论文标题
中国的第一个劳动力技能分类法
China's First Workforce Skill Taxonomy
论文作者
论文摘要
中国是世界第二大经济体。经过四十年的经济奇迹,中国的经济正在转变为先进的基于知识的经济。但是,我们仍然对中国劳动力的技能以及这些技能的发展和空间分配缺乏详细的了解。例如,美国标准化的技能分类学O*NET在理解制造和基于知识的工作的动态以及自动化和外包的潜在风险中发挥了重要作用。在这里,我们使用机器学习技术来弥合这一差距,创建了中国的第一个劳动力技能分类法,并将其映射到O*网络。这使我们能够将劳动力技能两极分化揭示到社会认知技能和感官身物质技能中,并根据劳动力技能探索中国的区域不平等,并将其与传统指标(例如教育)进行比较。我们为公众和政策制定者构建了一个在线工具,以探索技能分类法:Skills.sysu.edu.cn。我们还将在出版时公开向其他研究人员公开使用分类数据集。
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.