A dataset of mentorship in bioscience with semantic and demographic estimations.

ABSTRACT: Mentorship in science is crucial for topic choice, career decisions, and the success of mentees and mentors. Typically, researchers who study mentorship use article co-authorship and doctoral dissertation datasets. However, available datasets of this type focus on narrow selections of fields and miss out on early career and non-publication-related interactions. Here, we describe Mentorship, a crowdsourced dataset of 743176 mentorship relationships among 738989 scientists primarily in biosciences that avoids these shortcomings. Our dataset enriches the Academic Family Tree project by adding publication data from the Microsoft Academic Graph and "semantic" representations of research using deep learning content analysis. Because gender and race have become critical dimensions when analyzing

SUBMITTER: Ke Q 

PROVIDER: S-EPMC9345966 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature