Market Uncertainty at Work: Toward a Multidimensional Measurement of Precarity

• In Event: Organizations, Occupations, and Work Section Roundtables
  In Refereed Roundtable (90 minute): Table 13: Precarious Work Contexts

Abstract

The topic of precarious work has emerged as a prominent concern in global research and policy debates over the past several decades. Though not a new phenomenon, technological, economic, and political changes have coalesced to expand the reach of a “flexible” business practice designed to accommodate increasing market uncertainty and competition. Despite the concept's theoretical richness, a central challenge remains: precarious work is difficult to define and measure in a way that captures its multidimensional nature without sacrificing analytical precision. Most existing studies either focus on survey measurements that capture isolated dimensions of precarity, such as benefits, perceived job loss risk, or schedule arrangements or use composite measures with unclear theoretical foundations, leaving the multifaceted core—subjectively perceived risks—elusive. This project bridge that gap by using large-scale job review data and supervised machine learning to construct a multi-dimensional data-driven measure of precarity. With this new measure, I examine how precarity is distributed across occupations and classes and quantify the intensity of worker sentiment attached to precarious conditions—thereby addressing critiques regarding both the empirical operationalization and conceptual clarity of precarity.

Author

• Di Xin, New York University