EAGER: The impact of mentorship networks on academic research

EAGER：导师网络对学术研究的影响

• 批准号: 1646635
• 负责人: Stephen David
• 金额: $ 26.03万
• 依托单位: Oregon Health & Science University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-11-01 至 2019-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1646635&HistoricalAwards=false
• 关键词: EAGER; impact; mentorship; networks; academic

Mentorship provides an important influence on how scientific researchers develop professionally. Most researchers spend several years training under just one or two graduate and/or postdoctoral mentors, suggesting that this small number of relationships can have large impact on subsequent careers. Mentorship can have 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. Networks of mentors and trainees can be represented by a directional graph resembling a traditional family tree. This project develops a large database of academic mentorship relationships and tools for analyzing the impact of mentorship on scientific careers. Development of this database addresses the mission of the Science of Science & Innovation Policy program. The data will be made open-access for general use by the public, providing a new resource for studying the dynamics of academic research fields. More generally, the Academic Family Tree represents a successful crowdsourcing project and provides an example for other efforts to engage the public in scientific research projects.This project uses semantic and graph theoretic analyses to characterize the impact of mentorship networks on professional success and on the evolution of research fields. This project uses crowdsourcing to expand the Academic Family Tree, a public, web-based database of formal mentoring relationships (doctoral and postdoctoral) across all fields of academic research. Researchers in the mentorship database are linked to publication metadata in multiple publication databases and to funding data in the Federal RePORTER database. Semantic and graph theoretic analyses are used to determine what features of the mentorship network influence the subsequent careers of trainees. Focusing on trainees with at least two mentors, these analyses evaluate direct intellectual impact of mentor expertise, measured by latent semantic analysis of publications, and indirect social impact, measured by the similarity of the lineage of the two mentors in the larger academic genealogy. Two measures of trainees' professional success are considered: the number of trainees they themselves mentor and their ability to obtain research funding.

导师制对科研人员的专业发展具有重要影响。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，这表明这种少量的关系可能会对随后的职业生涯产生很大的影响。导师制既可以通过学习新技能和概念为受训者带来直接的智力效益，也可以通过与导师的社会网络接触而带来间接的社会效益。导师和学员的网络可以用类似于传统家谱的方向图来表示。该项目开发了一个大型的学术导师关系数据库和分析导师对科学事业的影响的工具。该数据库的开发解决了科学创新政策计划的科学的使命。这些数据将开放供公众使用，为研究学术研究领域的动态提供新的资源。更一般地说，学术家谱代表了一个成功的众包项目，并为其他让公众参与科学研究项目的努力提供了一个例子。该项目使用语义和图论分析来描述导师网络对专业成功和发展的影响。研究领域。该项目利用众包扩大学术家谱，这是一个公共的、基于网络的数据库，记录了所有学术研究领域的正式导师关系（博士和博士后）。导师数据库中的研究人员链接到多个出版物数据库中的出版物元数据和联邦RePORTER数据库中的资助数据。语义和图论分析用于确定导师网络的哪些功能会影响受训者随后的职业生涯。专注于学员与至少两个导师，这些分析评估导师的专业知识的直接智力影响，测量出版物的潜在语义分析，和间接的社会影响，测量的两个导师在更大的学术谱系的血统的相似性。学员的专业成功的两个措施被认为是：学员的人数，他们自己的导师和他们获得研究资金的能力。