Author(s): | Greene, D. Beard, N. Clegg, T. & Weight, E. |
Date: | 2023 |
Publication: | Big Data & Society |
Citation: | Greene, D., Beard, N., Clegg, T., & Weight, E. (2023). The visible body and the invisible organization: Information asymmetry and college athletics data. Big Data & Society, 10(1). https://doi.org/10.1177/20539517231179197 |
Section on webpage: | Critical Data Justice Literature |
Tenets: | Using technology intentionally to build communities and enhance learning. |
Annotation: | (Abstract) Elite athletes are constantly tracked, measured, scored, and sorted to improve their performance. Privacy is sacrificed in the name of improvement. Athletes frequently do not know why particular personal data are collected or to what end. Our interview study of 23 elite US college athletes and 26 staff members reveals that their sports play is governed through information asymmetries. These asymmetries look different for different sports with different levels of investment, different racial and gender makeups, and different performance metrics. As large, data-intensive organizations with highly differentiated subgroups, university athletics are an excellent site for theory building in critical data studies, especially given the most consequential data collected from us, with the greatest effect on our lives, is frequently a product of collective engagement with specific organizational contexts like workplaces and schools. Empirical analysis reveals two key tensions in this data regime: Athletes in high-status sports, more likely to be Black men, have relatively less freedom to see or dispute their personal data, while athletes in general are more comfortable sharing personal data with people further away from them. We build from these findings to develop a theory of collective informational harm in bounded institutional settings such as the workplace. The quantified organization, as we term it, is concerned not with monitoring individuals but building data collectives through processes of category creation and managerial data relations of coercion and consent. |