| NSF Org: |
SMA SBE Office of Multidisciplinary Activities |
| Recipient: |
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| Initial Amendment Date: | July 31, 2019 |
| Latest Amendment Date: | July 31, 2019 |
| Award Number: | 1933803 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Mary Feeney
SMA SBE Office of Multidisciplinary Activities SBE Directorate for Social, Behavioral and Economic Sciences |
| Start Date: | October 1, 2019 |
| End Date: | September 30, 2023 (Estimated) |
| Total Intended Award Amount: | $176,475.00 |
| Total Awarded Amount to Date: | $176,475.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
900 S CROUSE AVE SYRACUSE NY US 13244-4407 (315)443-2807 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
312 Hinds Hall Syracuse NY US 13244-1190 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | SciSIP-Sci of Sci Innov Policy |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.075 |
ABSTRACT
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.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Our findings have significantly advanced the understanding of how these demographic factors interplay to affect academic productivity and career trajectories. Notably, one of our studies uncovered patterns of gender bias in mentorship, particularly at senior career stages, and identified critical factors that influence the likelihood of trainees pursuing academic research careers. These insights are backed by comprehensive databases developed during the project, incorporating previous work from the Eileen.io project and extending the scope of available datasets for future research.
Broader impact
The broader impacts of this project are many. First, it has enhanced our understanding of the role mentorship plays in shaping scientific careers, especially for underrepresented groups. The insights gained from this study have potential implications for developing policies and practices that promote equity in scientific training.
Additionally, the project has produced valuable resources for the scientific community, including the Academic Family Tree (AFT) database, which integrates mentorship data with publication records. This integration facilitates a deeper analysis of mentorship networks and research topics and will serve as a novel resource for future studies.
The project also emphasized capacity building through the organization of two Science of Science Summer Schools in 2021 and 2022. These events brought together over 100 students from around the globe, providing them with training in advanced research methodologies and exposure to the frontiers of the science of science research.
Dissemination and Publications
The research team has actively disseminated the findings through various channels. Several manuscripts detailing the project’s results have been submitted and published in peer-reviewed journals, the materials of the summer school are available online, and the software and datasets are also available through NSF Public Access Repository.
Science of Science Summer School
- Webiste: https://s4.scienceofscience.org
MENTORSHIP dataset and software
- Publication: https://www.nature.com/articles/s41597-022-01578-x
- Dataset: https://doi.org/10.5281/zenodo.4917086
- Software: Demographicx Python Package https://doi.org/10.5281/zenodo.4898367
Last Modified: 04/23/2024
Modified by: Daniel E Acuna
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