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Research funding: past performance is a stronger predictor of future scientific output than reviewer scores

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  • Győrffy, Balázs
  • Herman, Péter
  • Szabó, István

Abstract

Scientific grants are awarded almost exclusively on the basis of an independent peer review of a proposal submitted by the principal investigator (PI). The writing and reviewing of these applications consumes a significant amount of researchers’ time. Here, we perform a large-scale performance evaluation of review-based grant allocation via analysis of the grant proposals submitted to the Hungarian Scientific Research Fund.

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  • Győrffy, Balázs & Herman, Péter & Szabó, István, 2020. "Research funding: past performance is a stronger predictor of future scientific output than reviewer scores," Journal of Informetrics, Elsevier, vol. 14(3).
  • Handle: RePEc:eee:infome:v:14:y:2020:i:3:s1751157719303694
    DOI: 10.1016/j.joi.2020.101050
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    References listed on IDEAS

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    Cited by:

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    2. Helen Peterson & Liisa Husu, 2023. "Online panel work through a gender lens: implications of digital peer review meetings," Science and Public Policy, Oxford University Press, vol. 50(3), pages 371-381.
    3. Shahd Al-Janabi & Lee Wei Lim & Luca Aquili, 2021. "Development of a tool to accurately predict UK REF funding allocation," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 8049-8062, September.
    4. Wen Lou & Jiangen He & Lingxin Zhang & Zhijie Zhu & Yongjun Zhu, 2023. "Support behind the scenes: the relationship between acknowledgement, coauthor, and citation in Nobel articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5767-5790, October.
    5. Fernandez Martinez, Roberto & Lostado Lorza, Ruben & Santos Delgado, Ana Alexandra & Piedra, Nelson, 2021. "Use of classification trees and rule-based models to optimize the funding assignment to research projects: A case study of UTPL," Journal of Informetrics, Elsevier, vol. 15(1).
    6. Marton Demeter & Agnes Jele & Zsolt Balázs Major, 2022. "The model of maximum productivity for research universities SciVal author ranks, productivity, university rankings, and their implications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4335-4361, August.
    7. Buehling, Kilian, 2021. "Changing research topic trends as an effect of publication rankings – The case of German economists and the Handelsblatt Ranking," Journal of Informetrics, Elsevier, vol. 15(3).
    8. Manuel Goyanes & Márton Demeter & Aurea Grané & Tamás Tóth & Homero Gil Zúñiga, 2023. "Research patterns in communication (2009–2019): testing female representation and productivity differences, within the most cited authors and the field," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 137-156, January.
    9. Jinyang Dong & Jiamou Liu & Tiezhong Liu, 2021. "The impact of top scientists on the community development of basic research directed by government funding: evidence from program 973 in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8561-8579, October.

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    More about this item

    Keywords

    Funding; Reviewer assessments; Basic research; Publications; Scientific output; Q1; H-index; Internationalization;
    All these keywords.

    JEL classification:

    • Q1 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture

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