their daily challenges as uncertified drivers isolated behind the wheels. Also, it helped us capture key elements of the relation between drivers and the app (i.e., eligibility, acceptance rate, the five-star evaluation system, price surging mechanisms, etc.). Accordingly, we prioritized two main strategies to gather our empirical material: in-car discussion and netnography. The in-car-discussion methodological choice was inspired by the work of researchers associated with the Dynamo project (Salehi et al., 2015)5. Adapting it to our case, we decided to use Uber’s services as a rider. This allowed us to observe and interact with drivers in situ, without causing any disruption of their daily routine. Moreover, it helped us to learn more about the drivers’ demographics, their employment history, their motives and working hours, and their perception regarding the app. To the best of our knowledge, this is the first academic research project that uses such an approach – the in-car discussions – as part of a comprehensive data collection protocol.

  • 6 Sayarah (2013) carried out an in-depth review of research that used “netnography” to investigate on (...)
  • 7 In the context of the platform economy, an increasing number of researchers has been performing obs (...)

5Our thorough and comprehensive observations of an online web-based forum were made in line with Kozinets’ (2002)6 study of online communities. His research methods were framed under the practices of “netnography”, or “ethnography on the Internet”, which is a “qualitative research methodology that adapts ethnographic research techniques to the study of cultures and communities emerging through computer-mediated communications” (Kozinets, 2002: 2)7. The online observations provided us with first-hand knowledge about the inter-drivers’ interactions and their perception of collegial solidarity. As in the case of Salehi et al. (2015), the online observations allowed us to capture the volatility of the relation between workers and the considerable risk of friction, as one driver told us, between “competitive colleagues”. It also informed us of drivers’ adaptive strategies to ensure better working conditions. Furthermore, it gave us access to hundreds of discussions threads regarding almost every aspect of the Uber model. We were able to observe and analyse screenshots taken from their app and addressing issues such as daily and weekly revenues, price surging, promotions, driver ratings and fare cancellations.

  • 8 In this context, talking publicly about their work experiences, challenges and even about the oppor (...)
  • 9 With the aim of understanding the dynamics of price surging and its impact on both drivers and ride (...)
  • 10 During these trips, we did not initiate discussion related to the research; nevertheless, some usef (...)

6The main phase of our fieldwork started in July 2017 and lasted until March 2018. Uber’s business operations in Quebec having been regulated, it facilitated drivers’ recruitment and allowed them to interact more freely on online forums8. We were able to conduct a series of 65 in-car discussions with drivers in Quebec (Montreal, Montérégie and Gatineau). These discussions allowed us to observe (in-situ) and analyse an important part of the drivers’ labour process and their interaction with both the riders and the app. We adopted active measures to ensure a diversified set of trips. To this end, we conducted trips during different periods of the day (early morning, peak time, end of the business day, evening and midnight) on both weekdays and weekends. We also balanced our investigation between short and long trips moving between urban centres and the suburbs9. On several occasions, we used different riders’ accounts in order to strengthen drivers’ anonymity (i.e., they cannot be technically tracked back by following one rider account). As per our ethical protocol, all drivers were informed about our research objectives and identity as academic researchers from the first moment of our conversations. In a few cases, drivers expressed their discomfort or unwillingness to proceed with the discussion. This taught us that being in the position of a rider with the ability to note the driver’s performance represented a power imbalance. As a result, we chose to conduct what we called “silent trips” where we did not initiate discussions with the drivers, which allowed them to frame the communicational context10. Throughout the in-car-discussions, we learned about drivers’ employment history, their cultural background, period of active service on the platform, their daily challenges and the tactics they are developing to adapt to the market. Moreover, we explored their untold ways to plan for their driving experiences, the investments they are making in the cars and their positioning vis-à-vis the application and the passengers.

  • 11 As the group is open to all, this includes non-drivers, such as journalists, students, researchers, (...)
  • 12 Therefore, we implemented strict measures to avoid any direct use or citing of the material (posts, (...)

7At the same time, we also conducted a thorough and prolonged “digital immersion” into the largest public Facebook pages for Uber drivers in Montreal and Quebec City. As of April 2018, more than 2,500 members11 and 100 very active core participants who post and participate in discussion were observed. Overall, more than 100 threads, englobing hundreds of comments/pictures/screenshots, were reviewed, interpreted and helped us acquire a first-hand understanding the inter-drivers’ dynamics and daily challenges. Throughout our observations, we undertook measures to abide by the ethics of carrying out research online, whereby researchers must acknowledge that, even though these groups are open to the public, participants (drivers in our case) may not be fully aware of the implications of this situation12.

3. Contextualization and theorization

3.1 The 2008 crisis and the emergence of the gig economy

8From Taylorian factory labour to gig work, capitalism has been consistently adapting its organizational setups to safeguard its profit margins despite a series of global crises. Following the great recession of 2007-8, we have witnessed a new cycle in the reorganization of work relations through the emergence of several global entities, such as Uber (2008), Airbnb (2008)13, TaskRabbit (2008)14, Deliveroo (2013)15 and Foodora (2014)16. These new players share two common features: they all use the Internet infrastructure to match “demand and supply of work and services at an extremely high speed” (DeStephano, 2015) within local markets, and they all reclassify workers as independent contractors (Prassl and Risak, 2015). As a result, the already growing non-standard/atypical working arrangements have registered new categories of employment with no guarantee of a stable income, nor access to social protection. Elert and Henerkson assessed the transformation induced by an organization such as Uber. They propose the approach of an “evasive entrepreneurship”, which is a “profit-driven business activity in the market that introduces Schumpeterian technological or organizational innovations in order to evade the existing institutional framework (2016: 10). Uber is the most emblematic company of this emerging gig economy and has since grown exponentially to dominate the global market for local transportation. In the U.S., their active drivers increased from below 50,000 in January 2013 to 464,681 drivers by December 2015 (Hall & Krueger, 2016). Hence, one third of those drivers kept on actively “ubering” for the next two years while only 11% went inactive after one month (ibid: 18). Today, the application accounts for 75 million riders and 3 million drivers (Uber, online17). They completed 4 billion trips (by 2017) across more than 600 cities in 63 countries, averaging 15 million trips per day or 143 trips per second (ibid). Moreover, the organization managed to raise more than 21.5 billion USD in 21 rounds of funding and its market value reached 62 billion USD while registering around 2.4 billion USD as profit in the first quarter of 2018 (Crunchbase, online)18.

9In October 2014, Uber launched its service in Montreal, followed by Quebec City in February 2015, and in both Laval and Longueuil a few months later. For two years, the company operated illegally, and hundreds of drivers were progressively fined by the local authorities19. As of March 2016, the Uber fleet in the Province of Quebec relied on more than 3,500 drivers (Roy, 2016). In June 2016, the Assemblée Nationale du Quebec (National Assembly of Quebec) enacted the Act to Amend Various Legislative Provisions Respecting Mainly Transportation Services by Taxi (Bill 100)20. The new regulation was designed to accommodate the Uber model and legalized services such as UberX and Uberpool, as well as their drivers’ rating system, the data collection mechanism and dynamic pricing (also known as “price surging”). Moreover, the Taxi Industry Advisory Panel was abolished, which gave the relevant ministry the right to solely authorize pilot projects that “may have different standards and rules than those prescribed by the laws or regulations under the Minister’s administration (Bill 100: 3). Following its implementation, Quebec’s government and Uber signed an agreement21 (September 2016) overseeing the company’s operations and allowing it to operate for 50,000 hours per week, calculated as an equivalent of 300 taxi licences22. As for the drivers, the agreement, labelled as a pilot project,acknowledged their classification as “driver-partners” by Uber (without providing any further clarification) and obliged them to acquire a class 4C taxi driving permit. Nevertheless, Uber drivers were not allowed to provide transportation services outside the medium of the app (paragraph 39). In other words, they were certified by the government to work exclusively for Uber23. In discussing the regulation of Uber in Quebec, Susan Bissom-Rapp and Urwana Coiquaud stated that the province had delegated its “law-making power to the entity it aims to regulate” (2017: 10). For them, this is in line with a series of regulations intending at downgrading the labour protection and fueling the proliferation of grey zones in work relations. The current case of Uber drivers’ in Quebec echoes the situation faced by the workers, mainly women, providing home childcare (RSGs) who were classified as entrepreneurs in 2003 and for a time excluded from the right of unionization, social and legal protection under the labour laws (ibid: 9). In both cases, the government’s preferences opted for a classification which prioritizes the commercial contractual relations over the standard employment relations.

