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Task specialization across research careers
bioRxiv - Scientific Communication and Education Pub Date : 2020-11-12 , DOI: 10.1101/2020.07.01.181669
Nicolas Robinson-Garcia , Rodrigo Costas , Cassidy R. Sugimoto , Vincent Larivière , Gabriela F. Nane

Research careers are typically envisioned as a single path in which a scientist starts as a member of a team working under the guidance of one or more experienced scientists and, if they are successful, ends with the individual leading their own research group and training future generations of scientists. Here we study the author contribution statements of published research papers in order to explore possible biases and disparities in career trajectories in science. We used Bayesian networks to train a prediction model based on a dataset of 70,694 publications from PLoS journals, which included 347,136 distinct authors and their associated contribution statements. This model was used to predict the contributions of 222,925 authors in 6,236,239 publications, and to apply a robust archetypal analysis to profile scientists across four career stages: junior, early-career, mid-career and late-career. All three of the archetypes we found - leader, specialized, and supporting - were encountered for early-career and mid-career researchers. Junior researchers displayed only two archetypes (specialized, and supporting), as did late-career researchers (leader and supporting). Scientists assigned to the leader and specialized archetypes tended to have longer careers than those assigned to the supporting archetype. We also observed consistent gender bias at all stages: the majority of male scientists belonged to the leader archetype, while the larger proportion of women belonged to the specialized archetype, especially for early-career and mid-career researchers.

中文翻译:

跨研究职业的任务专业化

通常将研究生涯设想为一条单一的道路,在此道路上,科学家将以团队成员的身份在一个或多个经验丰富的科学家的指导下开始工作,如果成功,则以个人领导自己的研究小组并培训后代为终点的科学家。在这里,我们研究已发表研究论文的作者贡献陈述,以探索科学职业轨迹中可能存在的偏见和差距。我们使用贝叶斯网络来训练基于PLoS期刊的70694种出版物的数据集的预测模型,其中包括347136名不同的作者及其相关的贡献陈述。该模型用于预测6,236,239种出版物中的222,925位作者的贡献,并应用强大的原型分析来概述四个职业阶段的科学家:大三,职业早期,职业中期和职业后期。我们发现的所有三种原型-领导者,专业者和支持者-都是职业初期和中期的研究人员。初级研究人员仅显示两种原型(专业化和辅助性),后期职业研究人员(领导和辅助性)也是如此。分配给领导者和专门原型的科学家的职业生涯往往比分配给支持原型的科学家更长。我们还观察到了各个阶段的性别偏见:大多数男性科学家属于领导者原型,而较大比例的女性属于专门原型,特别是对于职业生涯早期和中期的研究人员。和支持-从事职业早期和中期的研究人员。初级研究人员仅显示两种原型(专业化和辅助性),后期职业研究人员(领导和辅助性)也是如此。分配给领导者和专门原型的科学家的职业生涯往往比分配给支持原型的科学家更长。我们还观察到各个阶段的性别偏见一致:大多数男性科学家属于领导者原型,而较大比例的女性属于专门原型,特别是对于职业生涯早期和中期的研究人员。和支持-从事职业早期和中期的研究人员。初级研究人员仅显示两种原型(专业化和辅助性),后期职业研究人员(领导和辅助性)也是如此。分配给领导者和专门原型的科学家的职业生涯往往比分配给支持原型的科学家更长。我们还观察到了各个阶段的性别偏见:大多数男性科学家属于领导者原型,而较大比例的女性属于专门原型,特别是对于职业生涯早期和中期的研究人员。分配给领导者和专门原型的科学家的职业生涯往往比分配给支持原型的科学家更长。我们还观察到了各个阶段的性别偏见:大多数男性科学家属于领导者原型,而较大比例的女性属于专门原型,特别是对于职业生涯早期和中期的研究人员。分配给领导者和专门原型的科学家的职业生涯往往比分配给支持原型的科学家更长。我们还观察到了各个阶段的性别偏见:大多数男性科学家属于领导者原型,而较大比例的女性属于专门原型,特别是对于职业生涯早期和中期的研究人员。
更新日期:2020-11-12
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