Abstract

Motivated by recent criticisms of the low reliability and high costs of science funding allocation by grant peer review, the paper investigates the alternative of funding science by lottery, and more generally the possible introduction of a formal random element in the funding process. At first it may seem that randomness will lower expected efficiency, by allocating funds to less meritorious projects. By focusing on the notion that we want funded research projects to ultimately make our lives better, and the observation that the causal effect of research projects is subject to change over time, the paper argues that the introduction of randomness can counteract a bias towards the familiar present in grant peer review, and thus increase the overall efficiency of science funding. The time-dependant nature of scientific merit is exemplified by the historical processes leading to the discovery of the structure of DNA. The argument regarding the relative effectiveness of random allocation is supported by a computer simulation of different funding mechanisms on a hypothetical dynamic epistemic landscape.

Keywords

Science funding Grant peer review Random allocation Research funds Scientific merit 

References

  1. Allen, G. E. (1975). Life science in the twentieth century (History of science). New York: Wiley.Google Scholar
  2. Avin, S. (2014). Breaking the grant cycle: On the rational allocation of public resources to scientific research projects. PhD thesis, University of Cambridge, Cambridge, https://www.repository.cam.ac.uk/handle/1810/247434
  3. Bush, V. (1945). Science, the endless frontier: A report to the President. U.S. Government printing office, Washington.Google Scholar
  4. Dinges, M. (2005). The Austrian science fund: Ex post evaluation and performance of FWF funded research projects. Vienna: Institute of Technology and Regional Policy.Google Scholar
  5. Geuna, A., Salter, A. J., & Steinmueller, W. E. (2003). Science and innovation: Rethinking the rationales for funding and governance. Northampton: Edward Elgar Publishing.CrossRefGoogle Scholar
  6. Graves, N., Barnett, A. G., & Clarke, P. (2011). Funding grant proposals for scientific research: Retrospective analysis of scores by members of grant review panel. BMJ, 343. doi:10.1136/bmj.d4797.Google Scholar
  7. Greenberg, D. S. (1998). Chance and grants. The Lancet, 351(9103), 686. doi:10.1016/S0140-6736(05)78485-3.CrossRefGoogle Scholar
  8. Herbert, D. L., Barnett, A. G., Clarke, P., et al. (2013). On the time spent preparing grant proposals: An observational study of Australian researchers. BMJ Open, 3, e002800. doi:10.1136/bmjopen-2013-002800.CrossRefGoogle Scholar
  9. Kitcher, P. (2011). Science in a democratic society. Amherst: Prometheus Books.Google Scholar
  10. NIH. (2013). NIH grants policy statement. Accessed Nov 9, 2013, http://grants.nih.gov/grants/policy/nihgps_2013/
  11. NSF. (2013). Grant proposal guide. Accessed Nov 9, 2013, http://www.nsf.gov/publications/pub_summ.jsp?ods_key=gpg
  12. Polanyi, M. (1962). The republic of science: Its political and economic theory. Minerva, 1, 54–73.CrossRefGoogle Scholar
  13. Popper, K. (1959). The logic of scientific discovery. London: Hutchinson.Google Scholar
  14. Strevens, M. (2003). The role of the priority rule in science. The Journal of Philosophy, 100(2), 55–79.CrossRefGoogle Scholar
  15. Weisberg, M., Muldoon, R. (2009). Epistemic landscapes and the division of cognitive labor. Philosophy of Science, 76(2), 225–252. http://www.jstor.org/stable/10.1086/644786

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of History and Philosophy of ScienceUniversity of CambridgeCambridgeUK

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