Gender differences in dropout rate: From field, career status, and generation perspectives

IF 3.4 2区 管理学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Yunhan Yang , Chenwei Zhang , Huimin Xu , Yi Bu , Meijun Liu , Ying Ding
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引用次数: 0

Abstract

The dropout of scholars poses risks by depleting valuable resources and hindering the scientific community. Knowledge gaps on this issue lack consistency across career statuses and overlook its dynamic nature. To address this gap, we analyzed the career trajectories of over 24 million scholars in 19 fields from the MAG dataset, examining dropout rates by field, career status, and generation. Firstly, we observed an unexpectedly high proportion of transients, comprising a growing proportion of newcomers and accounting for over 50% of publications in most soft sciences. This highlights the shortage of continuants, such as scholars with full careers, who contribute to scientific communities. Secondly, our exploration into gender-specific dropout rates revealed that women exhibit a significantly higher dropout rates within the first 20 years, covering career statuses including junior dropout, early-career dropout, and mid-career dropouts. Notably, early- and mid-career dropouts demonstrate the lowest and most stable dropout rates. These insights prompted the development of a gendered scientific career model that combines changes in scholar numbers and dropout rates across career statuses. Lastly, our generational analysis spanning four generations unveiled a diminishing gender gap in dropout rates. In hard sciences, women encounter initial career challenges, with the gender gap in dropout rates decreasing over time. In contrast, the gender gap in soft sciences persists longer. These findings hold consistent across six subfields, offering implications for field evaluation, gender disparities policies, and a deeper understanding of scholarly dropout across generations.
辍学率的性别差异:从领域、职业地位和代际角度看辍学率的性别差异
学者的辍学带来了风险,耗尽了宝贵的资源,阻碍了科学界的发展。关于这一问题的知识空白缺乏跨职业状态的一致性,也忽视了其动态性质。为了弥补这一不足,我们分析了 MAG 数据集中 19 个领域超过 2400 万学者的职业轨迹,按领域、职业状态和世代研究了辍学率。首先,我们观察到了出乎意料的高比例 "过客"(transients),在大多数软科学领域,"过客 "占新进学者的比例越来越大,发表的论文超过了 50%。这凸显了为科学界做出贡献的连续性人才(如拥有完整职业生涯的学者)的短缺。其次,我们对不同性别的辍学率进行的调查显示,女性在前 20 年内的辍学率明显较高,包括初级辍学、职业生涯早期辍学和职业生涯中期辍学。值得注意的是,职业生涯早期和中期辍学者的辍学率最低,也最稳定。这些洞察力促使我们开发了一个性别科学职业模型,该模型结合了不同职业状态下学者人数和辍学率的变化。最后,我们跨越四代人的代际分析揭示了辍学率的性别差距正在缩小。在硬科学领域,女性在最初的职业生涯中会遇到挑战,但随着时间的推移,辍学率的性别差距会逐渐缩小。相比之下,软科学领域的性别差距持续时间更长。这些发现在六个子领域都是一致的,对领域评估、性别差异政策以及深入了解各代学者的辍学情况都有意义。
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来源期刊
Journal of Informetrics
Journal of Informetrics Social Sciences-Library and Information Sciences
CiteScore
6.40
自引率
16.20%
发文量
95
期刊介绍: Journal of Informetrics (JOI) publishes rigorous high-quality research on quantitative aspects of information science. The main focus of the journal is on topics in bibliometrics, scientometrics, webometrics, patentometrics, altmetrics and research evaluation. Contributions studying informetric problems using methods from other quantitative fields, such as mathematics, statistics, computer science, economics and econometrics, and network science, are especially encouraged. JOI publishes both theoretical and empirical work. In general, case studies, for instance a bibliometric analysis focusing on a specific research field or a specific country, are not considered suitable for publication in JOI, unless they contain innovative methodological elements.
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