3.2 The gig economy as an extension of the job centrifugation dynamic in the post-Fordist era

10In the mid-20th century, observing the striking flaws of laissez-faire capitalism, most of the so-called developed countries adopted a Keynesian framework and chose to set full employment as the main objective guiding an interventionist economic policy. The concept of “Fordist wages relations” was developed to describe the regulation mode in this regime and designed around a central character: the factory worker working full-time on a permanent contract, earning a stable, growing income, which was sufficient to provide for the entire family. The social protection system was simultaneously built around the same character. As it is now fully acknowledged, this framework was to be challenged during the transition into the neo-liberal regime of the early 1980s. Under this new regime, where labour was viewed as just another commodity, which should compete between each other and be subjected to market forces, greater labour flexibility and reduced social protections were praised as the new leitmotifs. In these conditions, the “Platform capitalism” (Srnicek N., 2017), as argued by Eric Tucker (2017), appeared as a response to the socioeconomic transformations which declined the standard employment relationship and fueled the “growth of precarious work, including own-account self-employment and temporary work”.

11To take stock of the deepening fragmentation of labour markets under these new circumstances, rather than turning to the classic dichotomies between primary and secondary markets (Wilkinson, 1981), internal and external job markets (Reve, 1990) and between formal and informal work (Lewis, 1979); the “job centrifugation dynamic” concept (see Figure 1), inspired by Atkinson’s research (1985) on the flexible firm was developed by Durand to characterize the new era. In short, “recent developments in the employment system seem to imply that the centre-periphery paradigm now works on several levels”, and that “the issue of outsourcing, temporary work (…), the self-employed (…) that had traditionally been attributed to the periphery, is now harboured in the heart of the production systems” (2004: 186).

12For the author, the dynamic of job centrifugation pushing employment towards peripheral labour markets results in a breakdown of working conditions, while still conserving the ability of central firms to control and direct the labour process. Within the new context, lower wages and restricted access to social protection and fringe benefits are associated with working conditions that are constantly eroded by the proliferation of different employment statuses. By enhancing competition among workers and directly targeting group solidarity, this labour transformation has also enacted a “methodical destruction of the collective” (Bourdieu, 1998). Such reasoning bridges with the most recent reflexions on platform capitalism by David Weill and Tanya Goldman (2016) who argue that the current transformation induced by the digital technologies are “part of a much broader context of profound changes that have and will continue to transform the workplace for millions of workers”. In this perspective they assume that many of those organizations are using the technological edge, namely the algorithmic organization of the labour process, to deepen the fissuring of workplaces24. In the same line, Nick Srnicek (2017: 76) describes electronic platforms as a model of “hyper-outsourced” organizations whereby workers, fixed capital, maintenance and training are outsourced. In the case of Uber, we argue, the workers’ centrifugation is further accentuated so individual drivers are being classified as “partners” rather than subcontractors. During the London litigation process, in the case of drivers Aslam Y. and Farrar J., the legal representative of Uber referred to the company in London as a “mosaic of 30,000 small businesses linked by a common platform25. This explicit tendency towards promoting the drivers-Uber relation as mere commercial relation between “partners” is more likely, we believe, to be an imposed franchising, which is one of the features of a fissured workplace as argued by David Weill (2014). As a result, individual drivers are pushed to an unbalanced partnership in which multibillions global corporate is exploiting their living labour force and their “petty capital” as argued by Eric Tucker (2016) in his investigation of the Uber case in Toronto.

  • 26 This term refers to the Internal Revenue Services (IRS) form, which must be filed by whoever pays m (...)
  • 27 In a recent study, Lawrence Katz and Alan Krueger estimated that “the share of workers in alternati (...)
  • 28 For the Poverty and Employment Precarity in Southern Ontario (PEPSO) research group, “Employment th (...)
  • 29 Non-standard employment, as we define it, includes part-time work (less than 30 hours a week), temp (...)

13In these conditions, the gig economy in general, and Uber’s gig job model in particular, can be inserted within the job centrifugation dynamic. In the USA, it is functionally responding to the flourishing so-called “1099 economy26, whereas self-employment and independent contracting are being increasingly recognized as the norm for gaining access to the job market27. While specific statistics on the gig economy are not available in Canada (nor in Quebec); we do know that the country, according to the OECD, has the highest rate of low-paid workers, a situation now affecting one quarter of workers and illustrating a long-term trend, which started in the mid-1970s (Larochelle and Coté, 2009). Even though the proportion of non-standard employment in total employment has stabilized in the last 10 years; it should be clearly stated that atypical jobs have become a central feature of Canadian labour markets: less than half of the country’s workers had a standard employment relation in 2013 (PEPSO, 2015: 10)28. As for Quebec, the share of people with atypical employment29 (all forms combined) in total employment increased drastically from 16.7% in 1976 to almost 40% in 2015 (Matte et al., 1998; ISQ, 2017). Self-employed workers (without paid assistants) represented a significant share of the overall so-called “independent workers” (374,400 out of 540,000 workers, Cloutier-Villeneuve, 2014). This last category was singled out as the most frequent category of the atypical work in the period between 2011 and 2013 as the share of independent workers with paid assistants lost five points while the full-time temporary jobs increased by 4 points in the period between 1997/99 and 2011/13. This explicitly shows that the landscape of the atypical work in Quebec has been increasingly shifting towards less entrepreneurial features and normalization of insecure jobs. In the same line, workers’ remuneration may represent another feature of impoverished labour market in Quebec. Available data shows that around 23% of workers (of which 60% are women) are earning less than $15 per hours (half of them are earning less than $12).

14In short, as elsewhere in the Western world, Quebec’s job system has undergone fundamental changes over the last 40 years. Two complementary phenomena stand out: a decline in permanent, stable, full-time employment and an increase in the number of non-standard workers. The new productive “combinatoire” has introduced a centrifugal movement of jobs towards peripheral markets, while the proliferation of employment statuses has led to increasing numbers of jobs that are poorly paid, offer only partial eligibility for private benefits, and provide limited access to public benefits, union representation and collective bargaining(Noiseux, 2014). Furthermore, these upheavals in the job market have a greater impact on specific categories of individuals according to class, ethnicity, age (Noiseux, 2012), and sex (Crespo, 2009; Noiseux, 2011). As we will see further on in Section 2, the Uber gig work model clearly fits within this framework.

3.3 The gig economy as an expression of state-enabled, competition-driven neoliberalism

  • 30 This, in turn, is largely correlated with the personal characteristics of workers, such as age, sex (...)

15The transformations of the labour markets in advanced capitalism, as presented in the last section, is neither random nor the effect of laissez-faire policies. Rather, they are the result of decisions made by states consistently guided by the principle of competition (Dardot and Laval, 2009). To put it bluntly, the state plays a crucial role in provoking competition between workers located at the bottom of labour markets, such that these decisions affect the employment and living conditions of the working poor engaged in the gig economy. As we have shown elsewhere, while the trend has been towards the widening of the welfare state in Quebec and Canada in the decades following the Second World War, the economic setbacks of the late 1970s bolstered the adoption of neo-liberal policies. Through the transformation of unemployment insurance and social assistance programs (realigned around the workfare model), but also by refusing to adapt labour laws to the differentiated needs of the increasingly numerous atypical workers; the state engaged in a planned remodelling of labour markets fostered by a Friedmanian-type of interventionism aiming at increasing competition between workers, and the pool of workers, at the rough end of the labour markets (Boucher and Noiseux, 2018). The end result, 40 years later, is a labour market that is, more than ever, characterized by employment status-based segmentation30, precariousness and the inequality of access to social and labour rights protections.

  • 31 In Quebec, workers have to be recognized as “salaried” in order to unionize, unless a labour court (...)
  • 32 Fewer than 40% of unemployed Canadians now have access to unemployment insurance, compared to more (...)

