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Soziale Bedingungen und Effekte der quantitativen Leistungsmessung: Ergebnisse einer Befragung von jungen Wissenschaftlerinnen und Wissenschaftlern

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  • Rogge, Jan-Christoph

Abstract

In diesem Beitrag werden die Auswirkungen des Journal Impact Faktor und anderer Formen der quantitativen Leistungsmessung auf die Arbeit und die Karrieren des sogenannten wissenschaftlichen Nachwuchses aus Sicht desselben beleuchtet. Anhand von Interviews mit 20 Wissenschaftlerinnen und Wissenschaftlern aus zehn Disziplinen, die mindestens promoviert sind, aber (noch) keine Professur bekleiden, werden drei Thesen entwickelt: (1) Die zunehmende praktische Virulenz der quantitativen Leistungsmessung trägt dazu bei, dass die Wissenschaft mehr und mehr zum „Karrierejob“ wird. (2) Um ihre Chancen auf Erfolg zu wahren, setzen insbesondere die aufstiegsorientierten Wissenschaftlerinnen und Wissenschaftler Strategien zur Verbesserung ihres Publikationsoutputs ein. (3) Selbstsicherheit und Routine im Publikationsprozess sind wesentlich von der beruflichen Förderung durch Mentorinnen und Mentoren abhängig.

Suggested Citation

  • Rogge, Jan-Christoph, 2015. "Soziale Bedingungen und Effekte der quantitativen Leistungsmessung: Ergebnisse einer Befragung von jungen Wissenschaftlerinnen und Wissenschaftlern," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 66(2), pages 205-214.
    • Handle: RePEc:zbw:espost:168594
    DOI: 10.5771/0038-6073-2015-2-205
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    References listed on IDEAS

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    1. Christoph Bartneck & Servaas Kokkelmans, 2011. "Detecting h-index manipulation through self-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(1), pages 85-98, April.
    2. Alexandru T. Balaban, 2012. "Positive and negative aspects of citation indices and journal impact factors," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(2), pages 241-247, August.
    3. Gualberto Buela-Casal & Izabela Zych, 2012. "What do the scientists think about the impact factor?," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(2), pages 281-292, August.
    4. Brian C. Martinson & Melissa S. Anderson & Raymond de Vries, 2005. "Scientists behaving badly," Nature, Nature, vol. 435(7043), pages 737-738, June.
    5. Aksnes, Dag W. & Rip, Arie, 2009. "Researchers' perceptions of citations," Research Policy, Elsevier, vol. 38(6), pages 895-905, July.
    6. Daniel Teodorescu & Tudorel Andrei, 2014. "An examination of “citation circles” for social sciences journals in Eastern European countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 209-231, May.
    7. Jerome K. Vanclay, 2012. "Impact factor: outdated artefact or stepping-stone to journal certification?," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(2), pages 211-238, August.
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