Early-career setback and future career impact
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Abstract (arXiv)
Setbacks are an integral part of a scientific career, yet little is known about whether an early-career setback may augment or hamper an individual's future career impact. Here we examine junior scientists applying for U.S. National Institutes of Health (NIH) R01 grants. By focusing on grant proposals that fell just below and just above the funding threshold, we compare "near-miss" with "near-win" individuals to examine longer-term career outcomes. Our analyses reveal that an early-career near miss has powerful, opposing effects. On one hand, it significantly increases attrition, with one near miss predicting more than a 10% chance of disappearing permanently from the NIH system. Yet, despite an early setback, individuals with near misses systematically outperformed those with near wins in the longer run, as their publications in the next ten years garnered substantially higher impact. We further find that this performance advantage seems to go beyond a screening mechanism, whereby a more selected fraction of near-miss applicants remained than the near winners, suggesting that early-career setback appears to cause a performance improvement among those who persevere. Overall, the findings are consistent with the concept that "what doesn't kill me makes me stronger." Whereas science is often viewed as a setting where early success begets future success, our findings unveil an intimate yet previously unknown relationship where early-career setback can become a marker for future achievement, which may have broad implications for identifying, training and nurturing junior scientists whose career will have lasting impact.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 Mar 2019.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 1; 2025: 2; 2026: 3.
8 papers.
- 2025Dissecting Submission Limit in Desk-Rejections: A Mathematical Analysis of Fairness in AI Conference Policiescited by 9
- 2024Promotional Language and the Adoption of Innovative Ideas in Sciencecited by 8
- 2023China and the U.S. produce more impactful AI research when collaborating togethercited by 6
- 2025AI-Driven Automation Can Become the Foundation of Next-Era Science of Science Researchcited by 3
- 2021On predicting research grants productivitycited by 1
- 2026The Rise of Large Language Models and the Direction and Impact of US Federal Research Fundingcited by 1
- 2026Bridging Through Absence: How Comeback Researchers Bridge Knowledge Gaps Through Structural Re-emergencecited by 0
- 2026Science Utopia? Closed-Loop LLM Simulation of Academic Research Ecosystemscited by 0
- 2026Science Utopia? Closed-Loop LLM Simulation of Academic Research Ecosystems1 Oct 2026
- 2026Bridging Through Absence: How Comeback Researchers Bridge Knowledge Gaps Through Structural Re-emergence25 Feb 2026
- 2026The Rise of Large Language Models and the Direction and Impact of US Federal Research Funding21 Jan 2026
- 2025AI-Driven Automation Can Become the Foundation of Next-Era Science of Science Research17 May 2025
- 2025Dissecting Submission Limit in Desk-Rejections: A Mathematical Analysis of Fairness in AI Conference Policies2 Feb 2025
- 2024Promotional Language and the Adoption of Innovative Ideas in Science4 Jun 2024
- 2023China and the U.S. produce more impactful AI research when collaborating together21 Apr 2023
- 2021On predicting research grants productivity20 Jun 2021