16The Uber case clearly highlights the central role played by the state in catalysing the centrifugation dynamic. On the one hand, after allowing Uber to enter the market and to operate at the regulatory margins for over two years, and therefore enabling it to shape a new “grey zone of employment” (Azais, 2015); Quebec’s government has, as we have seen, recently legalized its operations in the province, while creating a new employment status, labelled as “driver-partner”, which is nowhere to be found in the labour laws. Although it is certainly too soon to clearly understand the consequences and the full significance of this new status, it can already be stated that it could correlate with the driver’s inadmissibility to most labour-protection schemes inherited from the Fordist era. It will also most probably restrict drivers’ ability to organize collectively31. Regarding the catalysing role of the state, and a substantial amount of driver’s background encountered during our fieldwork fit this narrative (cf. 3.1), it can also be said that the multiple remodelling of unemployment insurance and social assistance programs over the years has laid the foundations for the growth of the gig economy. In other words, by restricting access to unemployment insurance32 and by “activating” social assistance in the direction of the workfare model, the state has left behind an important pool of distressed workers, who can now be mobilized under the gig economy model.

4. Deconstructing the Uber Model, Evidence from the Field

17The Uber story, as stated across its main webpage33, headlines the creation of possibilities for “riders, drivers and cities” as the company ultimate objective. It confirms that the app is in fact “changing the logistical fabric of cities around the world” and defines its mission as making transportation as reliable as running water”, so “everyone benefits” including its drivers who can find in Uber “a new flexible way to earn money”. This last assertion was explicitly placed upfront by David Plouffe, former Uber chief adviser and board members, who identified Uber as critically helping individuals overcome the challenges of wage stagnation, work-life balance, underemployment and student loans (Uber Newsroom, 2015). He further claimed that Uber “can quite literally help transport people out of poverty, offering people affordable rides whenever, wherever they need one” (ibid). He also underlined that Uber is “simply asking cities to allow their citizens to use their personal assets – their cars – to make money by driving their fellow citizens around their city” (ibid). The company also refers to available data showing that, “in London, nearly a third of driver partners live in areas where unemployment rates are highest (Uber, 2018, online34). These assertions are also in line with Plouffe’s claims that, “[i]n France, 25 percent of our over 10,000 drivers were unemployed before driving with Uber, and around 40 percent of those had been out of work for more than a year” (Uber Newsroom, 201535). In sum, as a self-proclaimed working-class saviour, Uber has been promoting a model of work relations based on the promise of liberating workers from hardship, inflexibility at work and the ongoing disciplining practices in conventional work settings. This overpromised freedom of work is overlooking the fact that a significant number of those workers would not be in need to get engaged in “microtasking” in a healthy economy with an adequate supply of good jobs (Srnicek, 2017: 82). The table below presents the threefold Uber marketing package being sold to drivers as the pillars of workers’ emancipatory path.

18In the following, we contest the “Uber story” and critically expose how this business model is accentuating work precarity and workers’ subordination rather than boosting their autonomy and flexibility. To this end, this section will be subdivided into three parts, which will directly respond to the three pillars of the Uber model, as we identified throughout their main promotional campaign.

4.1 A diverse community of car owners “making good money”?

19In August 2017, Uber launched a new promotional campaign highlighting the stories of five Montreal drivers36. The campaign framed the Uber driving experience as civic engagement, which was aimed at inducing social change rather than as a work activity, in which workers provide a paid service. It portrayed drivers as agents of change, using some of their driving experience to gain support for social causes, such as fighting child hunger in Africa, or act as ambassadors of their city while socializing with tourists’ riders. The campaign magnified the stories of two female drivers, drawing attention to their status as mothers, who benefit from their driving work as a way to pursue their studies, while taking care of their children. In this first section, addressing and going beyond the “make good money” assertion as shown in table 1, we investigate the validity of this rhetoric by answering three interconnected questions.

4.1.1 Social entrepreneurs or working poor car “owners”?

  • 37 In order to respect the confidentiality agreement we have with the drivers, their real names have b (...)

20Our first interviewed driver, Andrew37, was a long-term unemployed man in his mid-40s with a university degree in cultural studies and unable to make ends meet with the insufficient monthly welfare assistance. He presented himself as a libertarian who wished to be involved in an emerging technology that would change the way of doing business and saw Uber as a way to get in touch with others interested in innovative technologies. Another driver, Steve, in his early-20s and with a hearing impairment, viewed his driving experience as an opportunity to be productive despite being labelled as “unfit for work” and excluded from several jobs, including taxi driving. When first interviewed, both drivers, who still received social assistance while ubering, attested to have managed to have somehow improve their revenues through the app. However, their stories reveal more about their adaptive strategies to ensure a decent income in a difficult context. Not only did Andrew state that he had to use his credit card limit to purchase an eligible car – a “2006” – at a time when he used to live one hour outside the vicinity of Montreal where Uber was still operating illegally, but, as shown below, he also had to make extreme decisions to be able to break with his prolonged unemployment status.

21“As a result, I didn’t sleep very well, because if Uber was not successful then I would have this car that I couldn’t pay for, and my credit card had no more margin… By the end of March 2015, I started “ubering”. It was working, I started having clients (…) But the thing is I live (…) an hour outside Montreal (…) outside of Uber territory. I brought a rolled-up mattress, which I put it in the back of my car, and I slept in my car [in a public building], they had underground parking there. My car is long, so I could sleep (…) Because it was winter time, so I would sleep in my car, and then in the morning I would go to Starbucks to clean my face, have a coffee, and then I would do Uber. That is how it began for me (…) And that’s what I was doing in March, April and May of 2015.”

22Similarly, Steve’s strategy to overcome his five years of unemployment and the dozens of rejected jobs applications was centred on his driving experience with Uber. For more than one year, he was illegally driving despite being harassed on several occasions by the taxi “cowboys”38 and being fined by the Bureau du Taxi in Montreal. Hence, as a strategy to increase his income, he used to drive as a full-timer and casually rented his car to other drivers. At the time of our first interview, he was driving for eight hours per day and leasing his two cars, for other drivers with hearing impairments, around the clock at a rate of CAD 30 per eight-hour shift when he was not working.

  • 39 The third driver whom we interviewed in the summer of 2016 stopped driving a few months later as he (...)

23One year later, we interviewed both drivers to track the impact of the Uber regulation on their work conditions. Andrew was now further away from his self-identification as a libertarian entrepreneur or a “free spirit”. He was on his way to join “Téo Taxi”, a new electric taxi company hiring full-time drivers with a fixed salary and paid overtime. As for Steve, he was recovering from a work accident that he had had while working in a workshop where he had found a job after stopping “ubering”. He kept on with his side business of subleasing cars but emphasized the significant amount of time and money he was paying for the maintenance of the cars39. Their stories can be added to the many other testimonies that we gathered during the 65 in-car discussions and the prolonged online observations we conducted between July 2017 and March 2018. In one of the discussions, Emmanuel, a self-employed mechanic and father of two, who is originally from Haiti, summed up his situation by stating that, for him, Uber is not only an option. Rather, it is a “must” when he is short of cash and has to do the grocery shopping. Similarly, some of the student drivers also identify their driving work as a “must” in order to reduce their debt burden without being exposed to discriminatory practices and rigid work conditions in conventional on-call jobs.

  • 40 Many of the drivers we encountered were previously active in the services sectors, students trying (...)

24Overall, our findings reveal that the drivers’ community is overpopulated with workers already engaged in precarious work relations and who are deferring to Uber as a way to make ends meet40. Far from being motivated by “social entrepreneurship”, driving for Uber is more likely to be a key adaptive strategy used by the working poor in their quest for a living wage. That being said, this narrative clearly points to a landscape where Uber is, as it claims while not using this language, effectively exploiting a fragmented labour market while “helping” precarious workers to increase their revenue in the context of deteriorating remuneration levels and increasingly restricted access to insufficient social protection allowances. Our findings bridge with those outlined through the work of a group of researchers who investigated the work lives of Uber drivers in Washington, D.C. (Wells and al., 2017) as their research also revealed that drivers were trapped in a “debt-to-work pipeline” with significant financial risks while struggling to cope with the company’s self-regulations and “near total control over what really matters for drivers”.

