Scientometrics

, Volume 110, Issue 1, pp 521–528 | Cite as

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

  • Johan Bollen
  • David Crandall
  • Damion Junk
  • Ying Ding
  • Katy Börner
Article

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.

Keywords

Bibliometrics Funding Peer review PageRank Collective intelligence 

Supplementary material

11192_2016_2110_MOESM1_ESM.pdf (127 kb)
Supplementary material 1 (pdf 126 KB)

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Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2016

Authors and Affiliations

  • Johan Bollen
    • 1
    • 3
    • 4
  • David Crandall
    • 1
    • 4
  • Damion Junk
    • 1
  • Ying Ding
    • 1
    • 3
  • Katy Börner
    • 1
    • 2
    • 3
    • 4
  1. 1.School of Informatics and ComputingIndiana UniversityBloomingtonUSA
  2. 2.Department of Information and Library ScienceIndiana UniversityBloomingtonUSA
  3. 3.Indiana University Network InstituteIndiana UniversityBloomingtonUSA
  4. 4.Center for Complex Network and Systems ResearchIndiana UniversityBloomingtonUSA

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