Department of Economics, Sociology, and Statistics, RAND Corporation, Santa Monica, CA, USA.
Abt Associates, Rockville, MD, USA.
Sci Rep. 2023 May 19;13(1):8119. doi: 10.1038/s41598-023-34809-1.
This paper investigates to what extent there is a 'traditional' career among individuals with a Ph.D. in a science, technology, engineering, or math (STEM) discipline. We use longitudinal data that follows the first 7-9 years of post-conferral employment among scientists who attained their degree in the U.S. between 2000 and 2008. We use three methods to identify a traditional career. The first two emphasize those most commonly observed, with two notions of commonality; the third compares the observed careers with archetypes defined by the academic pipeline. Our analysis includes the use of machine-learning methods to find patterns in careers; this paper is the first to use such methods in this setting. We find that if there is a modal, or traditional, science career, it is in non-academic employment. However, given the diversity of pathways observed, we offer the observation that traditional is a poor descriptor of science careers.
本文旨在探讨在拥有科学、技术、工程或数学（STEM）领域博士学位的个人中，“传统”职业的存在程度。我们使用纵向数据，跟踪了在美国 2000 年至 2008 年期间获得学位的科学家在授予学位后 7-9 年的首次就业情况。我们使用三种方法来识别传统职业。前两种方法强调了最常见的职业，其中包含了两种常见性的概念；第三种方法将观察到的职业与学术管道定义的原型进行比较。我们的分析包括使用机器学习方法来寻找职业模式；本文是首次在这种情况下使用此类方法。我们发现，如果存在典型的或传统的科学职业，那就是在非学术领域就业。然而，鉴于观察到的途径多样性，我们可以指出，传统是对科学职业的一个不恰当描述。