4.1.2 Everybody is Ubering?

25As for the “diversity” of Uber-drivers, it clearly does not exist when we look at the situation through a gender lens. In the course of nine months of almost daily use of Uber services, we failed to encounter more than two female drivers out of the 65 in-car discussion we had. The first encounter with a female driver came after more than two months and through a female passenger profile41. In common with gender-based diversity, the ethnic heterogeneity of the drivers’ community is very slim. By March 2018, when we concluded our fieldwork, it was clear that we had been sat behind a reserved army of declassed male migrants. Out of the 65 in-car-discussions we had, fewer than five non-migrant drivers (or drivers not belonging to visible minorities). Instead, what we had seen in front of us was an overconcentration of migrants from the Middle East and North Africa, followed by drivers from Haitian backgrounds42. To a significant extent, this mirrors the ethnic structure of the taxi driver community in Montreal, as underlined by Saiid, a Montreal driver who used to work as a taxi driver and had joined the Uber network two years ago. Saiid labels ubering as a “migrants’ job”43. This situation seems to be close to what is observed elsewhere in other Western cities. In the case of London, available data released by Transport for London (TFL) authorities indicate that, among migrant drivers who are holders of private hire driving licences, the majority are non-white migrants44. Moreover, Uber had identified the last decisions of London mayor which aimed at heralding a “new era” for London’s taxi and private hire trades (ridesharing companies)45 as discriminating against their drivers of whom many are immigrants (Davies, 2017). In its released statement, Uber identified their Londoners drivers as working hard “to look after themselves and their families” (ibid). Similarly, in Paris, Uber is being seen as a key opportunity for the second generation of migrants living in the suburbs and trapped in poverty and despair46.

  • 47 This study highlights that the highest probability of overqualification concerns marginalized migra (...)

26Emblematic of the socioeconomic backgrounds of others declassed migrant drivers, Saiid arrived in Quebec five years ago as a skilled migrant with a university degree in agronomy. He never managed to secure job interviews, although he fulfilled all technical requirements and had already accredited his degrees. For him, migrants are pushed into precarious jobs due to systematic “hidden discriminatory practices”. Similarly, Kanj, a Lebanese migrant with more than 15 years of work experience in logistics, was also ubering as he had failed to find employment in his field of expertise. He “ubers” while pursuing a short-term course at university, which he believes will help him increase his chances of being offered “quality jobs”. Another driver, who recently landed, stated that while he had previously worked as a mechanical engineer in charge of developing automation programs for industrial production lines back home, his driving experience with Uber represents his entry strategy into Quebec’s highly restrictive job market. One of the two female drivers we encountered, told us that “ubering” was their (with her spouse) fastest way to generate revenues. Therefore, they bought a car and started driving on a rotating shift-work system. Rather than a diversified portrait of a heterogeneous labour force, similar stories of overqualified migrants ‘ubering’ for a living and overcoming economic exclusion were continuously forthcoming during our fieldwork. Encountering drivers with degrees in engineering, education, sciences and business administration was such a frequent occurrence in our fieldwork that it routinely informed our discussions. In turn, this contributed to the saturation that we had reached by March 2018. These drivers’ appreciation of Uber is centred around its ability to spare them the challenges of on-call employment, which is more likely to be taken up by newly arriving migrants, as stated by an Algerian migrant who detailed his successive work experiences. As a father of three children, he felt uncomfortable with being under the radar of an employer and on-call to fill the gaps in staffing during periods of extreme weather conditions, weekends and holidays. With Uber, he had invested part of his savings in a qualified car and started, “cashing-in”. These findings are in line with the conclusion of the recent CIRANO report, which pointed out to the professional overqualification among the immigrant workers in Quebec (Boudarbat and Montmarquette, 201647).

4.1.3 A money machine?

27The first thing we note at this stage of our study regarding “the money question” is that it is clear that, in order to survive ubering, a long period of learning by trial and error must be endured. The burden of this behind-the-wheels-on-your-own learning period is fully borne by drivers striving for cash without fully acknowledging the implications for their physical health and, as we will see, the depreciation of their assets resulting from their work for Uber. As the driving experience is a highly customized economic activity, but also because our research objectives do not intend to measure the net earnings grossed by drivers, it is certainly risky48. Drivers’ income is the output of a combination of factors (type of car, driving hours, share of surged trips out of the overall accepted rides, maintenance cost, fiscal deduction and/or conformity, etc.). That being said, in February 2016, Christopher Nardi, a journalist with Journal de Montreal, worked as a full-time Uber driver for a week, earning no more than CAD 4.60 per working hour after deducting all expenses. Nardi’s gross earnings amounted to CAD 608 for 35 working hours, while his net revenue (after deducting Uber’s share) was CAD 456.08, which is the equivalent of CAD 13 per hour. However, once he calculated the net expenses for driving a Toyota Corolla (CAA) for 671 kilometres per week, his take-home earnings dropped to CAD 161, which equated to CAD 4.6 per hour49. This dismal account echoes our empirical findings. As per our observations in the field, this seems to close resemble a portrait of workers who do not concentrate most of their activities on high-demand periods.

  • 50 The issue of “choice” will be discussed further in the following section.
  • 51 The Uber website states that drivers’ “payment for the trip is calculated as: ((base fare + time ra (...)

28On several occasions, we witnessed drivers posting screenshots and observed that the vast majority showed meagre daily or weekly revenues. These observations and the resulting debates taught us that drivers’ revenues were very irregular, to say the least. They appear to be extremely volatile and fluctuate dramatically from one day to another, or even during the same day, depending on what time and in which neighbourhood the driver “chose50” to Uber. Inexperienced drivers lacking functional knowledge of the market were usually those most affected by this dynamic. In some of the online posts, drivers referred to negative earnings per hour when a driver spent more than one hour with no trip, or when making a very long trip (over 50 minutes) for less than CAD 20. As an example of this kind of situation, one driver posted details of one of his long trips, in which he had to drive for 410 kilometres in four hours for CAD 187, with his net earnings reduced to CAD 140 after deducting Uber’s share. He stated that this journey had cost him CAD 40 in fuel. While discussing the matter with his fellow drivers, he expressed his doubt regarding the profitability of such long trips, taking into consideration the car depreciation cost and the time lost during the empty drive back. Other drivers exclusively target the downtown area, which means that they undertake a lot of small trips mounting to CAD 6, although their fares can fall to CAD 4 or even less when accounting for expenses and Uber’s share of the fare51. While we have to say that some drivers do talk about their relatively high gross income online, they often overlook the fact that they drove close to 12 hours per day in the process.

  • 52 These are also more likely to be inexperienced drivers, but we also observed this situation in the (...)
  • 53 To be able to drive for Uber, Rahim, a driver we encountered, had to change his car and buy the new (...)

29We also found that the quest for cash is pushing drivers to implement different coping strategies. A considerable number of drivers is shifting between driving via the UberX platform and delivering food via the Uber Eats platform. Their rationale is simple: it is always better to cash-in rather than patrolling the streets with no clients during periods of low demand. After all, every minute count; this is especially true for drivers seeking to make extra money in a couple of hours per day52. Besides (and sometimes alongside) this, some drivers have decided to make serious investment decisions to maintain their Uber livelihoods. Some adopt strategies to lower their running costs related to fuel and maintenance expenses by investing in certain types of cars (such as electrical cars)53. Others are obliged to renew their car to abide by the company list of qualified models for UberX or UberSelect. In some cases, we encountered drivers who bought their cars exclusively for ubering. Some used up their credit limits, while others applied for a car loan or used their life savings to purchase a car (such as when religious restrictions impeded them from applying for a loan and paying interests) worth up to CAD 20,000; so that it complies with Uber’s ever-changing policies. Such capital investments, despite the high uncertainty resulting from the fact that the Uber-license in Quebec is still, even today, undergoing a trial period, increases the exit cost for drivers and in turn pushes them to introduce deeper coping strategies (long working hours, degrading their services from UberSelect to UberX or Uber Eats) to ensure higher revenues and survive the market’s ups and downs.

30In sum, even though it is difficult to calculate the exact hourly wage of drivers in Montreal, our fieldwork can certainly attest that, even when they are multiplying the aforementioned coping strategies, ubering is certainly not a “money machine” as claimed by the company. Our empirical findings tend to point in the opposite direction, revealing a business model that exploits the precarity of a largely segmented labour market, while externalizing an important part of the production cost (and risk) to further burden workers.

