Teamwork has become more important in recent decades. We show that larger teams generate an unintended side effect: individuals who finish their PhD when the average team in their field is larger have worse career prospects. Our analysis combines data on career outcomes from the Survey of Doctorate Recipients with publication data that measures team size from ISI Web of Science. As average team size in a field increased over time, junior academic scientists became less likely to secure research funding or obtain tenure and were more likely to leave academia relative to their older counterparts. The team size effect can fully account for the observed decline in tenure prospects in academic science. The rise in team size was not associated with the end of mandatory retirement. However, the doubling of the NIH budget was associated with a significant increase in team size. Our results demonstrate that academic science has not adjusted its reward structure, which is largely individual, in response to team science. Failing to address these concerns means a significant loss as junior scientists exit after a costly and specialized education in science. 
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                            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 mentorship and disparities in science, we also provide estimations of these factors. We perform extensive validations of the profile–publication matching, semantic content, and demographic inferences, which mostly cover neuroscience and biomedical sciences. We anticipate this dataset will spur the study of mentorship in science and deepen our understanding of its role in scientists’ career outcomes. 
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                            - PAR ID:
- 10381689
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- Scientific Data
- Volume:
- 9
- Issue:
- 1
- ISSN:
- 2052-4463
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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