Platformization of Inequality: Gender and Race in Digital Labor Platforms

Isabel Munoz, Pyeonghwa Kim, Clea O'Neil, Michael Dunn, Steve Sawyer

Research output: Contribution to journalArticlepeer-review

Abstract

We contribute empirical and conceptual insights regarding the roles of digital labor platforms in online freelancing, focusing attention to social identities such as gender, race, ethnicity, and occupation. Findings highlight how digital labor platforms reinforce and exacerbate identity-based stereotypes, bias and expectations in online freelance work. We focus on online freelancing as this form of working arrangement is becoming more prevalent. Online freelancing also relies on the market-making power of digital platforms to create an online labor market. Many see this as one likely future of work with less bias. Others worry that labor platforms' market power allows them to embed known biases into new working arrangements: a platformization of inequality. Drawing on data from 108 online freelancers, we discuss six findings: 1) female freelance work is undervalued; 2) gendered occupational expectations; 3) gendered treatment; 4) shared expectations of differential values; 5) racial stereotypes and expectations; and 6) race and ethnicity as an asset. We discuss the role of design in the platformization and visibility of social identity dimensions, and the implications of the reinforced identity perceptions and marginalization in digital labor platforms.

Original languageEnglish (US)
Article number108
JournalProceedings of the ACM on Human-Computer Interaction
Volume8
Issue numberCSCW1
DOIs
StatePublished - Apr 23 2024

Keywords

  • Digital labor platforms
  • gender
  • identity
  • online freelancing
  • race
  • stereotypes

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Human-Computer Interaction
  • Computer Networks and Communications

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