4.2 Working and moonlighting extended hours whenever … the market wants you in

31Offering potential drivers flexible work conditions, thus liberating them from the obligation of having to work fixed hours, is, following the money machine argument, the second most important component of Uber’s rhetoric to mobilize new drivers. Moving away from the rigidity of the Fordist model, where the machine dictates the pace (and the labour needs), and pretending to go beyond the post-Fordist/Toyotist model of ‘lean production’, where workers’ schedules are adjusted to the just-in-time labour process dictated by consumer demand, Uber’s recruitment rhetoric is focused on drivers’ own priority by promoting the notion of complete freedom in terms of when they choose to drive. In the following, again building on our observations in the field, we critically discuss Uber’s claim that drivers can drive whenever they have time, ting their own schedule and therefore be “there for all of life’s most important moments” (cf. Table 1).

  • 54 Most of them work on most holidays, thus “choosing” to skip festivities in order to cash-in on impo (...)
  • 55 The full statement is available via the following link, (...)
  • 56 Our own observations clearly show that a 12-hour working day is not exceptional, but rather a frequ (...)

32The first and most important consideration when discussing the issue of freedom to choose is the fact that this question is somehow irrelevant for many full-timers who spend most of their non-sleeping time behind the wheel. As an example, Rahim, a Montreal driver in his early 60s who is originally from Pakistan, described his daily life as a series of work intervals, which might make up more than 65 hours per week. His work starts as early as morning prayers and concludes late in the evening. Rahim was familiar with other drivers working for more than 12 hours per day. He spoke about one of his friends who used to sometimes work for more than 16 hours per day. For him as for his friends, this situation was driven by the need to earn a certain amount of money, which they considered sufficient54. For full-time drivers, the primary limit on their freedom to choose their schedule is thus Uber Canada’s in-house regulation that forces active drivers to go offline for six hours after having spent 12 hours online. This was driven by the company attempt to “prevent drowsy driving”, despite its assertion that “most driver-partners use the Uber app less than 10 hours a week”, according to a written statement55 written by Rob Khazzam, the company general manager in Canada56.

4.2.1 Chasing market demand

33At first glance, the expressed willingness to restore workers as free individuals (Miller and Rose, 1995) is clearly internalized by the drivers. Almost all of our discussants referred to the flexibility of working hours as their main motive to continue driving, despite the significant increase in the number of drivers (and subsequent lower revenues) patrolling the streets of the city. While this obsession with the right to choose their own working hours can be attested among both full-time and part-time self-identified drivers at the discursive level; more tangible information about how their work schedule is built was gathered in the course of our fieldwork. For most of the drivers, working hours are adapted to market dynamics, with their so-called ‘personalized’ work schedule largely determined by consumer demand, Uber price-surge decisions. Also, the work schedule in the first jobs, which is less likely to be controlled by part-time drivers, represents a key determinant of the drivers working hours.

  • 57 Similarly, the online discussions often showed drivers celebrating their good earnings for working (...)

34The driving experience differs significantly across the days of the week. During weekdays, i.e., Monday to Thursday, most of the drivers structure their schedule so that they catch the peak-time intervals (mornings and end of business days). They avoid the in-between periods as demand, in general, decreases. Accordingly, the weekday working day for the “average” Uber driver could be subdivided into three major blocks (mornings, afternoons and evenings). Our findings show that weekends (Thursday to Sunday) are the most desired working periods for almost all active drivers. They represent an important inducement in the drivers’ decisions about structuring their working hours. Almost all drivers agreed that working during weekends is more lucrative, even when considering the increased number of Uber-drivers on the road57. Though, some underlined the challenges they encounter on Fridays and Saturdays evenings (drunk passengers, fights, etc.). Overall, in these matters, our findings show that the bulk of drivers structure their working shifts not so much around their individual preference, but directly in line with market demand.

  • 58 Even if this is difficult to substantiate, it appears that Uber is using this tactic to increase th (...)
  • 59 Accordingly, this is how a rider manages to find an Uber partner within five minutes of waiting dur (...)
  • 60 See , accessed 24 September 2018.

35That being said, the “set your own schedule” promise is also considerably influenced by the price surging tactic used by Uber to crowd in drivers and to ensure an oversupply of labour in the market. This tactic is used mainly, but not only58, during extraordinary situations (snowstorms, freezing rain, extremely hot temperatures and special occasions, such as New Year’s Eve or even during weekends). Based on a continuous assessment of factors of demand, Uber’s algorithms assess the situation and impose a price surge on specific geographical areas, which usually lasts for a limited period (sometimes for only a few minutes, but it can also be maintained for more than an hour). Such a tactic is used to retain and soldier available labour and pull inactive drivers online59. In the extract, below, Linh Tran a product manager at Uber was explaining how the company uses their incentives to ‘dictate’ drivers on where to go so they ensure a good riding experience for their riders and reliable revenues for the drivers60.

36Experience of rush hours in San Francisco is extremely difficult because our riders and drivers are constantly moving and they’re moving in different flows of traffic. In the morning our riders do not live in the core of the city so they’re trying to get to work and they exist in surrounding the city right … but our drivers are probably … stuck in the middle of the city because they’ve just dropped off the early birds. Now they want to get out and they want to go somewhere with longer trips so they’re gonna head towards the popular places … but we don’t want them to head over there because that just degrades ETA (Estimated Arrival Time)… In order to help drivers, understand where to go? Our investments include promotions or bonuses or incentives that dictate where are the best places to go and they enable our drivers understand what they should do in this situation.

37(Uber engineering YouTube channel, video uploaded on June 5, 2018, 07’:39” – 08’:38”)

38In one of our replicated trips with price surging, we had to pay double the ordinary price because it was conducted during a snow episode. In another trip, which coincided with a large failure of the metro network, the initial price increased fourfold, rising to 52 dollars (CAD). This means that hundreds of drivers will then “deliberately choose” to be channelled by an automated management mechanism towards the designated areas. The “surge hunt” is thus a widespread practice among drivers and another significant determinant of their working schedule. Almost all drivers referred to price surging as an important determinant of the when and where to uber. This was even the case among those driving on an occasional basis or those who had decided to stop ubering.

  • 61 As we observed on the online forum, two drivers received slightly different surging rates for the s (...)

39The price surging issue is continuously highlighted and discussed on the online forum we observed. Drivers share information about surged areas, compare notifications and most importantly discuss the impact of this tactic on their revenues and working hours. Some drivers revealed on the forum that this tactic is manipulative and sometimes unfair. Several drivers post screenshots of notifications of price surging (x 2.7, x 3.0, x 4.0) received even when offline, prompting then to go on the road, only to find that the surge had ended before they reached the location. Other drivers talked about receiving notifications of high surging periods but failed to pick up any clients, even after being more than half an hour in the designated area. This prompted some drivers to speak about the “illusion of surging” when no actual trips were demanded by customers. We also observed that the tactic is unevenly used by the app, as it pushes more drivers into the market, especially new ones61. Similar situations were observed by Rosenblat and Strake (2016) as their fieldwork revealed that price surging is “unreliable for drivers”.

4.2.2 About moonlighters

  • 62 A significant number of self-identified part-time drivers are driving more than 30 hours per week. (...)

40When we enquired about those self-identified part-time drivers, which made up about half of the drivers whom we met in the course of in-car discussions62, we found that some of them worked for up to five or six hours per day. The number goes up to 12 hours during weekends. Massoud, a full-time driver, told us about his friend: “He works in the IT business, so after spending up to 8 hours behind the screen … he goes outside, takes his car and drive through Uber.” Accordingly, the ceiling of 12 driving hours in order to prevent drowsy driving is ineffective with some of the part-timers.

  • 63 During one of our in-car discussions, the non-migrant driver told us that he had decided to start w (...)

41That being said, the Uber narrative about the right to choose when you want to work has a more grounded validity when looking more specifically at drivers identified as part-timers. For student part-time drivers, for example, Uber represents an important opportunity to earn money, while not being obligated to abide by rigid work shifts or stay under the radar of on-call jobs, which are incompatible with their class schedule. Others, such as Nabil, a migrant engineer and father of three children, values Uber’s flexibility as it helps him to balance his parental role with the need to work. Hence, for Nabil, Massoud and many drivers we encountered, ubering for a given number of hours on their way to work or while coming back home, and even in the evening, is simply an easy way to earn additional money. In some cases, drivers do not even perceive it as proper work63.

