This study explores the prevalence of postdoctoral fellows in fast-moving and competitive scientific research. We use the results of a new and original large-scale survey of scientists in Japan and the United States for the analyses. Descriptive statistics show that, in both Japan and the United States: (1) the mean citation time lag was shorter by about 2 years in the highly cited papers (top 1 %) compared to other normal papers; and (2) the perceived degree of competitive threat was also higher for the projects producing the highly cited papers compared to those for normal papers. We also found that the likelihood of participation of postdoctoral fellows is significantly higher in research with shorter mean time lag and higher competitive threat (while that of students is not), controlling for author size, suggesting that postdoctoral fellows are especially prevalent in research efforts in fast-moving and competitive scientific research.
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“Journal field” refers to the 19 natural science fields in the Essential Science Indicators (ESIs) of Thomson Reuters. Details are shown in the section “Definition of journal fields” of Appendix.
The survey in Japan was conducted from the end of 2009 to the summer of 2010. The survey in the United States was conducted from the autumn of 2010 to early 2011. Since there was a lag of about 5–10 years between the publication of focal papers and the survey, there is the possibility that respondents were not confident about the co-author information they provided. To avoid as much as possible ambiguity about responses, we presented in the web questionnaire the last name and first initial of each author. We also dropped from our analyses those records from which incomplete answers were captured.
The results using only normal papers were similar to those presented here. These results are available from the authors on request. .
Young author respondents account for about 12.1 % (343) of the 2,831 focal papers authored by two or more individuals.
The level of funding was another variable used to control for size of the research team. However, there would be significant endogeneity in the level of funding with respect to the participation of a postdoctoral fellow, since the surveyed personnel expenditures included those related to employing scientists and technicians specifically in research projects. For this reason, the survey item mainly measured the personnel cost of young scholars, especially postdoctoral fellows, employed for the project. Thus, we decided not to include this measure.
Adams, J. D., Black, G. C., Clemmons, J. R., & Stephan, P. E. (2005). Scientific teams and institutional collaborations: Evidence from U.S. universities, 1981–1999. Research Policy, 34, 259–285.
Baldi, S., & Hargens, L. L. (1997). Re-examining price’s conjectures on the structure of reference networks: Results from the special relativity, spatial diffusion modeling and role analysis literatures. Social Studies of Science, 27, 669–687.
Bednorz, G., & Müller, K. A. (1986). Possible high Tc superconductivity in the Ba–La–Cu–O system. Zeitschrift für Physik B, 64, 189–193.
Black, G., & Stephan, P. E. (2010). The economics of university science and the role of foreign graduate students and postdoctoral scholars. In C. T. Clotfelter (Ed.), American Universities in a global market (pp. 129–161). Chicago: University of Chicago Press.
Empirica GmbH. (2005). Post-docs in the life sciences. Paper prepared for the NetReAct Project. www.netreact-eu.org/documents/NetreactDeliverable1.3.pdf. Accessed: 29 03 2013.
Franzoni, C., Scellato, G., & Stephan, P. (2012). Foreign born scientists: Mobility patterns for sixteen countries. NBER working paper series. Working paper no. 18067.
Hagstrom, W. O. (1974). Competition in science. American Sociological Review, 39, 1–18.
Hall, B.H., & Trajtenberg, M. (2004). Uncovering GPTS with patent data, NBER working paper, no. 10901.
Hargens, L. L. (2000). Using the literature: Reference networks, reference contexts, and the social structure of scholarship. American Sociological Review, 65, 846–865.
Igami, M., & Okazaki, T. (2007). Capturing nanotechnology’s current state of development via analysis of patents. oecd science, technology and industry working papers 2007/04, OECD Publishing.
Kamerlingh Onnes, H. (1911). The disappearance of the resistivity of mercury. Leiden: Commun. Phys. Lab. Univ. 122b.
Larivière, V. (2012). On the shoulders of students? The contribution of PhD students to the advancement of knowledge. Scientometrics, 90, 463–481.
Merton, R. K. (1973). The sociology of science: Theoretical and empirical investigations. Chicago: University of Chicago Press.
OECD. (2009). Patent statistics manual. Paris: OECD Publishing.
Price, D. J. D. S. (1965). Networks of scientific papers. Science, 149, 510–515.
Stephan, P. E. (2012). How economics shapes science. Cambridge: Harvard University Press.
Takahashi, K., Tanabe, K., Ohnuki, M., Narita, M., Ichisaka, T., Tomoda, K., et al. (2007). Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell, 131, 861–872.
Takahashi, K., & Yamanaka, S. (2006). Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell, 126, 663–676.
Wu, M. K., Ashburn, J. R., Torng, C. J., Hor, P. H., Meng, R. L., Gao, L., et al. (1987). Superconductivity at 93 K in a new mixed-phase Y–Ba–Cu–O compound system at ambient pressure. Physical Review Letters, 58, 908–910.
