Task-Level Inequality in DAO Work Systems: An Empirical Analysis of Participation, Rewards, and Skill Structure

Abstract

Decentralized task platforms are increasingly used to coordinate online collaborative work and on-platform economic activity, yet the micro-level structures shaping participation, rewards, and skill organization remain insufficiently understood. In this paper, we conduct an empirical analysis of task-level inequality in DAO-based work systems by jointly examining task-contributor participation patterns, reward allocation, and skill structures. Using a large-scale dataset of task-contributor interactions, we investigate how participation is distributed across contributors, how rewards are concentrated, and how skill relationships are organized across tasks and participants. Our results show that participation is broadly distributed, while rewards are highly concentrated among a relatively small subset of contributors. In addition, skill distributions differ systematically between rewarded and non-rewarded tasks, as well as between earning and non-earning contributors. A skill co-occurrence analysis further reveals a sparse yet highly structured network characterized by distinct functional clusters and limited cross-domain associations. These findings provide a multi-dimensional empirical view of inequality in decentralized work systems and suggest that operational decentralization is shaped not only by open participation, but also by how work, skills, and economic rewards are organized within collaborative platforms.

Lingling Zhang

Research Assistant

Lingling Zhang is a Research Assistant in the Human-Centered Machine Intelligence Lab, working on privacy-first cloud resource prediction.

Morteza Zihayat

Principal Investigator

Dr. Morteza Zihayat is a Canada Research Chair (CRC) in Human-Centered AI and Associate Professor at Toronto Metropolitan University, Faculty of Engineering and Architectural Science. He also holds appointments as Adjunct Associate Professor at the University of Waterloo (Management Sciences) and IBM Faculty Fellow at IBM Centre for Advanced Studies. He is the Director of the Human-Centered Machine Intelligence Lab.