42Are the moonlighters fully free to choose their own work shifts? On one of the trips, we encountered Clement, a French migrant in Montreal, who was driving on a part-time basis. He started his life as a salesman and later reoriented his career to work as a professional self-employed interior designer. Clement asserted that he ubers in his spare time or when in need of extra cash. Throughout the trip, he kept praising his driving experience as an important way to earn money and socialize with people while controlling his working hours. Along with his other fellow drivers, Clement kept on emphasizing that he could log off and log on whenever he wanted. However, once we enquired about his reasons for going online, his reply was centred on the challenges he faces as a self-employed contractor lacking a continuous flow of contracts and experiencing revenue shortages. Later in the discussion, Clement answered our question whether he had a choice about ubering or not on that particular day; his straightforward reply was “maybe no, I don’t have the choice not to work today!” .Clement’s reply was simple and transparent, and underlined the role of the market in determining his working hours for Uber.

4.3 No office, no boss… the app is in charge

43The third pillar of Uber branding targeting potential drivers’ points towards an emancipatory discourse in the form of the “no office, no boss” motto promise to reduce workers’ subordination and make them autonomous agents. Thus, ubering is not only presented as an option that allows drivers to break free of the rigidity of fixed working hours, as discussed in the previous section. It is also portrayed as a non-hierarchical work experience compared to the conditions encountered in conventional work settings. In this last section, then, we discuss the claim that drivers are self-managed, boss-less partners making their own decisions regarding when and where to drive, as well as about whom they pick up, and how they drive and provide services. Again, at first glance, whether in their cars or through their online interactions, drivers are explicitly praising the no boss aspect of their driving experience. For those drivers, Uber is freeing them from being closely supervised or ordered. Chang, a part-time driver, provided a typical example of those discourses about non-hierarchical work at Uber.

44You work for yourself, you are totally free (…) nobody forces you to do it, you don’t work for somebody. Uber is the platform you can use to make money for yourself (…) Uber is a free way! People do Uber because they don’t like to be controlled by others (…) everybody wants freedom (…) doesn’t want to be ordered (…) Uber is freedom that’s why more people are taking it up.

45Similarly, our in-car discussions with drivers and online observations regularly focused on the quest for personal freedom at work. As most migrant drivers were fully convinced that discrimination would be present wherever they worked, they saw Uber as a break from having to deal with day-to-day prejudices in the workplace. For others, ubering is a way to operate freely and make their own decisions in order to achieve some kind of personal autonomy. These discourses about the absence of control, total freedom and autonomous decision-making are, however, challenged by several features of the labour process at Uber. On this topic, it is important to state, first and foremost, that entering the market as an Uber driver is not totally control-free and involves going through some red-tape procedures. As we have seen, aspiring drivers not only have to be “accepted” by Uber, but also have to fulfil all the requirements agreed between the company and the relevant authorities, as in the case of Quebec. However, they remain not recognized as taxi drivers and thus operating within the limits of the agreement (i.e., exclusively through the app).

46The supervisory role of Uber, as well as drivers’ subordination to the company’s decisions, is also highlighted by its authoritative (and ever-changing) decisions regarding vehicle models associated with different Uber services. Those decisions, outside the control of the so-called driver-partners, can have dramatic consequences, as we found during our discussion with Andrew, a Montreal driver who had to change his car, so he could continue ubering, as his original car had become outdated. As a result, he upgraded his car for a model that would also be eligible for UberSelect as a way to increase his potential earnings. He undertook the required procedures and managed to obtain a large loan to purchase the new car. A couple of months later, the list was modified and the model he bought was disqualified for UberSelect. In expressing his discomfort, Andrew stated that he felt ‘betrayed’ by the company, with his main question being: “Why didn’t Uber inform drivers about the changes before they made their new investment?” His instinctive response was: “They don’t care”.

47Once a “partner” is on the road, driving for Uber also involves following its in-house regulations, such as the rule limiting the driving working day. Drivers also have to follow a number of directives (e.g., not having friends or family members in the car when online, using video cameras, not cancelling trips and not accepting cash)64. Moreover, Uber’s “blind ride acceptance” rule oblige drivers to accept trips without knowing the destination (Rosenblat and Stark, 2015). This rule obliges drivers, in some cases, to accept trips where they have to drive for up to 10 kilometres to pick up a client going for a trip as short as one kilometre, as confirmed by many drivers. In one case, a driver had to drive from Montreal to Laval to pick-up a passenger. On one of the early trips we conducted, the nearest driver, a student, had to drive around 24 kilometres to the pick-up location without knowing our destination. As he told us, his decision to accept the call was driven by his willingness to maintain a high rate of acceptance65.

  • 66 In June 2016, Uber rolled out a new feature, allowing the app to track drivers’ performance in the (...)
  • 67 As for the formal “No office” promise, it seems to be generally valid as workers almost entirely wo (...)
  • 68 Here is one example of an app message received by a driver regarding the professionalism of his dri (...)
  • 69 The driver who posted this screenshot expressed his concerns about security, as he received it whil (...)

48Uber drivers may not be working from an office, but their driving app can be seen as an extension of the company office, which follows them (and their car66) as soon as they are online67. There may also be no boss in the cars, but the app is always there to make sure the in-house regulations are being complied with. The app is omnipresent in the drivers’ labour process: it is used as a punch clock for initiating and terminating work shifts, as a way to access different training materials and as a tool to help manage the labour process. It is also being used as the main tool to oversee the quality assurance of the services provided as well as a platform to evaluate and discipline the drivers. More explicitly, the app may ask drivers to use a phone holder to avoid any risks while driving. As shown by drivers’ screenshots of notifications, the app can ask them to ensure clients’ comfort by adapting the type of music they are playing or by asking them to engage in friendly discussions with passengers68. Others were asked by the app to ensure that their cars were cleaned. In some cases, drivers even stated that the app would send them a notification, asking them to take an instant picture, which they thought was a way for Uber to avoid the same account being used by more than one driver69.

49In short, as we learned from our fieldwork, even if almost all the drivers we encountered perceive the app to be a purely objective technological tool facilitating their driving experience, it is certainly incarnating a very direct supervisory role within the Uber model. Using a multifunctional digital management tool, Uber often manages to disguise the supervisory role through technological innovation. But this control-vanishing technique has its limit as highlighted by Nathaniel, who labelled his condition as an Uber driver as being like “a slave of the app”.

5. Conclusion

50It is now well acknowledged that the Uber organization circumvented taxi regulations and opened up the transportation sector of the working poor, owners of cars, and striving for extra income as presented by Hill (2015: 8). Relying on a “don’t ask permission ethic”, in vogue in Silicon Valley (Kenney and Zisman, 2016), it minimized the entry cost and very quickly crowded-in precarious workers and vulnerable unemployed Montrealers. Later on, cohabiting with a government committed to the neo-liberalization of labour policies, a new “grey zone of employment” was institutionalized. This led to the legalization of a “driver-partner” status, which denies Uber drivers most of the social protection schemes inherited from the Fordist era. Acting as a market-driven ancillary social security net in a time of setbacks in social spending and wage stagnation; our observations point towards a business model where Uber is functionally mobilizing and, indeed, providing a key opportunity to a non-heterogeneous precariat comprising declassed migrants, who are relegated to and often constrained by peripheral labour markets. This ability to exploit labour market loopholes is an important part of the untold truth about Uber.

51As we have shown, driving for Uber is not a money machine. Earnings are volatile and the work involves long hours as well as the need to refine coping strategies, where the risk is fully borne by the drivers in order to make ends meet. Even the majority of the drivers who self-identified as part-timers are, in effect, job accumulators, driving for up to six hours per day (and sometimes up to 10 hours on weekends). The Uber narratives regarding flexibility are also explicitly challenged by the working conditions of drivers as observed in our fieldwork. As we have seen, drivers are chasing periods of high demand (and price surging) and structure their life accordingly. Henceforth, the “make your own schedule” rhetoric is, in effect, an extension of the offline on-call employment schemes, whereas the market remains the key determinant of workers’ schedule. Hereby, Uber managed to exploit the “just-in-time” labour force, which Marx would have labelled as a readily available ‘reserve army’, waiting to be triggered by app incentives. As for the notion of autonomous self-managed boss-less partners, it turns into an illusion once we highlight the central role of the app within the Uber model. As a multifunctional structure, it is explicitly embodying a supervisory role, which allows for a thorough monitoring of drivers’ performance, as well as acting as the main tool to enforce drivers’ disciplining. We would also like to insist that we observed a significant number of drivers being pushed to financial hazards as they are using their savings and obtaining loans to purchase cars. The latter are not only serving as prerequisites for drivers’ employability, but they also build up the company profile as a global player in the transportation industry.

