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International collaboration does not have greater epistemic authority

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  • Zi‐Lin He

Abstract

The consistent finding that internationally coauthored papers are more heavily cited has led to a tacit agreement among politicians and scientists that international collaboration in scientific research should be particularly promoted. However, existing studies of research collaboration suffer from a major weakness in that the Thomson Reuters Web of Science until recently did not link author names with affiliation addresses. The general approach has been to hierarchically code papers into international paper, national paper, or local paper based on the address information. This hierarchical coding scheme severely understates the level and contribution of local or national collaboration on an internationally coauthored paper. In this research, I code collaboration variables by hand checking each paper in the sample, use two measures of a paper's impact, and try several regression models. I find that both international collaboration and local collaboration are positively and significantly associated with a paper's impact, but international collaboration does not have more epistemic authority than local collaboration. This result suggests that previous findings based on hierarchical coding might be misleading.

Suggested Citation

  • Zi‐Lin He, 2009. "International collaboration does not have greater epistemic authority," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(10), pages 2151-2164, October.
  • Handle: RePEc:bla:jamist:v:60:y:2009:i:10:p:2151-2164
    DOI: 10.1002/asi.21150
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    Cited by:

    1. Ki-Seok Kwon & Han Woo Park & Minho So & Loet Leydesdorff, 2012. "Has globalization strengthened South Korea’s national research system? National and international dynamics of the Triple Helix of scientific co-authorship relationships in South Korea," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(1), pages 163-176, January.
    2. Yifan Qian & Wenge Rong & Nan Jiang & Jie Tang & Zhang Xiong, 2017. "Citation regression analysis of computer science publications in different ranking categories and subfields," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(3), pages 1351-1374, March.
    3. Jiang Wu, 2013. "Geographical knowledge diffusion and spatial diversity citation rank," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 181-201, January.
    4. María Bordons & Javier Aparicio & Rodrigo Costas, 2013. "Heterogeneity of collaboration and its relationship with research impact in a biomedical field," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(2), pages 443-466, August.
    5. Peter Mutschke & Philipp Mayr, 2015. "Science models for search: a study on combining scholarly information retrieval and scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2323-2345, March.
    6. Basma Albanna & Julia Handl & Richard Heeks, 2021. "Publication outperformance among global South researchers: An analysis of individual-level and publication-level predictors of positive deviance," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8375-8431, October.
    7. Dongqing Lyu & Kaile Gong & Xuanmin Ruan & Ying Cheng & Jiang Li, 2021. "Does research collaboration influence the “disruption” of articles? Evidence from neurosciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 287-303, January.
    8. Thelwall, Mike & Wilson, Paul, 2014. "Regression for citation data: An evaluation of different methods," Journal of Informetrics, Elsevier, vol. 8(4), pages 963-971.
    9. Peter Mutschke & Philipp Mayr & Philipp Schaer & York Sure, 2011. "Science models as value-added services for scholarly information systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 349-364, October.

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