An efficient system to fund science: from proposal review to peer-to-peer distributions
- 2.2k Downloads
This paper presents a novel model of science funding that exploits the wisdom of the scientific crowd. Each researcher receives an equal, unconditional part of all available science funding on a yearly basis, but is required to individually donate to other scientists a given fraction of all they receive. Science funding thus moves from one scientist to the next in such a way that scientists who receive many donations must also redistribute the most. As the funding circulates through the scientific community it is mathematically expected to converge on a funding distribution favored by the entire scientific community. This is achieved without any proposal submissions or reviews. The model furthermore funds scientists instead of projects, reducing much of the overhead and bias of the present grant peer review system. Model validation using large-scale citation data and funding records over the past 20 years show that the proposed model could yield funding distributions that are similar to those of the NSF and NIH, and the model could potentially be more fair and more equitable. We discuss possible extensions of this approach as well as science policy implications.
KeywordsBibliometrics Funding Peer review PageRank Collective intelligence
The authors acknowledge the generous support of the National Science Foundation under Grant SBE #0914939 and SMA #1636636, the National Institutes of Health under Grants #P01AG039347 and #U01GM098959, and the Andrew W. Mellon Foundation. We also thank the Los Alamos National Laboratory Research Library, the LANL Digital Library Prototyping and Research Team, Thomson-Reuters, and the Cyberinfrastructure for Network Science Center at Indiana University for furnishing the data employed in this analysis. The authors thank Marten Scheffer (Wageningen University) for his extensive feedback on our work and his support of in vivo implementations.
Compliance with ethical standards
The authors declare that they have no competing financial interest.
- Azoulay, P., Zivin, J. S. G., & Manso, G. (2012). NIH peer review: Challenges and avenues for reform. National Bureau of Economic Research Working Paper 18116.Google Scholar
- Editor (2010). Calm in a crisis. Nature, 468, 1002.Google Scholar
- Editor (April 25 2011). Dr. No money: The broken science funding system. Scientific American.Google Scholar
- Editorial (2013). Twice the price. Nature, 493(7434).Google Scholar
- F.S.C. of the Federal Demonstration Partnership (2007). A profile of federal grant administrative burden among federal demonstration partnership faculty. Tech. rep. http://www.iscintelligence.com/archivos_subidos/usfacultyburden_5.pdf.
- Geard, N., & Noble, J. (2010) Modelling academic research funding as a resource allocation problem. In 3rd world congress on social simulation.Google Scholar
- National Science Foundation (2009). Fiscal year 2010 budget request to congress.Google Scholar
- National Science Foundation (2015). Fy2015 agency financial report. NSF report nsf16002. http://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf16002.
- Rowe, G. L., Burgoon, S., Burgoon, J., Ke, W., & Börner, K. (2007). The scholarly database and its utility for scientometrics research. In Proceedings of the 11th international conference on scientometrics and informetrics (pp. 457–462).Google Scholar
- Southwick, F. (2012). Academia suppresses creativity. The Scientist.Google Scholar