From Double to Triple Burden: Gender Stratification in the Latin American Data Annotation Gig Economy

TL;DR

This study explores gender-based disparities in Latin America's data annotation gig economy, highlighting women's triple burdens of unpaid care, economic instability, and precarious platform work, with implications for labor rights and AI supply chains.

Contribution

It provides new insights into gender stratification, labor segmentation, and regional inequalities in the Latin American gig annotation sector through empirical survey data.

Findings

Women are disproportionately engaged in annotation due to caregiving and economic instability.

Low wages, task irregularity, and lack of benefits are key challenges faced by female annotators.

Women express ambivalence about the value of their work compared to men.

Abstract

This paper examines gender stratification in the Latin American data annotation gig economy, with a particular focus on the "triple burden" shouldered by women: unpaid care responsibilities, economic precarity, and the volatility of platform-mediated labor. Data annotation, once lauded as a democratizing force within the global gig economy, has evolved into a segmented labor market characterized by low wages, limited protections, and unequal access to higher-skilled annotation tasks. Drawing on an exploratory survey of 30 Latin American data annotators, supplemented by qualitative accounts and comparative secondary literature, this study situates female annotators within broader debates in labor economics, including segmentation theory, monopsony power in platform labor, and the reserve army of labor. Findings indicate that women are disproportionately drawn into annotation due to caregiving obligations and political-economic instability in countries such as Venezuela, Colombia, and Peru. Respondents highlight low pay, irregular access to tasks, and lack of benefits as central challenges, while also expressing ambivalence about whether their work is valued relative to male counterparts. By framing annotation as both a gendered survival strategy and a critical input in the global artificial intelligence supply chain, this paper argues for the recognition of annotation as skilled labor and for regulatory interventions that address platform accountability, wage suppression, and regional inequalities.