# Invisible Collaborators: Underrepresentation, Research Networks, and Outcomes of Biomedical Researchers

> **NIH NIH R01** · OHIO STATE UNIVERSITY · 2022 · $214,367

## Abstract

This interdisciplinary project will greatly enhance our understanding of the scientific contributions of
 women, members of racial and ethnic under represented minorities (URMs), and research staff and inform
science and scientific workforce policy regarding those groups. Our work is made possible through the
 use of unique new data from the UMETRICS project and on scores on NIH applications.
The UMETRICS data allow us to identify all people employed on research projects, not just those who are
listed as authors on publications. With these powerful data, we will provide new perspectives on the
positions of women and URMs in the network of scientific collaborations. This is particularly important
because existing evidence indicates that women and members of underrepresented racial and ethnic
groups are disadvantaged in terms of the authorship credit they receive for their contributions to science.
Because our UMETRICS data make it possible to identify all people working on projects, we can study for
the first time the extent to which women and URMs are even included on publications controlling for the
role played and the amount of effort devoted to projects. Our analysis of staff is also timely as NIH has
repeatedly considered increasing support for staff scientists. If staff are less likely to appear as coauthors
on articles than faculty, postdocs, or perhaps graduate students, it becomes critically important for policy
to be able to find other ways to quantify their contribution to science.
There is also mixed evidence that women trainees perform better under the mentorship of women
mentors. In addition to coming to mixed conclusions, existing work on the benefits of a gender match
between trainees and mentors is descriptive rather than causal. We will use unique large-scale data on
scores on NIH fellowship applications to estimate the causal effect of a gender match on women trainees.
RELEVANCE (See instructions):
 Policy makers seek to ensure that our best and brightest regardless of gender, race, and ethnicity are
 represented in science. But, unfortunately, it is often hardest to quantify the relative contribution to
 science of members of underrepresented groups and research staff. This project will use new data to
 better quantify the credit received by women, underrepresented racial and ethnic minorities, and research
 staff in science and provide policy-relevant guidance for improving their training and funding.

## Key facts

- **NIH application ID:** 10450882
- **Project number:** 5R01GM140281-03
- **Recipient organization:** OHIO STATE UNIVERSITY
- **Principal Investigator:** Jason David Owen-Smith
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $214,367
- **Award type:** 5
- **Project period:** 2020-08-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10450882

## Citation

> US National Institutes of Health, RePORTER application 10450882, Invisible Collaborators: Underrepresentation, Research Networks, and Outcomes of Biomedical Researchers (5R01GM140281-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10450882. Licensed CC0.

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