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Selection of research fellowship recipients by committee peer review. Reliability, fairness and predictive validity of Board of Trustees' decisions

Citations

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Cited by:

  1. Mario Paolucci & Francisco Grimaldo, 2014. "Mechanism change in a simulation of peer review: from junk support to elitism," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(3), pages 663-688, June.
  2. Banal-Estañol, Albert & Macho-Stadler, Inés & Pérez-Castrillo, David, 2019. "Evaluation in research funding agencies: Are structurally diverse teams biased against?," Research Policy, Elsevier, vol. 48(7), pages 1823-1840.
  3. Lutz Bornmann & Julian N. Marewski, 2019. "Heuristics as conceptual lens for understanding and studying the usage of bibliometrics in research evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 419-459, August.
  4. Alexandre Rodrigues Oliveira & Carlos Fernando Mello, 2016. "Importance and susceptibility of scientific productivity indicators: two sides of the same coin," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 697-722, November.
  5. Ulf Sandström & Martin Hällsten, 2008. "Persistent nepotism in peer-review," Scientometrics, Springer;Akadémiai Kiadó, vol. 74(2), pages 175-189, February.
  6. Marsh, Herbert W. & Jayasinghe, Upali W. & Bond, Nigel W., 2011. "Gender differences in peer reviews of grant applications: A substantive-methodological synergy in support of the null hypothesis model," Journal of Informetrics, Elsevier, vol. 5(1), pages 167-180.
  7. Hans-Dieter Daniel, 2019. "Lutz Bornmann: Recipient of the 2019 Derek John de Solla Price Medal," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1235-1238, December.
  8. Bornmann, Lutz & Mutz, Rüdiger & Daniel, Hans-Dieter, 2008. "How to detect indications of potential sources of bias in peer review: A generalized latent variable modeling approach exemplified by a gender study," Journal of Informetrics, Elsevier, vol. 2(4), pages 280-287.
  9. Bornmann, Lutz & Mutz, Rüdiger & Daniel, Hans-Dieter, 2007. "Gender differences in grant peer review: A meta-analysis," Journal of Informetrics, Elsevier, vol. 1(3), pages 226-238.
  10. Vieira, Elizabeth S. & Cabral, José A.S. & Gomes, José A.N.F., 2014. "How good is a model based on bibliometric indicators in predicting the final decisions made by peers?," Journal of Informetrics, Elsevier, vol. 8(2), pages 390-405.
  11. Groen-Xu, Moqi & Bös, Gregor & Teixeira, Pedro A. & Voigt, Thomas & Knapp, Bernhard, 2023. "Short-term incentives of research evaluations: Evidence from the UK Research Excellence Framework," Research Policy, Elsevier, vol. 52(6).
  12. Benda, Wim G.G. & Engels, Tim C.E., 2011. "The predictive validity of peer review: A selective review of the judgmental forecasting qualities of peers, and implications for innovation in science," International Journal of Forecasting, Elsevier, vol. 27(1), pages 166-182.
  13. Azzurra Ragone & Katsiaryna Mirylenka & Fabio Casati & Maurizio Marchese, 2013. "On peer review in computer science: analysis of its effectiveness and suggestions for improvement," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(2), pages 317-356, November.
  14. Bornmann, Lutz & Daniel, Hans-Dieter, 2007. "Gatekeepers of science—Effects of external reviewers’ attributes on the assessments of fellowship applications," Journal of Informetrics, Elsevier, vol. 1(1), pages 83-91.
  15. Benda, Wim G.G. & Engels, Tim C.E., 2011. "The predictive validity of peer review: A selective review of the judgmental forecasting qualities of peers, and implications for innovation in science," International Journal of Forecasting, Elsevier, vol. 27(1), pages 166-182, January.
  16. Andrea Bonaccorsi & Luca Secondi, 2017. "The determinants of research performance in European universities: a large scale multilevel analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1147-1178, September.
  17. Albert Banal-Estañol & Qianshuo Liu & Inés Macho-Stadler & David Pérez-Castrillo, 2021. "Similar-to-me Effects in the Grant Application Process: Applicants, Panelists, and the Likelihood of Obtaining Funds," Working Papers 1289, Barcelona School of Economics.
  18. Bornmann, Lutz & Mutz, Rüdiger & Daniel, Hans-Dieter, 2008. "Latent Markov modeling applied to grant peer review," Journal of Informetrics, Elsevier, vol. 2(3), pages 217-228.
  19. Jens Jirschitzka & Aileen Oeberst & Richard Göllner & Ulrike Cress, 2017. "Inter-rater reliability and validity of peer reviews in an interdisciplinary field," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 1059-1092, November.
  20. Stephen A Gallo & Joanne H Sullivan & Scott R Glisson, 2016. "The Influence of Peer Reviewer Expertise on the Evaluation of Research Funding Applications," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-18, October.
  21. Esposti, Roberto & Materia, Valentina, 2015. "The determinants of the public R&D cofinancing rate An empirical assessment on agricultural research," 2015 Conference, August 9-14, 2015, Milan, Italy 211624, International Association of Agricultural Economists.
  22. Rüdiger Mutz & Lutz Bornmann & Hans-Dieter Daniel, 2015. "Testing for the fairness and predictive validity of research funding decisions: A multilevel multiple imputation for missing data approach using ex-ante and ex-post peer evaluation data from the Austr," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(11), pages 2321-2339, November.
  23. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
  24. Qurat-ul Ain & Hira Riaz & Muhammad Tanvir Afzal, 2019. "Evaluation of h-index and its citation intensity based variants in the field of mathematics," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 187-211, April.
  25. Stefan Hornbostel & Susan Böhmer & Bernd Klingsporn & Jörg Neufeld & Markus Ins, 2009. "Funding of young scientist and scientific excellence," Scientometrics, Springer;Akadémiai Kiadó, vol. 79(1), pages 171-190, April.
  26. Bornmann, Lutz & Daniel, Hans-Dieter, 2007. "Convergent validation of peer review decisions using the h index," Journal of Informetrics, Elsevier, vol. 1(3), pages 204-213.
  27. Amin Mazloumian, 2012. "Predicting Scholars' Scientific Impact," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-5, November.
  28. Materia, V.C. & Pascucci, S. & Kolympiris, C., 2015. "Understanding the selection processes of public research projects in agriculture: The role of scientific merit," Food Policy, Elsevier, vol. 56(C), pages 87-99.
  29. Flaminio Squazzoni & Károly Takács, 2011. "Social Simulation That 'Peers into Peer Review'," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 14(4), pages 1-3.
  30. Kevin W. Boyack & Caleb Smith & Richard Klavans, 2018. "Toward predicting research proposal success," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 449-461, February.
  31. Martin Reinhart, 2009. "Peer review of grant applications in biology and medicine. Reliability, fairness, and validity," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(3), pages 789-809, December.
  32. Axel Philipps, 2022. "Research funding randomly allocated? A survey of scientists’ views on peer review and lottery," Science and Public Policy, Oxford University Press, vol. 49(3), pages 365-377.
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