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A two-fold evaluation in science: the case of Nobel Prize

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Abstract

The Nobel Prize is a prestigious award for outstanding contributions in different fields of science. However, the issue of how Nobel laureates stand out from all nominees remains a “black box” to be explored. Using data on nominees and nominators for the prizes in physics, chemistry, and physiology or medicine from 1901 to 1950, in this study, the influences of the academic impact of a nominee’s research, social identities of nominators, and the interaction between the two factors on the nominee’s chance of winning were explored. The main determinants for a nominee to receive a Nobel Prize include the academic impact as measured by using L-index and h-index, and nominators’ academic identity. However, significant disciplinary differences exist in terms of the influences of such factors. In physics, a nominee’s L-index showed a very significant and positive effect, and nominators’ administrative identity was helpful, and also their interactions. In chemistry, a nominee’s h-index, as well as a nominator’s administrative identity and academic identity, were all significant, and similar to physics, interactions between L-index and administrative identity could also increase a nominee’s probability of winning the prize. In physiology or medicine, nominee’s h-index and nominators’ academic identity were of great concern, and when a nominee with a high h-index was nominated by a nominator with a high academic identity, the nominee’s chance of being awarded was observed to be increased.

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Notes

  1. For example, it is hard to say that a scientist who published 20 medium-impact papers with 20 citations to each (h-index = 20) is better than someone having 10 high-impact papers with 200 citations to each (h-index = 10).

  2. The Lowry paper is named after American biochemist Oliver H. Lowry whose paper, “Protein measurement with the Folin phenol reagent,” published in the Journal of Biological Chemistry (Lowry et al., 1951), is the most highly cited paper ever in the scientific literature. Since then, more sensitive methods for the measurement of protein have been introduced; however, Lowry’s paper that introduced the new method of measurement remains the “King of the Classics,” with 356,297 citations as of July 2023.

References

  • Ashton, S. V., & Oppenheim, S. (1978). A method of predicting Nobel Prize winners in chemistry. Social Studies of Science, 8(3), 341–348.

    Article  Google Scholar 

  • Baffes, J., & Vamvakidis, A. (2011). Are you too young for the Nobel Prize? Research Policy, 40(10), 1345–1353.

    Article  Google Scholar 

  • Boh, W. F., Evaristo, R., & Ouderkirk, A. (2014). Balancing breadth and depth of expertise for innovation: A 3M story. Research Policy, 43(2), 349–366.

    Article  Google Scholar 

  • Bornmann, L., & Daniel, H. D. (2005). Does the h-index for ranking of scientists really work? Scientometrics, 65(3), 391–392.

    Article  Google Scholar 

  • Bornmann, L., Mutz, R., Neuhaus, C., & Daniel, H. (2008). Citation counts for research evaluation: Standards of good practice for analyzing bibliometric data and presenting and interpreting results. Ethics in Science and Environmental Politics, 8(1), 93–102.

    Article  Google Scholar 

  • Brown, L. D., & Gardner, J. C. (1985). Using citation analysis to assess the impact of journals and articles on contemporary accounting research (CAR). Journal of Accounting Research, 23(1), 84–109.

    Article  Google Scholar 

  • Burt, R. S. (1995). Structural holes: The social structure of competition. Harvard University Press.

    Google Scholar 

  • Chan, H. F., Laura, G., & Benno, T. (2014). Awards before and after the Nobel Prize: A Matthew effect and/or a ticket to one’s own funeral? Research Evaluation, 23(3), 210–220.

    Article  Google Scholar 

  • Chan, H. F., Mixon, F. G., & Torgler, B. (2018). Relation of early career performance and recognition to the probability of winning the Nobel Prize in economics. Scientometrics, 114(3), 1069–1086.

    Article  Google Scholar 

  • Chan, H. F., & Torgler, B. (2012). Econometric fellows and Nobel laureates in economics. Economics Bulletin, 32(4), 3365–3377.

    Google Scholar 

  • Chan, H. F., & Torgler, B. (2013). Time-lapsed awards for excellence. Nature, 500(7460), 29.

    Article  Google Scholar 

  • Chan, H. F., & Torgler, B. (2015). The implications of educational and methodological background for the career success of Nobel laureates: An investigation of major awards. Scientometrics, 102(1), 847–863.

    Article  Google Scholar 

  • Charlton, B. G. (2007). Measuring revolutionary biomedical science 1992–2006 using Nobel prizes, Lasker (clinical medicine) awards and Gairdner awards (NLG metric). Medical Hypotheses, 69(1), 1–5.

    Article  MathSciNet  Google Scholar 

  • Clynes, T. (2016). Where Nobel winners get their start. Nature, 538(7624), 152.

    Article  Google Scholar 

  • Cole, S. (1992). Making science: Between nature and society. Harvard University Press.

