人才计划与科学家职业流动:以长江学者为例

[目的/意义]科学家的职业流动容易受到政策的影响。本文旨在通过回归模型分析人才计划与科学家职业流动的关系,特别是与其职业流动方向的关系。对于我国未来的人才政策制定具有参考价值。[研究设计/方法]本文以入选长江学者特聘计划的科学家为样本,构建其职业经历数据,并通过双重差分模型分析入选人才计划对职业流动行为的影响。[结论/发现]研究发现,入选长江计划促进了科学家的职业流动。在入选长江计划5年内,科学家更多地从东部地区向中西部地区流动,也更多地向排名级别更低的高校流动。[创新/价值]在研究方法上使用了回归模型而非描述性分析;研究结论为认知人才计划对科学家职业流动的影响提供了新的角度。     

Relational mechanisms governing multifaceted collaborative behavior of academic scientists in six fields of science and engineering

Norms of academic science and engineering are moving in the direction of broader applicability and transferability of knowledge beyond the borders of the university. In response, scientists are expected to engage in collaboration that includes both basic and applied collaborative activities. More specifically, the norms of science are beginning to change to allow for novel forms of collaboration that involve sharing of research ideas on multiple facets of collaborative work. This paper examines the extent to which multifaceted collaboration is attributable to relational aspects of individuals’ networks. Specifically, we ask the question: what relational aspects of social capital determine multifaceted collaboration among scientists in six fields of science and engineering? Borrowing literature from social capital and science and technology (S&T) human capital, this paper develops a multi-level model of multifaceted collaboration and presents a set of testable hypotheses. Then using data from a national survey of men and women faculty in six fields, we analyze the multi-level data: relationship or dyad level (level 1) and ego level (level 2) with hierarchical linear modeling (HLM) to predict multifaceted collaboration of academic scientists. Findings show that some relational characteristics explain multifaceted collaborative behavior as predicted, while others behave in unexpected ways. Conclusions place the findings in context for theory and policy.     

In good company: The influence of peers on industry engagement by academic scientists

Previous research on academic entrepreneurship and engagement with industry has found that the behaviour of academics is influenced by their local social context. However, we know little about the mechanisms that produce this effect. We argue that academic scientists’ industry engagement is influenced significantly by the behaviour of their peers, that is, the behaviour of colleagues of similar seniority. Using insights from social psychology, we hypothesize that these peer effects are produced by the mechanism of social comparison. In an analysis of data from multiple sources for 1370 UK academic scientists and engineers, we find that peer effects are stronger for early career individuals and weaker for star scientists, suggesting the incidence of social comparison. We argue that individuals look to their immediate peers for inspiration, because they view them as an important reference group and use them as a benchmark for their own ambitions and behaviours. Our findings have important implications for how universities may encourage scientists’ behaviours by paying attention to local work contexts.     

明星科学家能否提升转制科研院所的双重绩效？—以广东省为例

科研院所改革的重点在于加快科技成果转化,明星科学家成为影响改制目标实现的“第一要素”。以广东省科研院所改革为背景,本文探索了明星科学家在组织创新与经济效益中的作用效果,并分析了项目式与平台式改革模式的调节效果,研究发现：明星科学家对组织双重绩效均有显著的正向影响,并且对创新绩效的促进效果高于经济绩效；政府财政科技项目在明星科学家与创新绩效关系中起正向调节作用,而创新平台在明星科学家与科研院所创新绩效、经济绩效关系中均起到正向调节作用。研究结论将为科研院所的人才体系优化与资助模式改革提供参考依据。