杨锡怡,张玲玲,柳卸林,周小宇.强化优化专业人才队伍建设 提升重大科技基础设施效能[J].中国科学院院刊,2024,39(4):737-747.
强化优化专业人才队伍建设 提升重大科技基础设施效能
Strengthen and optimize professional talent team building to enhance effectiveness of large-scale research infrastructures
强化优化专业人才队伍建设 提升重大科技基础设施效能
Strengthen and optimize professional talent team building to enhance effectiveness of large-scale research infrastructures
作者
杨锡怡1
上海科技大学 创业与管理学院 上海 201210
YANG Xiyi1
School of Entrepreneurship and Management, ShanghaiTech University, Shanghai 201210, China
张玲玲2,3,4
中国科学院大学 经济与管理学院 北京 100190;中国科学院大数据挖掘与知识管理重点实验室 北京 100190;中国科学院大学 数字经济监测预测预警与政策仿真教育部哲学社会科学实验室(培育)北京 100190
ZHANG Lingling2,3,4
School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China;Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing 100190, China;MOE Social Science Laboratory of Digital Economic Forecasts and Policy Simulation, University of Chinese Academy of Sciences, Beijing 100190, China
柳卸林1,2
上海科技大学 创业与管理学院 上海 201210;中国科学院大学 经济与管理学院 北京 100190
LIU Xielin1,2
School of Entrepreneurship and Management, ShanghaiTech University, Shanghai 201210, China;School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China
周小宇1*
上海科技大学 创业与管理学院 上海 201210
ZHOU Xiaoyu1*
School of Entrepreneurship and Management, ShanghaiTech University, Shanghai 201210, China
上海科技大学 创业与管理学院 上海 201210
YANG Xiyi1
School of Entrepreneurship and Management, ShanghaiTech University, Shanghai 201210, China
张玲玲2,3,4
中国科学院大学 经济与管理学院 北京 100190;中国科学院大数据挖掘与知识管理重点实验室 北京 100190;中国科学院大学 数字经济监测预测预警与政策仿真教育部哲学社会科学实验室(培育)北京 100190
ZHANG Lingling2,3,4
School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China;Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy of Sciences, Beijing 100190, China;MOE Social Science Laboratory of Digital Economic Forecasts and Policy Simulation, University of Chinese Academy of Sciences, Beijing 100190, China
柳卸林1,2
上海科技大学 创业与管理学院 上海 201210;中国科学院大学 经济与管理学院 北京 100190
LIU Xielin1,2
School of Entrepreneurship and Management, ShanghaiTech University, Shanghai 201210, China;School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China
周小宇1*
上海科技大学 创业与管理学院 上海 201210
ZHOU Xiaoyu1*
School of Entrepreneurship and Management, ShanghaiTech University, Shanghai 201210, China
中文关键词
重大科技基础设施;人才队伍建设;经费管理;绩效考核
英文关键词
large-scale research infrastructure;professional team building;funding management;talent performance evaluation
中文摘要
重大科技基础设施(以下简称“大设施”)的建设和运行不仅涉及基础科研问题,还涉及复杂的工程和管理问题。强化优化专业人才队伍建设是全面提升大设施效能的关键因素。目前我国在大设施人员经费支持、人才考核和激励制度建设上对设施专业工程、技术和管理人才的关注不足,严重降低了大设施专业人才队伍的稳定性和工作积极性,进而直接制约了大设施科学和社会效益的发挥。通过对我国多个大设施进行调研,梳理了在人才队伍建设方面的问题与困难。在此基础上,结合国际相关设施的先进经验,提出了3点政策建议,旨在推动我国更好地依托大设施建设世界科技强国。
英文摘要
The construction and operation of large-scale research infrastructures involves not only basic scientific research issues, but also complex engineering and management issues. Therefore, strengthening and optimizing professional talent team-building is a key factor in comprehensively improving the effectiveness of large-scale research infrastructures. However, current management system of these infrastructures pays insufficient attention to professional engineering and technical talents and management talents in terms of financial support, talent evaluation, and incentive system construction, which has seriously reduced the stability and work enthusiasm of these talents, which in turn directly restricts the scientific and social benefits of the infrastructures. By investigating several typical domestic large-scale research infrastructures, this study sorts out their problems and difficulties in professional talent team-building. On this basis, combined with the advanced experience of international related infrastructures, this study puts forward three policy suggestions, aiming to enable China to better rely on large-scale research infrastructures to become a world scientific and technological power.
DOI10.16418/j.issn.1000-3045.20240206001