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Resilience of science after austerity.
Ye Sun1, Athen Ma2, Georg von Graevenitz3
1School of Mathematics, Southeast University, Nanjing, Jiangsu 210096, China.
PNAS Nexus
|June 3, 2025
Summary
Austerity measures impacted science funding, with highly competitive universities gaining income while lower-ranked ones lost it. However, less competitive universities showed surprising resilience and increased grant applications after austerity was relaxed.
Area of Science:
- Complexity science
- Bibliometrics
- Science policy
Background:
- Governments implemented austerity measures starting in 2009, leading to science funding restrictions and increased competition.
- The study examines the impact of austerity on university grant income and research competitiveness.
Purpose of the Study:
- To analyze the allocation of science funding across UK universities during austerity periods.
- To develop and validate a network-based measure of research competitiveness.
- To assess the resilience of scientific research to austerity measures.
Main Methods:
- Utilized a complexity science approach, employing a bipartite network of universities and scientific subjects to measure research competitiveness.
- Analyzed a dataset of 43,430 UK-funded grants awarded between 2006 and 2020.
- Exploited the 2015 UK general election as a natural experiment to study the relaxation of austerity.
Main Results:
- Highly competitive universities increased their grant income under austerity, whereas less competitive universities experienced a decline.
- Less competitive universities demonstrated high resilience, with significant growth in grant applications and income after the unexpected relaxation of austerity in 2015.
- The network-based competitiveness measure proved to be a more effective proxy for research competitiveness than aggregate grant income.
Conclusions:
- Research competitiveness, measured through network analysis, significantly influences university grant income during periods of austerity.
- Less competitive institutions exhibited unexpected resilience, indicating a potential for recovery and growth post-austerity.
- The findings underscore the utility of complexity science methods for understanding science funding dynamics and research competitiveness.
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