52Finally, while many investigations were driven by the need to answer the question: What’s new about Uber? It is explicit that the organization main innovation is the reincarnation of the piece-wage system in context of large scale – on the global level – fully automated processes of production. In this regard, we believe Uber, and fellow application-based capitalist organizations are leaned to favourite the “form of wages most in harmony with the capitalist mode of production” (Marx, [1887] in Srnicek, 2017). Hence, as the proletarianization of the workers was triggered by the capitalists need to maximize benefits and maintain a strict control over the production process; the de-proletarianization of work relations, as imposed by Uber, we believe, should be seen as a deliberative strategic decision towards exploring new ways of maximizing profits and lowering the production costs.

53Tucker (2017), building on the works Wallace Clement (1983), reminds us that domestic system – or putting-out system – cohabited with the factory system in several sectors. Hereby, the Uber model of physically decentralized application-based employment portrayed as autonomous, flexible and profitable is being developed on the ruins of the model of the factory system which was, itself, built on the ruins of the domestic system (Gorz, 1989: 18). In this context, the freeing of the workers from the boundaries and the conditionalities of the factory systems is accompanied by an extensive centralization of the control and the supervision over the production process through the build-up of the organization algorithmic/smart machines apparatus. Today, the application workers - Uber drivers in our case - are subject to a twofold process of “accumulation by dispossession” (Harvey, 2004). On the one hand, their de-proletarianization is dispossessing them from all sorts of labour protection/benefits or bargaining power. And secondly, because drivers are obliged to give the organization unconditional access to efficiently exploit their own assets (cars/phones/Internet connection), they are being dispossessed from the value of their “dead labour” embodied in their private properties which are being monetized (Kenney and Zysman, 2016), exploited and consumed as part of the Uber process of value production.

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1 In his research, Vili Lehdonvirta (2016) argues that Microwork emerged as ways to “compensate the shortfalls of artificial intelligence”. He explained that platforms provide employers with APIs (application programing interface) which is a “codified interface through which the employer’s software can issue inputs to and receive outputs from the workforce as if it was a software module”.

2 Rabih Jamil conducted the fieldwork.

3 As we initiated the research in the summer of 2016, when Uber was still operating illegally in Montreal, reaching out to the drivers was the main challenge that we first faced. In this early stage, we were able to conduct only six individual semi-structured interviews with drivers whom we found through direct postings on social media platforms, such as Facebook groups and Kijiji, a web-based classified ads service. These interviews were mainly carried out at the drivers preferred premises and lasted from 60 to 120 minutes. Three drivers were re-interviewed one year later to assess the changes since the new regulations were enacted in 2017. The interviews were conducted as part of a larger project directed by Y. Noiseux on non-standard workers’ collective organization processes (see The authors would like to thank Alexandre Legault who helped in conducting the interviews and elaborating the interviewing process.

4 As a result, we shifted our methodological framework towards conducting ethnographically inspired investigations aiming at deconstructing the relational context linking drivers, riders and the app. To this end, our fieldwork involved three objectives: 1) to capture the nature of the relation governing the interaction between the three parties; 2) to describe the labour process within which the drivers operated; and 3) to expose the power dynamics within the Uber gig work model.

5 Their method included the creation of paid tasks to reach out to active workers operating on the Mechanical Turk, a micro-employment platform managed by e-commerce giant Amazon, without disrupting their working hours and/or affecting their daily revenues.

6 Sayarah (2013) carried out an in-depth review of research that used “netnography” to investigate online social interaction.

7 In the context of the platform economy, an increasing number of researchers has been performing observations of digital interactions as a key research method within communities of workers who are active on online labour platforms (Salehi et al., 2015; Irani and Silberman, 2013; Graham et al., 2017; Lehdonvirta, 2016). Similarly, Rosenblat and Stark (2015) conducted observations of interactions between Uber drivers on public online forums over a period of nine months.

8 In this context, talking publicly about their work experiences, challenges and even about the opportunities rendered possible by the platform was a significant risk for those non-regulated drivers who were demonized as “job stealers” by the taxi industry.

9 With the aim of understanding the dynamics of price surging and its impact on both drivers and riders, we conducted the same routes more than once.

10 During these trips, we did not initiate discussion related to the research; nevertheless, some useful information was provided by the drivers on their own initiative. The “in-car discussions” stopped once we reached saturation with their empirical input.

11 As the group is open to all, this includes non-drivers, such as journalists, students, researchers, marketing specialists and (maybe more importantly when assessing the freedom of speech on the page) one of Uber’s managers in Quebec.

12 Therefore, we implemented strict measures to avoid any direct use or citing of the material (posts, discussion threads, personalized screenshots) posted by the drivers.

13 See, accessed 17 September 2018.

14 See, accessed 17 September 2018.

15 See , accessed 17 September 2018.

16 See, accessed 17 September 2018.

17, accessed 17 September 2018.

18, accessed 17 September 2018.

19 The Bureau du Taxi in Montreal issued 580 infractions for Uber drivers in 2015, compared to only 34 in 2014. In, accessed 16 April 2018.

20 L.Q. 2016: 22., accessed 16 April 2018.

21 To read the full text of the agreement, see, accessed 16 April 2018. In September 2017, the project pilot was extended for another year with minor amendments, mainly related to training obligations.

22 Moreover, the agreement set out a compensation system if this limit on hours was exceeded.

23 While the decree recognizes Uber as a taxi intermediary, it does not recognize Uber drivers as taxi drivers.

24 “Fissuring is accomplished through a variety of business models: subcontracting, use of temporary agencies and labor brokers, franchising, licensing, and third-party management. Many business models in the on-demand sector represent a deepening fissuring of the workplace, as technology and software algorithms enable companies to further outsource significant proportions of the work”. See , accessed 24 September 2018.

25 See para 90 , accessed 24 September 2018.

26 This term refers to the Internal Revenue Services (IRS) form, which must be filed by whoever pays more than USD 600 per year for a self-employed, independent contractor or a business owner.

27 In a recent study, Lawrence Katz and Alan Krueger estimated that “the share of workers in alternative work arrangements in their main job increased by 5.7 percentage points (or by over 50 percent) from 2005 to 2015” (2016: 7). More shockingly, they underlined that “a striking implication of these estimates is that all of the net employment growth in the U.S. economy from 2005 to 2015 appears to have occurred in alternative work arrangements” (ibid: 7). The authors defined alternative work arrangements as “temporary help agency workers, on-call workers, contract workers, and independent contractors or freelancers” (ibid: 5).

28 For the Poverty and Employment Precarity in Southern Ontario (PEPSO) research group, “Employment that is secure, that provides a full range of benefits and that has a possible career path is generally viewed as better employment, and it is often referred to as a Standard Employment Relationship”, in The Precarity Penalty research report (2015: 10).

29 Non-standard employment, as we define it, includes part-time work (less than 30 hours a week), temporary work (including through temping agencies), and independent or so-called independent self-employment. For a discussion of the definition, see Noiseux (2014).

30 This, in turn, is largely correlated with the personal characteristics of workers, such as age, sex, migration status and ethnic origin.

31 In Quebec, workers have to be recognized as “salaried” in order to unionize, unless a labour court decision, which can take a year in the making, recognizes their subordination.

32 Fewer than 40% of unemployed Canadians now have access to unemployment insurance, compared to more than 80% in the 1980s. For an in-depth analysis of this evolution, see https ://, accessed 4 April 2018.

33 Uber, ’Finding the way”,, accessed 7 April 2018.

34 Uber, “Shifting expectations”,, accessed 7 April 2018.

35 See , accessed 1 October 2018

36 Uber Canada, “Testimonies”,, accessed 8 April 2018.

37 In order to respect the confidentiality agreement we have with the drivers, their real names have been changed in this paper to pseudonyms.

