基于多源数据的全球高层次科技人才群体判别研究——以基因组学领域为例

Research on Discrimination of Global High-level Scientific and Technological Talents Group Based on Multi-source Data——Taking genomics as an example

摘要:

本文基于高层次科技人才胜任力冰山模型,从论文、专利、重点实验室、著名企业、著名奖项和高影响力学术荣誉六个维度构建高层次科技人才群体判别指标,并以基因组学领域为研究实例,识别基因组学领域的全球高层次科技人才群体。通过对该群体进行国别、机构、代表性学者分析,发现全球约60%的高层次科技人才分布在美国,主要聚集在布洛德研究所、哈佛大学、麻省理工学院和加州大学等科研机构,并培养了Doudna, Jennifer A.、Glass, Christopher K.等杰出学者。

Abstract:

Based on the high-level scientific and technological talent competency iceberg model, this paper construct high-level scientific and technological talent group discriminant indicators from six dimensions of papers, patents, key laboratories, famous enterprises, famous awards and high-impact academic honors., and takes the field of genomics, identifing a global high-level scientific and technological talent community in the field of genomics. Through analysis of the country, institutions and representative scholars of the group, it is found that about 60% of the high-level scientific and technological talents in the world are distributed in the United States, mainly in the research institutions of the Broad Institute, Harvard University, Massachusetts Institute of Technology and the University of California, and trained outstanding scholars such as Doudna, Jennifer A., Glass, Christopher K.