The Measure of Class and The American Class Structure Revisited

• In Event: 50858 - Contributions to Marxist Sociology

Abstract

Social class indicates individuals’ access to economic resources and is key to understanding inequality. Current studies of social class often measure it using aggregate occupational groups. However, this measure of class may encounter the problem of using a fixed occupation-to-class mapping that neglects the important changes occurring within occupation due to technological change and organizational reform that may change an occupation’s class location over time. This study addresses this limitation by introducing a new “task-based class identification” model to evaluate an occupation's class location using text data and supervised machine learning based on Marxist class theory. Drawing on ONET’s occupational task data, I assessed class locations for detailed occupations in 2002 and 2020, linking this information to CPS surveys to map the U.S. labor force's class structure. Results reveal that while the American class structure has remained stable across four aggregate classes, significant shifts occurred within these categories. Particularly, within the non-managerial employee class, between 2002 and 2020, the share of proletarian workers declined by 8%. Decomposition analysis attributes 30% of this decline to changes in occupation size and 70% to within-occupation shifts, where proletarian workers experienced either “upskilling” or granted new supervisory tasks resulting in an upward class shifts. This important change cannot be captured by the occupation-based Weberian class analysis. Drawing on recent evidence of managers’ declining involvement in supervision tasks, I argue that there is a potential “deauthoritization of supervision,” where supervisory tasks are increasingly delegated to workers as surveillance technologies may have rendered supervision to mentorship, a task that no longer implies workplace authority.

Author

• Di Zhou, New York University