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Curriculum vitae method in science policy and research evaluation: the state-of-the-art

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  • Carolina Cañibano
  • Barry Bozeman

Abstract

This is a state-of-the-art assessment for a small but burgeoning research approach, use of curricula vitae in research evaluation. The accumulated research remains sufficiently modest for us to consider nearly all published studies and the full range of research purposes to which CV analysis has been applied. CV analysis has been theory-driven, and theory and tools have increasingly converged. Advances in method and technique have been abetted especially by the push for a scientific and technical human capital theory to explain the role of capacity in research evaluation. We summarize the theoretical rationale for CV analysis, and present three major foci: career trajectories, mobility, and the mapping of collective capacity. We assess progress in solving methodological and practical problems and the future research possibilities and remaining needs in developing methods. We reflect on some new research topics that could benefit from CV analysis. We draw on the papers in this special issue of Research Evaluation to illustrate research developments and to show the place of specific contributions in the developing CV literature. Copyright , Beech Tree Publishing.

Suggested Citation

  • Carolina Cañibano & Barry Bozeman, 2009. "Curriculum vitae method in science policy and research evaluation: the state-of-the-art," Research Evaluation, Oxford University Press, vol. 18(2), pages 86-94, June.
  • Handle: RePEc:oup:rseval:v:18:y:2009:i:2:p:86-94
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    Cited by:

    1. Sarah Seus & Susanne Bührer, 2022. "The evaluation of the Austrian START programme: an impact analysis of a research funding programme using a multi-method approach," The Journal of Technology Transfer, Springer, vol. 47(3), pages 673-698, June.
    2. Weilong Bi & Ho Fai Chan & Benno Torgler, 2019. "Self-esteem, self-symbolizing, and academic recognition: behavioral evidence from curricula vitae," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 495-525, April.
    3. Stephan, Paula E., 2010. "The Economics of Science," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 1, chapter 0, pages 217-273, Elsevier.
    4. Geuna, Aldo & Kataishi, Rodrigo & Toselli, Manuel & Guzmán, Eduardo & Lawson, Cornelia & Fernandez-Zubieta, Ana & Barros, Beatriz, 2015. "SiSOB data extraction and codification: A tool to analyze scientific careers," Research Policy, Elsevier, vol. 44(9), pages 1645-1658.
    5. Carolina Cañibano & F. Javier Otamendi & Francisco Solís, 2011. "International temporary mobility of researchers: a cross-discipline study," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(2), pages 653-675, November.
    6. Soleidy Rivero Amador & Maidelyn Díaz Pérez & María José López-Huertas & Reinaldo Javier Rodríguez Font, 2018. "Indicator system for managing science, technology and innovation in universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(3), pages 1575-1587, June.
    7. Valentina Tartari & Francesco Di Lorenzo & Benjamin A. Campbell, 2020. "“Another roof, another proof”: the impact of mobility on individual productivity in science," The Journal of Technology Transfer, Springer, vol. 45(1), pages 276-303, February.
    8. Mladen Djuric & Marina Dobrota & Jovan Filipovic, 2020. "Complexity-based quality indicators for human and social capital in science and research: the case of Serbian Homeland versus Diaspora," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 303-328, July.
    9. Elizabeth A. Corley & Barry Bozeman & Xuefan Zhang & Chin-Chang Tsai, 2019. "The expanded scientific and technical human capital model: the addition of a cultural dimension," The Journal of Technology Transfer, Springer, vol. 44(3), pages 681-699, June.
    10. Magnus Gulbrandsen & Taran Thune, 2017. "The effects of non-academic work experience on external interaction and research performance," The Journal of Technology Transfer, Springer, vol. 42(4), pages 795-813, August.
    11. Zaida Chinchilla-Rodríguez & Anuska Ferligoj & Sandra Miguel & Luka Kronegger & Félix Moya-Anegón, 2012. "Blockmodeling of co-authorship networks in library and information science in Argentina: a case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 699-717, December.
    12. Sabharwal, Meghna & Hu, Qian, 2013. "Participation in university-based research centers: Is it helping or hurting researchers?," Research Policy, Elsevier, vol. 42(6), pages 1301-1311.
    13. Lu, Xiao & McInerney, Paul-Brian, 2016. "Is it better to “Stand on Two Boats” or “Sit on the Chinese Lap”?: Examining the cultural contingency of network structures in the contemporary Chinese academic labor market," Research Policy, Elsevier, vol. 45(10), pages 2125-2137.
    14. Landström, Hans & Harirchi, Gouya & Åström, Fredrik, 2012. "Entrepreneurship: Exploring the knowledge base," Research Policy, Elsevier, vol. 41(7), pages 1154-1181.
    15. Wentian Shi & Quansheng Fu & Wenlong Yang & Fan Yang & Xiao Lin & Xueying Mu, 2022. "The spatial relationship between the mobility and scientific cooperation of Chinese scientists," Growth and Change, Wiley Blackwell, vol. 53(2), pages 951-971, June.
    16. Mladen Djuric & Jovan Filipovic & Stefan Komazec, 2020. "Reshaping the Future of Social Metrology: Utilizing Quality Indicators to Develop Complexity-Based Scientific Human and Social Capital Measurement Model," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 148(2), pages 535-567, April.
    17. Maxim Kotsemir & Ekaterina Dyachenko & Alena Nefedova, 2022. "Mobile young researchers and their non-mobile ‘twins’: who is winning the academic race?," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7307-7332, December.

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