Using Publication, Patent, and NSF Grant Data Linked to the Survey of Doctorate Recipients to Understand Science Career Trajectories

从联邦政府获得研究经费的科学家用它来产生科学发现，这些发现以研究论文和发明的形式传播，并获得专利。很少有数据来源将科学家与他们的学术产出联系起来，以联邦研究资助、出版物和专利来衡量。因此，人们对出版物、专利和NSF资助对职业成果（如薪酬和晋升）的影响了解有限。美国国家科学与工程统计中心（NCSES）开展了博士学位获得者调查（SDR），这是一项两年一次的科学、技术、工程和数学学科（STEM）博士学位获得者的纵向调查，使政策制定者和研究人员能够跟踪STEM博士的职业成果。NCSES将SDR与来自两个来源的出版物数据，以及专利和NSF拨款数据联系起来，提供了一个丰富的数据集，用于了解科学家和工程师的学术成果如何与职业轨迹相关。本项目将首先通过比较与算法匹配的出版物数据与手工整理的黄金标准数据来检查数据链接的质量。该项目的第二阶段将评估出版物数据中的测量误差对纵向SDR数据的影响。这项工作的结果将告知研究界链接数据中的错误和解决它的潜在解决方案。最后，利用时变变量和非时变变量对终身职位晋升进行建模，以深入了解“要么发表，要么灭亡”的学术民间智慧是否对科学家的职业轨迹产生了有意义的影响。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Scientists receiving research funding from the federal government use it to produce scientific discoveries that are disseminated as research papers and inventions that become patented. Few data sources link scientists to their scholarly output as measured by federal research grants, publications, and patents. As a result, there is a limited understanding of the impact of publications, patents, and NSF grants on career outcomes such as pay and promotion. The National Center for Science and Engineering Statistics (NCSES) conducts the Survey of Doctorate Recipients (SDR), a biennial, longitudinal survey of doctorate recipients in science, technology, engineering, and mathematics disciplines (STEM) which allows policymakers and researchers to track the career outcomes of STEM doctorates. NCSES linked the SDR with publications data from two sources, as well as data on patents and NSF grants providing a rich dataset with which to understand how the scholarly output of scientists and engineers correlates with career trajectories.This project will first examine the quality of the data linkages by comparing the algorithm-matched publication data to Gold Standard, hand-curated data. The second phase of this project will evaluate the effect of measurement error in publications data on the longitudinal SDR data. Results from this work will inform the research community about the error in the linked data and potential solutions for addressing it. Finally, time varying and non-time varying variables will be used to model promotion to tenure, providing insight into whether the academic folk wisdom of “publish or perish” has meaningful impact on scientists’ career trajectories.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.