Selected Papers of #AoIR2022: The 23rd Annual Conference of the Association of Internet Researchers Dublin, Ireland / 2-5 Nov 2022 Suggested Citation (APA): Fiers, F. (2022, November). Inequality and Discrimination in the Online Labor Market: A Scoping Review. Paper presented at AoIR 2022: The 23rd Annual Conference of the Association of Internet Researchers. Dublin, Ireland: AoIR. Retrieved from http://spir.aoir.org. INEQUALITY AND DISCRIMINATION IN THE ONLINE LABOR MARKET: A SCOPING REVIEW Floor Fiers Northwestern University Motivation While inequality and discrimination in the traditional labor market has been a central focus of various subfields of labor studies, economics and sociology (e.g., Bertrand & Duflo, 2017; Pager, 2007; Quillian et al., 2017), findings from traditional labor contexts may not generalize to the realm of digitally mediated labor. Nonetheless, digitally mediated labor is an increasingly prevalent: In 2016, 24% of American adults had earned money for performing a job they had found through an online platform (Pew Research Center, 2016). Such work arrangements encompass a diverse range of activities that may include selling something online, renting out property via the Internet, and performing “microtasks.” As the online labor market mediates access to opportunities to exchange work for money, it is important to understand who is able to capitalize on the existence of this labor market. Across different venues and disciplines, including sociology, economics, marketing, and computer science, there are a variety of approaches to understanding disparities in access to, participation in, and outcomes in the online labor market (e.g., Edelman et al., 2017; Hannák et al., 2017; Schor, 2017). This scoping review brings together these studies with the goals of understanding the approaches and central findings of these different strands of scholarship as well as synthesizing a new, refocused research agenda. We seek to understand how prior literature has investigated who does or does not participate as independent contractors on online labor markets and, among those participants, who is able to be successful and capitalize on their usage of the platforms. Theoretical Background Over the last few decades, digital inequality literature has advocated for studying online participation as a multistage process rather than as a set of binary outcomes (e.g., Scheerder et al., 2017; Shaw & Hargittai, 2018). Shaw and Hargittai (2018) propose a “pipeline of online participation inequalities” that breaks down the steps one needs to take before editing Wikipedia. While this is a type of online participation that is in theory accessible to all Internet users, online labor market participation requires external admission in the form of getting hired. In that way, barriers imposed by biases of hiring parties and mediating platforms significantly change the process of accessing the online labor market as opposed to other online spaces. Thus, we advance Shaw and Hargittai (2018)’s pipeline model to fit the process of becoming an independent contractor on or via online platforms and account for the power that hiring parties and platforms hold in this process. We then map prior literature across the stages of this enhanced pipeline to identify the foci of prior literature and directions for future research. Data and Methods We conducted a scoping review on the intersection of inequality and online labor, which is a type of systematic literature review that examines the state of a particular research field. The PRISMA approach (Moher et al., 2015) informed our process of systematically searching for, filtering through, and analyzing literature from five academic databases to ensure a broad and comprehensive set of studies. We filtered the data based on three clear inclusion criteria and coded the final set of 47 articles by adopting a selection of strategies that belong to the grounded theory (Corbin & Strauss, 2015). Subsequently, we lay out what aspects of and how online labor market inequality have been studied. Selected Findings and Discussion We break down online labor participation into a progression of eleven behaviors leading to participation in an online labor platform: from having heard of a platform to receiving payments and reviews (see Figure 1). Our analysis of prior literature indicates that the latter part of the pipeline of participation has received much more attention than the first half. Outcome variables related to having been hired and received a payment are particularly common in the examined body of literature. In contrast, hardly any studies take the first seven stages into account and, therefore, overlook the conditions that need to be met before an individual can perform a job or task. Within-individual analyses of participation that stretch across multiple pipeline stages are rare in the examined dataset. Similarly, prior literature has largely overlooked within-platform factors that limit one’s ability to participate online regardless of access and skill set. While unequal resource distribution generates an important set of barriers, an individual who has gained Internet access and developed digital skills might still face barriers to reaping the benefits of online labor due to bias built into the platform design, specifically as enforced by gatekeeping actors and systems (e.g., platform moderators, employers, and algorithmic intermediaries). A sole focus on resource-related barriers could falsely imply that if only people had the appropriate resources, they could participate. Therefore, this scoping review identifies a need for future research to focus on stages of the participation pipeline that get at the structural role of the platform in facilitating inequality and discrimination. References Bertrand, M., & Duflo, E. (2017). Field experiments on discrimination. In A. V. Banerjee & E. Duflo (Eds.), Handbook of Economic Field Experiments (Vol. 1, pp. 309–393). North-Holland. https://doi.org/10.1016/bs.hefe.2016.08.004 Corbin, J., & Strauss, A. (2015). Basics of qualitative research: Techniques and procedures for developing grounded theory (Fourth edition). SAGE Publications, Inc. Edelman, B., Luca, M., & Svirsky, D. (2017). Racial discrimination in the sharing economy: Evidence from a field experiment. American Economic Journal: Applied Economics, 9(2), 1–22. https://doi.org/10.1257/app.20160213 Hannák, A., Wagner, C., Garcia, D., Mislove, A., Strohmaier, M., & Wilson, C. (2017). Bias in online freelance marketplaces: Evidence from Taskrabbit and Fiverr. Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing, 1914–1933. Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P., Stewart, L. A., & PRISMA-P Group. (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic Reviews, 4(1), 1. https://doi.org/10.1186/2046-4053-4-1 Munn, Z., Peters, M. D. J., Stern, C., Tufanaru, C., McArthur, A., & Aromataris, E. (2018). Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Medical Research Methodology, 18(1), 143. https://doi.org/10.1186/s12874-018-0611-x Pager, D. (2007). The use of field experiments for studies of employment discrimination: Contributions, critiques, and directions for the future. The ANNALS of the American Academy of Political and Social Science, 609(1), 104–133. https://doi.org/10.1177/0002716206294796 Pew Research Center. (2016). Gig work, online selling and home sharing. Pew Research Center. https://www.pewresearch.org/internet/2016/11/17/gig-work-online- selling-and-home-sharing/ Quillian, L., Pager, D., Hexel, O., & Midtbøen, A. H. (2017). Meta-analysis of field experiments shows no change in racial discrimination in hiring over time. Proceedings of the National Academy of Sciences, 114(41), 10870–10875. Scheerder, A., van Deursen, A., & van Dijk, J. (2017). Determinants of Internet skills, uses and outcomes. A systematic review of the second- and third-level digital divide. Telematics and Informatics, 34(8), 1607–1624. https://doi.org/10.1016/j.tele.2017.07.007 Schor, J. B. (2017). Does the sharing economy increase inequality within the eighty percent?: Findings from a qualitative study of platform providers. Cambridge Journal of Regions, Economy and Society, 10(2), 263–279. https://doi.org/10.1093/cjres/rsw047 Shaw, A., & Hargittai, E. (2018). The Pipeline of Online Participation Inequalities: The Case of Wikipedia Editing. Journal of Communication, 68(1), 143–168. https://doi.org/10.1093/joc/jqx003 Figures Figure 1 Pipeline of participation in the online labor market