Using Computational Grounded Theory to Understand Tutors’ Experiences in the Gig Economy (2021)

Abstract: The introduction of online marketplace platforms has led to the advent of new forms of flexible, on-demand (or ‘gig’) work. Yet, most prior research concerning the experience of gig workers examines delivery or crowdsourcing platforms, while the experience of the large numbers of workers who undertake educational labour in the form of tutoring gigs remains understudied. To address this, we use a computational grounded theory approach to analyse tutors’ discussions on Reddit. This approach consists of three phases including data exploration, modelling and human-centred interpretation. We use both validation and human evaluation to increase the trustworthiness and reliability of the computational methods. This paper is a work in progress and reports on the first of the three phases of this approach.

## introduction the introduction of online platforms has contributed significantly to the changing economic structure and nature of employment @xcite . in labour markets, platforms are utilised to match and mediate between independent workers and consumers through flexible arrangements, where workers are contracted to perform single discrete tasks and are paid upon task completion, known as the "gig economy" @xcite . this can provide employment opportunities for those who struggle to find work and the underemployed to supplement their income @xcite . conversely, gig employment is also known to be chronically precarious and associated with low remuneration @xcite . to achieve their earnings goals, gig workers have been found to work on average 71 hours, compared to the standard 45 hours per week @xcite . these hours, however, are not fully paid, as workers spend considerable time waiting on or looking for gigs to perform @xcite . moreover, in countries such as the uk, gig workers are not eligible for minimum wage, overtime, sick or holiday pay and health insurance primarily because they are classified as "independent contractors" and not employees @xcite , which is currently the focus of legal debates. while some platforms act only as a channel connecting gig workers with customers, others are heavily involved in the process -from job assignments and pricing to work assessment through timing and reviews @xcite . this raises doubts as to whether gig workers have sufficient job autonomy to be considered "independent contractors" or if gig economy companies are taking advantage of the current binary worker classification system (i.e., employed or self-employed) to avoid providing employee benefits to employee-like workers @xcite . furthermore, the platform economy raises ethical issues relating to their reliance on algorithmic management @xcite , the lack of transparency on their operation @xcite , and their inherent power asymmetries, as gig workers are seen as the less powerful party in the process @xcite . moreover, working on some platforms could negatively impact workers' career development, social capital and networks @xcite . the issues relating to platform labour are varied and may be more obvious on some platforms than others. some argue that location-based platforms are less flexible and autonomous than locationindependent platforms @xcite . working on "microtask" platforms can limit workers' skills and career development @xcite , while workers on "macrotask" platforms feel that their work is underappreciated and underpaid @xcite . many of these issues are especially true for people who rely ## discussion and conclusions in this section, we discuss the preliminary results from phase one (gt and lda analysis), which have allowed us to gain some early insights toward answering the research question. therefore, these initial results should be interpreted with caution. the data analysis showed that tutors in the gig economy seem to experience both platform-related and teaching-related problems. platform issues include lack of bookings, poor pay, the opacity and the unfairness of rating systems, technical issues, and challenges in reaching the platform management. comparatively, teaching-related issues appear to start from the first steps in joining these platforms, since platforms offering educational services tend to have a strict hiring process and job requirements. other issues were found related to the unpaid time spent preparing lessons, as well as the time spent waiting for tutoring gigs to perform. although tutors can depend on scheduled lessons to help them save time, it may limit their job autonomy and makes it more like a traditional work arrangement. furthermore, the initial findings suggest that there are other challenges related to teaching that tutors may need to deal with, such as managing class time, dealing with students' different abilities and needs, and fulfilling student expectations. it seems that these teaching-related issues are distinctive of tutors' experiences in the gig economy, which shed light on some aspects of the second research question regarding how their experiences compare to those of other types of gig workers. in addition to that, to perform tutoring gigs, tutors typically teach for quite long periods of uninterrupted focus, which might pose a barrier to entry for people with caregiving responsibilities or those who lack a quiet place to teach. this does not seem to conform to the assumption that locationindependent platforms offer more freedom for workers to perform tasks around life activities. nonetheless, the initial findings suggest that being location-independent has encouraged many people to join tutoring platforms during covid-19 lockdowns, most likely due to an increase in free time or because of lost work or unemployment. tutoring gigs, like most macrotasks, can help workers develop their skills and advance their careers. furthermore, there is a possibility that tutoring platforms can help people without teaching experience explore the job's suitability. tutoring online appears to be similar to working for location-dependent platforms in allowing workers to build interpersonal relationships and giving opportunities to develop longer-term relationships with students. finally, as only a small portion of the data has been analysed, our understanding of tutors' experience in the gig economy is still limited; we expect to gain more insights and a deeper understanding following our analysis of the data after the completion of phases 2 and 3 of the research plan.