IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/68046.html

Influential Mathematicians: Birth, Education and Affiliation

Author

Listed:
  • Panaretos, John
  • Malesios, Chrisovalandis

Abstract

Research output and impact is currently the focus of serious debate worldwide. Quantitative analyses based on a wide spectrum of indices indicate a clear advantage of US institutions as compared to institutions in Europe and the rest of the world. However the measures used to quantify research performance are mostly static: Even though research output is the result of a process that extends in time as well as in space, indices often only take into account the current affiliation when assigning influential research to institutions. In this paper, we focus on the field of mathematics and investigate whether the image that emerges from static indices persists when bringing in more dynamic information, through the study of the "trajectories" of highly cited mathematicians: birthplace, country of first degree, country of PhD and current affiliation. While the dominance of the US remains apparent, some interesting patterns -that perhaps explain this dominance- emerge.

Suggested Citation

  • Panaretos, John & Malesios, Chrisovalandis, 2012. "Influential Mathematicians: Birth, Education and Affiliation," MPRA Paper 68046, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:68046
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/68046/1/Panaretos-NAMS2012%28274-286%29ft.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Luc Bauwens & Giordano Mion & Jacques-François Thisse, 2011. "The Resistible Decline of European Science," Recherches économiques de Louvain, De Boeck Université, vol. 77(4), pages 5-31.
    2. John Panaretos & Chrisovaladis Malesios, 2009. "Assessing scientific research performance and impact with single indices," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(3), pages 635-670, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pedro Albarrán & Raquel Carrasco & Javier Ruiz-Castillo, 2017. "Are Migrants More Productive Than Stayers? Some Evidence From A Set Of Highly Productive Academic Economists," Economic Inquiry, Western Economic Association International, vol. 55(3), pages 1308-1323, July.
    2. Carrasco, Raquel & Ruiz-Castillo, Javier, 2016. "The gender productivity gap : some evidence for a set of highly productive academic economists," UC3M Working papers. Economics 23525, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Raquel Carrasco & Javier Ruiz-Castillo, 2019. "Correction to: Spatial mobility in elite academic institutions in economics: the case of Spain," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(2), pages 173-173, June.
    4. Pedro Albarrán & Raquel Carrasco & Javier Ruiz-Castillo, 2017. "Geographic mobility and research productivity in a selection of top world economics departments," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 241-265, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Deming Lin & Tianhui Gong & Wenbin Liu & Martin Meyer, 2020. "An entropy-based measure for the evolution of h index research," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2283-2298, December.
    2. Carillo, Maria Rosaria & Papagni, Erasmo & Sapio, Alessandro, 2013. "Do collaborations enhance the high-quality output of scientific institutions? Evidence from the Italian Research Assessment Exercise," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 47(C), pages 25-36.
    3. Bornmann, Lutz & Mutz, Rüdiger & Daniel, Hans-Dieter, 2010. "The h index research output measurement: Two approaches to enhance its accuracy," Journal of Informetrics, Elsevier, vol. 4(3), pages 407-414.
    4. Zhenbin Yan & Qiang Wu & Xingchen Li, 2016. "Do Hirsch-type indices behave the same in assessing single publications? An empirical study of 29 bibliometric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1815-1833, December.
    5. Christoph Bartneck & Servaas Kokkelmans, 2011. "Detecting h-index manipulation through self-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(1), pages 85-98, April.
    6. Maziar Montazerian & Edgar Dutra Zanotto & Hellmut Eckert, 2019. "A new parameter for (normalized) evaluation of H-index: countries as a case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 1065-1078, March.
    7. Lutz Bornmann & Werner Marx, 2014. "How to evaluate individual researchers working in the natural and life sciences meaningfully? A proposal of methods based on percentiles of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 487-509, January.
    8. C. O. S. Sorzano & J. Vargas & G. Caffarena-Fernández & A. Iriarte, 2014. "Comparing scientific performance among equals," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(3), pages 1731-1745, December.
    9. William Cabos & Juan Miguel Campanario, 2018. "Exploring the Hjif-Index, an Analogue to the H-Like Index for Journal Impact Factors," Publications, MDPI, vol. 6(2), pages 1-11, April.
    10. Bornmann, Lutz & Marx, Werner, 2012. "HistCite analysis of papers constituting the h index research front," Journal of Informetrics, Elsevier, vol. 6(2), pages 285-288.
    11. Eduardo A. Oliveira & Enrico A. Colosimo & Daniella R. Martelli & Isabel G. Quirino & Maria Christina L. Oliveira & Leonardo S. Lima & Ana Cristina Simões e Silva & Hercílio Martelli-Júnior, 2012. "Comparison of Brazilian researchers in clinical medicine: are criteria for ranking well-adjusted?," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(2), pages 429-443, February.
    12. Shahid Yusuf & Kaoru Nabeshima, 2009. "Growth through Innovation : An Industrial Strategy for Shanghai," World Bank Publications - Reports 18613, The World Bank Group.
    13. Petridis, Konstantinos & Malesios, Chrisovalantis & Arabatzis, Garyfallos & Thanassoulis, Emmanuel, 2013. "Efficiency analysis of forestry journals: Suggestions for improving journals’ quality," Journal of Informetrics, Elsevier, vol. 7(2), pages 505-521.
    14. Roberto Todeschini, 2011. "The j-index: a new bibliometric index and multivariate comparisons between other common indices," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(3), pages 621-639, June.
    15. Lorna Wildgaard & Jesper W. Schneider & Birger Larsen, 2014. "A review of the characteristics of 108 author-level bibliometric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 125-158, October.
    16. Eduardo Araujo Oliveira & Roberto Peicots-Filho & Daniella Reis Martelli & Isabel Gomes Quirino & Maria Christina Lopes Oliveira & Mariana Guerra Duarte & Sergio Veloso Pinheiro & Enrico Antonio Colos, 2013. "Is there a correlation between journal impact factor and researchers’ performance? A study comprising the fields of clinical nephrology and neurosciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(2), pages 149-160, November.
    17. Edgar D. Zanotto & Vinicius Carvalho, 2021. "Article age- and field-normalized tools to evaluate scientific impact and momentum," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2865-2883, April.
    18. Rainer Frietsch & Sonia Gruber & Lutz Bornmann, 2025. "The definition of highly cited researchers: the effect of different approaches on the empirical outcome," Scientometrics, Springer;Akadémiai Kiadó, vol. 130(2), pages 881-907, February.
    19. Burgos, Albert, 2010. "Measurable utility for scientific influence," UMUFAE Economics Working Papers 16347, DIGITUM. Universidad de Murcia.
    20. Ozlem Inanc & Onur Tuncer, 2011. "The effect of academic inbreeding on scientific effectiveness," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(3), pages 885-898, September.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C00 - Mathematical and Quantitative Methods - - General - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:68046. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.