量化科学界的流失：基于队列的38个OECD国家科学家纵向研究
Quantifying Attrition in Science: A Cohort-Based, Longitudinal Study of Scientists in 38 OECD Countries
AI总结：
本研究利用Scopus数据，基于队列纵向追踪38个OECD国家16个STEMM学科的男女科学家，通过生存分析揭示学术流失的性别、学科及时代差异，发现流失的性别差异正逐渐缩小。
摘要：
在本文中，我们探讨科学界成员如何离开学术科学，以及流失（定义为停止发表）在不同性别、学科和时间上的差异。我们的方法基于队列且具有纵向性：我们长期追踪个体男女科学家，并量化传统上被称为“离开科学”的现象。利用Scopus（一个全球出版物与引文的文献计量数据库）的出版元数据，我们追踪了来自38个OECD国家、于2000年（N=142,776）和2010年（N=232,843）开始发表成果的科学家的发表生涯细节。本研究仅限于16个STEMM学科（科学、技术、工程、数学和医学），我们追踪这两个队列的个体学术产出直至2022年。我们使用生存分析来比较男女科学家的流失情况。随着科学界女性增多以及队列内女性比例增加，流失的性别差异正变得越来越小。除了所有STEMM学科层面的总体聚合变化外，在学科层面和不同时期也发现了广泛而细微的变化。对于男性与女性而言，科学界的流失因学科不同而意味着不同的事情；此外，对于进入科学劳动力的不同队列科学家而言，它也意味着不同的事情。最后，本研究测试了全球文献计量数据集，为探索流失中的性别和学科差异提供了新机遇。
英文摘要：
In this paper, we explore how members of the scientific community leave academic science and how attrition (defined as ceasing to publish) differs across genders, academic disciplines, and over time. Our approach is cohort-based and longitudinal: We track individual male and female scientists over time and quantify the phenomenon traditionally referred to as 'leaving science.' Using publication metadata from Scopus - a global bibliometric database of publications and citations - we follow the details of the publishing careers of scientists from 38 OECD countries who started publishing in 2000 (N = 142,776) and 2010 (N = 232,843). Our study is restricted to 16 STEMM disciplines (science, technology, engineering, mathematics, and medicine), and we track the individual scholarly output of the two cohorts until 2022. We use survival analysis to compare attrition of men and women scientists. With more women in science and more women within cohorts, attrition is becoming ever less gendered. In addition to the combined aggregated changes at the level of all STEMM disciplines, widely nuanced changes were found to occur at the discipline level and over time. Attrition in science means different things for men versus women depending on the discipline; moreover, it means different things for scientists from different cohorts entering the scientific workforce. Finally, global bibliometric datasets were tested in the current study, opening new opportunities to explore gender and disciplinary differences in attrition.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
