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An efficient system to fund science: from proposal review to peer-to-peer distributions

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Abstract

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.

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Acknowledgments

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.

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Correspondence to Johan Bollen.

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Bollen, J., Crandall, D., Junk, D. et al. An efficient system to fund science: from proposal review to peer-to-peer distributions. Scientometrics 110, 521–528 (2017). https://doi.org/10.1007/s11192-016-2110-3

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