Dissertations, Theses, and Capstone Projects

Date of Degree

2-2023

Document Type

Dissertation

Degree Name

Ph.D.

Program

Sociology

Advisor

Sharon Zukin

Committee Members

Thomas DeGloma

Van Tran

Richard Ocejo

Steven Vallas

Subject Categories

Inequality and Stratification | Sociology | Work, Economy and Organizations

Keywords

Inequality, Precarity, Digital Labor, Tech Organizations

Abstract

The tech industry, despite its reputation of generating “good jobs for all” and the promise that phrase offers in a city with socially and ethnically diverse, low-income populations, really creates high-paying jobs with a surprising degree of precarity. Inequality is sustained by the economic and work conditions of the tech industry—specifically, flexible employment and its adoption of an aggressively, rapidly changing technology that focuses on generating the newest, fastest, most marketable innovations. Software developers from underrepresented groups, the focus of this study, experience a complex precarity: not only are they relegated to disadvantaged job positions and treated differently from elite workers, but they face an uncertain future ahead. Software developers must prepare for imminent, continual career change by rapidly reskilling and developing strategies to cope with job insecurity. Proclaimed the backbone of future innovation and economic growth by tech company spokespersons and policy makers, these elite workers are in fact the poster children of a rising new cyber-precariat. But how exactly do tech workers experience precarity? Drawing on three years of fieldwork and 111 interviews with software workers in New York, my study parses the complex interactions between precarity, gender and racial inequality, and age discrimination. To explore multiple sources and dimensions of precarity, I identify organizational, cultural, and interpersonal mechanisms that generate precarious work conditions in large tech organizations. To understand the interconnectedness of particular dimensions of inequality, I explore how race-, sex-, and age-typing matches workers to precarious software jobs and how these practices are culturally patterned and experienced in tech workspaces.

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