    Google Scholar 

  • Coleman, J. S. (1988). Social capital in the creation of human capital. American Journal of Sociology, 94, S95–S120.

    Article  Google Scholar 

  • Costas, R., & Bordons, M. (2007). The h-index: Advantages, limitations and its relation with other bibliometric indicators at the micro level. Journal of Informetrics, 1(3), 193–203.

    Article  Google Scholar 

  • Crawford, E. (1992). Nationalism and internationalism in science, 1880–1939: Four studies of the NOBEL Population (1st ed.). Cambridge University Press.

    Book  Google Scholar 

  • Cronin, B., & Meho, L. (2006). Using the h-index to rank influential information scientists. Journal of the American Society for Information Science and Technology, 57(9), 1275–1278.

    Article  Google Scholar 

  • Dominique, Pestré, E., & Crawford. (1984). The beginnings of the Nobel Institution: The Science Prizes, 1901–1915. Cambridge University Press.

    Google Scholar 

  • Egghe, L., & Rousseau, R. (2021). The h-index formalism. Scientometrics, 126(7), 6137–6145.

    Article  Google Scholar 

  • Gallotti, R., & Domenico, M. (2019). Effects of homophily and academic reputation in the nomination and selection of Nobel laureates. Scientific Reports, 9(1), 17304.

    Article  Google Scholar 

  • Garfield, E., & Malin, M. V. (1968). Can Nobel Prize winners be predicted? Paper presented at 135th Annual Meeting, American Association for the Advancement of Science, Dallas, Texas – December 26–31

  • Garfield, E. (1970). Citation indexing for studying science. Nature, 227(5259), 870.

    Article  Google Scholar 

  • Garfield, E., & Welljams-Dorof, A. (1992). Of Nobel class: A citation perspective on high impact research authors. Theoretical Medicine, 13, 117–135.

    Article  Google Scholar 

  • Gingras, Y., & Wallace, M. L. (2010). Why it has become more difficult to predict Nobel Prize winners: A bibliometric analysis of nominees and winners of the chemistry and physics Prizes (1901–2007). Scientometrics, 82(2), 401–412.

    Article  Google Scholar 

  • Hillebrand, C. D. (2002). Nobel century: A biographical analysis of physics laureates. Interdisciplinary Science Reviews, 27(2), 87–93.

    Article  Google Scholar 

  • Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Ences of the United States of America, 102(46), 16569–16572.

    Article  MATH  Google Scholar 

  • Hogg, M. A., Terry, D. J., & White, K. M. (1995). A tale of two theories: A critical comparison of identity theory with social identity theory. Social Psychology Quarterly, 58(4), 255–269.

    Article  Google Scholar 

  • Inhaber, H., & Przednowek, K. (1976). Quality of research and Nobel-Prizes. Social Studies of Science, 6(1), 33–50.

    Article  Google Scholar 

  • Ioannidis, J. P. A., Cristea, I. A., & Boyack, K. W. (2020). Work honored by Nobel prizes clusters heavily in a few scientific fields. PLoS ONE, 15, e0234612.

    Article  Google Scholar 

  • Kaplan, E., & Meier, P. (1958). Nonparametric-estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481.

    Article  MathSciNet  MATH  Google Scholar 

  • Kleinbaum, D. G., & Klein, M. (2012). Survival analysis, a self-learning text. Springer.

    Book  MATH  Google Scholar 

  • Lowry, O. H., Rosebrough, N. J., Farr, A. L., & Randall, R. J. (1951). Protein measurement with the Folin phenol reagent. Journal of Biological Chemistry, 193(1), 256–275.

    Article  Google Scholar 

  • Ma, Y., Mukherjee, S., & Uzzi, B. (2020). Mentorship and protégé success in STEM fields. Proceedings of the National Academy of Sciences, 117(25), 14077–14083.

    Article  Google Scholar 

  • Maclachlan, J. (1991). Defining physics: The Nobel Prize selection process, 1901–1937. American Journal of Physics, 59(2), 166–174.

    Article  Google Scholar 

  • Martin, B. R. (1996). The use of multiple indicators in the assessment of basic research. Scientometrics, 36(3), 343–362.

    Article  Google Scholar 

  • Nahapiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. Academy of Management Review, 23(2), 242–266.

    Article  Google Scholar 

  • Niewerth, S., Vogt, P., & Thewes, M. (2022). Tender evaluation through efficiency analysis for public construction contracts. Frontiers of Engineering Management, 9(1), 148–158.

    Article  Google Scholar 

  • Okoli, C., & Oh, W. (2007). Investigating recognition-based performance in an open content community: A social capital perspective. Information & Management, 44(3), 240–252.

