  China is the world's second largest economy. After four decades of economic
miracles, China's economy is transitioning into an advanced, knowledge-based
economy. Yet, we still lack a detailed understanding of the skills that underly
the Chinese labor force, and the development and spatial distribution of these
skills. For example, the US standardized skill taxonomy O*NET played an
important role in understanding the dynamics of manufacturing and
knowledge-based work, as well as potential risks from automation and
outsourcing. Here, we use Machine Learning techniques to bridge this gap,
creating China's first workforce skill taxonomy, and map it to O*NET. This
enables us to reveal workforce skill polarization into social-cognitive skills
and sensory-physical skills, and to explore the China's regional inequality in
light of workforce skills, and compare it to traditional metrics such as
education. We build an online tool for the public and policy makers to explore
the skill taxonomy: skills.sysu.edu.cn. We will also make the taxonomy dataset
publicly available for other researchers upon publication.
