Collaborative Research: Social Dynamics of Knowledge Transfer Through Scientific Mentorship and Publication

合作研究：通过科学指导和出版进行知识转移的社会动力

• 批准号: 1933803
• 负责人: Daniel Acuna
• 金额: $ 17.65万
• 依托单位: Syracuse University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1933803&HistoricalAwards=false
• 关键词: Collaborative; Research; Social; Dynamics; Knowledge

Mentorship plays a critical role in the careers of scientific researchers. Most researchers spend several years training under just one or two graduate and/or postdoctoral mentors, suggesting that these few relationships can have a large impact on scientific careers. Mentorship can provide both direct intellectual benefits to the trainee, through the learning of new skills and concepts, and indirect social benefits, through engagement with the social network of the mentor. Given the importance of mentorship in scientific career development, this aspect of training may play an important role in determining access of underrepresented groups to scientific careers. The purpose of this study is to characterize the impact of demographic variables--such as gender, ethnicity and socio-economic background--on the outcome of scientific training.Networks of mentors and trainees can be represented by a directional graph resembling a traditional family tree. This project develops a large crowdsourced database of academic mentorship relationships, and links that data to databases that measure scientific productivity (publications and grants) and demographic variables. Graph theoretic and semantic tools will be used to determine if and how demographic variables, associated with both of the mentor and trainee, impact scientific productivity. A preliminary analysis of gender replicates previous reports of bias toward representation male researchers, especially at more senior career stages. Accurately modeling effects of demographic variables requires accounting for other variables that impact scientific productivity metrics, namely differences between fields and long-term temporal trends. This project will use semantic analysis of publication data to develop the concept of the "intellectual neighborhood" of mentors. and incorporate this into the modeling of career outcomes. Data will be made open-access for general use by the public, providing a new resource for studying the dynamics of research fields.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.

导师制在科研人员的职业生涯中起着至关重要的作用。大多数研究人员花了几年时间在一两个研究生和/或博士后导师的指导下进行培训，这表明这几种关系可以对科学事业产生很大的影响。导师制既可以通过学习新技能和概念为受训者提供直接的智力益处，也可以通过与导师的社会网络接触来提供间接的社会益处。鉴于导师制在科学职业发展中的重要性，这方面的培训可能在确定代表性不足的群体是否有机会从事科学职业方面发挥重要作用。本研究的目的是描述人口变量-如性别、种族和社会经济背景-对科学培训成果的影响，导师和受训者网络可用类似传统家谱的方向图表示。该项目开发了一个关于学术导师关系的大型众包数据库，并将该数据与衡量科学生产力（出版物和赠款）和人口变量的数据库联系起来。图论和语义工具将用于确定是否以及如何人口统计变量，与导师和受训者，影响科学生产力。性别的初步分析复制了以前的报告偏向代表男性研究人员，特别是在更高级的职业生涯阶段。要准确地模拟人口变量的影响，需要考虑影响科学生产力指标的其他变量，即领域之间的差异和长期的时间趋势。这个项目将使用出版物数据的语义分析来开发导师的“知识社区”的概念。并将其纳入职业成果的建模中。该奖项反映了NSF的法定使命，通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

The impact of heterogeneous shared leadership in scientific teams

科学团队中异质共享领导的影响

• DOI: 10.1016/j.ipm.2023.103542
• 发表时间: 2024
• 期刊: Information Processing & Management
• 影响因子: 8.6
• 作者: Xu, Huimin;Liu, Meijun;Bu, Yi;Sun, Shujing;Zhang, Yi;Zhang, Chenwei;Acuna, Daniel E.;Gray, Steven;Meyer, Eric;Ding, Ying
• 通讯作者: Ding, Ying