38, accessed 17 April 2018.

39 The third driver whom we interviewed in the summer of 2016 stopped driving a few months later as he managed to find a fixed job. For him, the driving experience was to overcome a period of unemployment and cope with the loss of income due to the reduced unemployment allowance.

40 Many of the drivers we encountered were previously active in the services sectors, students trying to heal their indebtedness, on-call workers or self-employed workers managing their small & micro-businesses or working independently.

41 As with their male colleagues, they are in search of working hours with high demand and price surging, and more importantly share the perception that they're driving work is temporary and/or serves to supplement the income received from their “normal” job. At first, we thought that a gender preference could have been embedded within the matchmaking algorithm; however, further trips discredited such an assumption. The gender disparity in the drivers’ community is also present throughout the online interactions as we did not manage to identify more than 10 active female drivers among the discussions. Interestingly, we realized recently that more women are getting involved in Uber Eats in Montreal, despite the fact that this service is known for its very low returns and relatively difficult work conditions, especially in urban areas. This points to a possible gender-based segmentation within the gig economy labour markets.

42 Similarly, on the online platform, a large majority of the drivers are actively engaged in discussions belong to visual minorities.

43 Almost all of these migrant drivers know at least two other members of their close family and circle of friends who are driving for Uber.

44 See UK Government,, accessed 10 April 2018. Accordingly, the recent TFL decision to ban Uber from the city has been seen as targeting migrant workers.

45 See , accessed 20 September 2018.

46 See,;, accessed in 16 September 2018.

47 This study highlights that the highest probability of overqualification concerns marginalized migrant workers (and members of visible minorities), even when they study in Quebec. The transferability of human capital acquired in countries of origin is the main challenge. Boudarbat and Montmarquette (2016) attributed this issue to a number of barriers, such as language deficiencies, cultural differences, the quality of education, and discrimination in the labour market (p. 59), concluding that overqualification is much higher among migrant skilled workers compared to their non-migrant peers. They also showed (ibid. p. 60; cf. Table 3.14) that the rate of overqualification among migrants with a higher education is double the rate among non-migrants.

48 Recently, the MIT-CEEPER research centre published the findings of a quantitative survey, based on a sample of over 1,000 drivers, which estimated drivers’ revenues at USD 3.37 per hour. Very quickly, these findings were highly criticized by Jonathan Hall, Uber’s chief economist, who discredited the methodology used in the survey (see, accessed 11 April 2018). In 2015, Hall, along with Alan Krueger (cited earlier in this paper), used Uber’s raw data to estimate drivers’ revenues at USD 19.04 per hour. MIT researcher, Stephen Zoepf, responded by issuing a statement in which he acknowledged some discrepancies in some aspects of the study, while asking for more transparent sharing of relevant data by Uber (, accessed 11 April 2018). To our knowledge, Uber still has not responded to his request.

49 His calculations were made on the basis of CAD 0.44 per kilometre., accessed 6 April 2018.

50 The issue of “choice” will be discussed further in the following section.

51 The Uber website states that drivers’ “payment for the trip is calculated as: ((base fare + time rate + distance rate) * surge multiplier) – Uber fee + tolls and other fees”. In one of the short trips we did (1.09 kilometres), we paid CAD 8.34 of which the share for the driver was only CAD 3.53, representing 42% of the fare we paid after deducting Uber’s fees (25%), taxes and Quebec’s operation fee. The driver’s share went up to 54% for a longer trip for which we paid CAD 23.55. While, at this moment, we are not in position to generalize this context; we note that all the operational costs, including the reservation fee, which is a “flat fee added to every trip that helps support safety initiatives for riders and drivers as well as other operational costs” (as per Uber’s website) is paid by riders. Similarly, the Quebec operation fee is a “separate variable fee that helps to defray Uber’s regulatory operating fees set by the pilot project in Quebec” (as per Uber’s website).

52 These are also more likely to be inexperienced drivers, but we also observed this situation in the case of drivers with more than one year of driving experience.

53 To be able to drive for Uber, Rahim, a driver we encountered, had to change his car and buy the newest model. He opted for a car with a hybrid engine in order to reduces his fuel costs.

54 Most of them work on most holidays, thus “choosing” to skip festivities in order to cash-in on important price surges on these occasions.

55 The full statement is available via the following link,, accessed 17 April 2018.

56 Our own observations clearly show that a 12-hour working day is not exceptional, but rather a frequent occurrence among full-timers trying to earn a decent living as discussed in the previous section.

57 Similarly, the online discussions often showed drivers celebrating their good earnings for working evenings.

58 Even if this is difficult to substantiate, it appears that Uber is using this tactic to increase the revenue of drivers when their pool of workers is not sufficient, therefore stimulating the recruitment of drivers.

59 Accordingly, this is how a rider manages to find an Uber partner within five minutes of waiting during such events, while it could take him/her more than an hour if using conventional taxi services.

60 See , accessed 24 September 2018.

61 As we observed on the online forum, two drivers received slightly different surging rates for the same period in the same location. The only difference was that the one receiving the highest rate was a newer driver.

62 A significant number of self-identified part-time drivers are driving more than 30 hours per week. It is important to note that we did not encounter any drivers who claimed to drive less than 10 hours per week.

63 During one of our in-car discussions, the non-migrant driver told us that he had decided to start working for Uber because he was tired of watching boring television shows. It should be stated that this type of narrative was uncommon in our experience.

64 Further details are available via the following link, accessed 17 April 2018.

65 In a recent initiative, the company stated that, as part of its effort to allocate more control to drivers over their work experience, it will allow them to refuse a maximum of two trip destinations per day. While such initiatives are making the driving experience less stressful, they remain an explicit sign of the company’s overall supervisory role practised through its multifunctional digital management tool embedded in the app.

66 In June 2016, Uber rolled out a new feature, allowing the app to track drivers’ performance in the car. It was intended that this new service would help the company to improve road safety. As a result, drivers receive “[d] aily reports about how their driving patterns compared to other drivers in their city – with suggestions on how to provide a smoother, safer ride; [r]eminders to drivers of the importance of taking a break when they need it; [m] essages in the driver app informing drivers that mounting their phone on the dashboard is safer than holding the phone in their hands; [s] peed display in the app that alerts drivers to the speed of their vehicle”,, accessed 17 April 2018.

67 As for the formal “No office” promise, it seems to be generally valid as workers almost entirely work from their own car. That being said, Uber drivers’ situation in this respect differs somewhat from workers engaged in contractual relations with electronic platforms, such as Mechanical Turk, Airbnb and even TaskRabbit. As expressed on the Uber website, the recruitment process is not limited to the online sign-up; rather, it requires a physical visit to the company premises to “complete a background screening. Our team will answer all of your questions and help you get ready to drive” (, accessed 15 April 2018). Moreover, the app offers, in specific cities, the service of a prescheduled in-person appointment. As for Montreal, on several occasions, we observed drivers posting requests about the company premises and/or helplines. This is welcomed by the company, which has established a “team of Uber experts” to help drivers with issues related to their accounts, fares, and tips about where and when to drive. The company’s local website encourages drivers to visit its office and meet with its experts. To a large extent, this seems to be quite similar to the type of relations already existing between some corporations and their salespeople (such as in the case of insurance companies) and therefore not entirely exempted from having to deal with some “office environment”.

68 Here is one example of an app message received by a driver regarding the professionalism of his driving: “A rider suggested that the level of conversation in the car would have been better, and we wanted you to know in case it helps you understand your ratings. Not every rider wants to talk during the ride, but top partners usually offer a friendly greeting and keep the conversation respectful and polite.”

69 The driver who posted this screenshot expressed his concerns about security, as he received it while driving on a highway and had to park on the roadside in order to take a picture of himself in a very small amount of time.

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Rabih Jamil et Yanick Noiseux, « Shake That Moneymaker: Insights from Montreal’s Uber Drivers »Revue Interventions économiques [En ligne], 60 | 2018, mis en ligne le 01 décembre 2018, consulté le 25 avril 2024. URL : ; DOI :

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Rabih Jamil

PhD Candidate in Sociology, Université de Montréal,

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Yanick Noiseux

Professeur Agrégé au département de Sociologie, Université de Montréal,

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