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资金的科学家利用这笔资金产生科学发现，这些发现被作为研究论文和发明专利传播。很少有数据来源将科学家与他们的学术产出联系起来，这些产出是由联邦研究赠款、出版物和专利来衡量的。因此，人们对出版物、专利和NSF赠款对薪酬和晋升等职业成果的影响了解有限。 国家科学和工程统计中心（NCSES）进行博士学位获得者调查（SDR），这是一项两年一度的纵向调查，对科学，技术，工程和数学学科（STEM）的博士学位获得者进行调查，使政策制定者和研究人员能够跟踪STEM博士学位的职业成果。NCSES将SDR与来自两个来源的出版物数据以及专利和NSF赠款数据相关联，提供了丰富的数据集，可以了解科学家和工程师的学术产出与职业轨迹的相关性。该项目将首先通过将算法匹配的出版物数据与黄金标准的手工数据进行比较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关于链接数据中的错误和解决问题的潜在解决方案。最后，时变和非时变变量将用于模拟终身教职的晋升，让我们深入了解“不发表就灭亡”的学术民间智慧该奖项反映了NSF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。

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.