    Article  Google Scholar 

  • Petersen, A. M. (2015). Quantifying the impact of weak, strong, and super ties in scientific careers. Proceedings of the National Academy of Sciences of the United States of America, 112(34), E4671–E4680.

    Google Scholar 

  • Rodríguez, J. G. (2022). Making the most of world talent for science? The Nobel Prize and fields medal experience. Scientometrics, 127(2), 813–847.

    Article  Google Scholar 

  • Rodriguez-Navarro, A. (2011a). Measuring research excellence: Number of Nobel Prize achievements versus conventional bibliometric indicators. Journal of Documentation, 67(4), 582–600.

    Article  Google Scholar 

  • Rodríguez-Navarro, A. (2011b). A simple index for the high-citation tail of citation distribution to quantify research performance in Countries and institutions. PLoS ONE, 6(5), e20510.

    Article  Google Scholar 

  • Rousseau, R. (2016). Citation data as a proxy for quality or scientific influence are at best PAC (probably approximately correct). Journal of the Association for Information Science & Technology, 67(12), 3092–3094.

    Article  Google Scholar 

  • Ryan, T. P. (1997). Modern regression methods Vol. 655. Wiley.

    Google Scholar 

  • Schlagberger, E. M., Bornmann, L., & Bauer, J. (2016). At what institutions did Nobel laureates do their prize-winning work? An analysis of biographical information on Nobel laureates from 1994 to 2014. Scientometrics, 109(2), 723–767.

    Article  Google Scholar 

  • Singh, R. (2007). India’s Physics and Chemistry Nobel Prize nominators and nominees in colonial and international context. Notes and Records of the Royal Society, 61(3), 333–345.

    Article  Google Scholar 

  • Stel, V. S., Dekker, F. W., Tripepi, G., Zoccali, C., & Jager, K. J. (2011). Survival analysis I: The Kaplan-Meier method. Nephron Clinical Practice, 119(1), c83–c88.

    Article  Google Scholar 

  • Stephan, P. E., & Levin, S. G. (1993). Age and the Nobel Prize revisited. Scientometrics, 28(3), 387–399.

    Article  Google Scholar 

  • Sun, Y., & Chen, L. (2019). Candidates’ Academic Influence, Nominators’ Status and The Awarding the Nobel Prize in Physics (1901–1950). Studies on Science of Science, 37(9), 1550–1557. (in Chinese).

    Google Scholar 

  • Thomson Reuters. (2011). Journal Citation Reports. Thomson Reuters Publication http://thomsonreuters.com/productsservices/science/science products/a-z/journal citation reports/

  • Tsai, W., & Ghoshal, S. (1998). Social capital and value creation: The role of intrafirm networks. Academy of Management Journal, 41(4), 464–476.

    Article  Google Scholar 

  • Van Dalen, H. (1999). The golden age of Nobel economists. The American Economist, 43(2), 19–35.

    Article  Google Scholar 

  • Walter, J., Lechner, C., & Kellermanns, F. W. (2007). Knowledge transfer between and within alliance partners: Private versus collective benefits of social capital. Journal of Business Research, 60(7), 698–710.

    Article  Google Scholar 

  • Wasko, M. M., & Faraj, S. (2005). Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. MIS Quarterly, 29(1), 35–57.

    Article  Google Scholar 

  • Yuasa. (1963). Center of scientific activity: Its shift from the 16th to the 20th century. Japanese Studies in the History of Science, 1(1), 57–75.

    MathSciNet  Google Scholar 

  • Zhang, H. H., Zuccala, A. A., & Ye, F. Y. (2019). Tracing the “swan groups” of physics and economics in the key publications of Nobel laureates. Scientometrics, 119(1), 425–436.

    Article  Google Scholar 

  • Zuckerman, H. (1967a). Sociology of Nobel Prizes. Scientific American, 217(5), 25–33.

    Article  Google Scholar 

  • Zuckerman, H. (1967b). Nobel laureates in science: Patterns of productivity, collaboration, and authorship. American Sociological Review, 32(3), 391–403.

    Article  Google Scholar 

  • Zuckerman, H. (1977). Scientific Elite: Nobel Laureates in the United States. Transaction Publishers.

    Google Scholar 

  • Zuckerman, H., & Merton, R. K. (1971). Patterns of evaluation in science – institutionalisation, structure and functions of referee system. Minerva, 9(1), 66–100.

    Article  Google Scholar 

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Authors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Lingzhi Chen & Yutao Sun

  2. University of Nottingham Ningbo, ningbo, China

    Cong Cao

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  1. Lingzhi Chen
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  2. Yutao Sun
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Correspondence to Yutao Sun.

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Chen, L., Sun, Y. & Cao, C. A two-fold evaluation in science: the case of Nobel Prize. Scientometrics 128, 6267–6291 (2023). https://doi.org/10.1007/s11192-023-04830-2

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