Wuchty, S., Jones, B., & Uzzi, B. (2007). The increasing dominance of teams in the production of knowledge. Science, 316, 1030–1036.
Yu, J., Vodyanik, M. A., Smuga-Otto, K., Antosiewicz-Bourget, J., Frane, J. L., Tian, S., et al. (2007). Induced pluripotent stem cell lines derived from human somatic cells. Science, 318, 1917–1920.
This research represents collaboration between the Institute of Innovation Research (IIR) of Hitotsubashi University and the National Institute of Science and Technology Policy (NISTEP), as part of the “Industry–university–government joint research on the innovation process” project, with support from Special Funds for Education and Research from Japan’s Ministry of Education, Culture, Sports, Science and Technology. This work was also supported by JSPS KAKENHI 21243020, and by the US National Science Foundation (OISE-1019038). The Georgia Institute of Technology implemented the survey in the United States, in collaboration with IIR and NISTEP. Paula Stephan contributed significantly to the design of our survey. We have benefitted significantly from the participants of the conference on “The Organisation, Economics and Policy of Scientific Research,” in February 2011 (Torino); the EUSPRI Conference on “Path-breaking Innovation: Understanding, Managing and Providing Support for Continuous Radical Change in Science and Innovation,” in June 2012 (Milan); and the 17th International Conference on Science and Technology Indicators, in September 2012 (Montreal).
Appendix: Survey methodology
Appendix: Survey methodology
Definition of journal fields
The “journal field” refers to the 19 natural science fields in the ESIs of Thomson Reuters. They are agricultural sciences; biology & biochemistry; chemistry; clinical medicine; computer science; engineering; environment/ecology; geosciences; immunology; materials science; mathematics; microbiology; molecular biology & genetics; neuroscience & behavior; pharmacology & toxicology; physics; plant & animal science; psychiatry/psychology; and space science. The journal fields were identified based on a list of journals disclosed by Thomson Reuters; that list as of April 30, 2008 was used.
Some results were based on three broad fields derived through further aggregation (i.e., physical sciences, life sciences, and medicine). Natural sciences comprised physical sciences, life sciences, and medicine. Papers from multidisciplinary fields, those published in journals such as Nature and Science, were reclassified into one of 19 fields, based on the backward citations of the multidisciplinary papers.
Identification of survey targets and research projects for the survey
The population of the survey comprised articles and letters in the Web of Science database of Thomson Reuters. The survey time window for the papers was from 2001 to 2006 (in the database year). The bibliographic information and the number of citations as of the end of December 2006 were used to identify the focal papers. Two sets of focal papers were selected from the population, as shown below.
Highly cited papers (approximately 3,000 in each survey): top 1 % highly cited papers in each journal field and in each database year; at least one author’s institution was located in Japan (for the Japanese survey) or in the United States (for the US survey).
Normal papers (approximately 7,000 in each survey): randomly selected papers in each journal field and in each database year from the population of the survey, excluding the above highly cited top 1 % papers; at least one author’s institution was located in Japan (for the Japanese survey) or in the United States (for the US survey).
The number of top 1 % highly cited papers in 2001–2006 was 2,906 for Japan and 24,338 for the United States. All highly cited papers within the time window were selected for the Japanese survey. We conducted proportional sampling for the United States, NHC × α, with a minimum of 70 highly cited papers in each field, where α = 2,906/24,338. Twice the count of highly cited papers was randomly selected as the number of normal papers for each field.
Corresponding authors or equivalents of approximately 18,000 possible focal papers were searched and identified as survey targets. If multiple papers were assigned to a single corresponding (or equivalent) author, one paper was randomly selected as a focal paper, with priority given in the selection process to highly cited papers. The results of interviews with scientists prior to implementing the survey suggested that when a scientist has multiple candidate papers for the survey, they are often from the same project. We decided that we would choose only one focal paper for each scientist, in consideration of the burden that response would place on each scientist.
In Japan, 7,652 survey targets were identified; of those, there were 1,932 scientists whose focal paper was a highly cited paper and 5,720 scientists whose focal paper was a normal paper. In the United States, 8,864 survey targets were identified; of those, there were 2,882 scientists whose focal paper was a highly cited paper and 5,982 scientists whose focal paper was a normal paper.
For the Japanese survey, 6,522 of the 7,652 survey targets were matched with only one possible focal paper. In the United States, 8,372 of the 8,863 survey targets had only one focal paper. In these cases, the focal papers were equal to the possible focal papers. On the other hand, 1,130 of the 7,652 survey targets in Japan and 491 of 8,863 in the United States were matched with more than one possible focal paper.
Possible response bias
Although this survey had a relatively high response rate, the non-response rate exceeded 70 %. For this reason, it was necessary to examine whether there were some major sources of response bias. This note examines possible response biases.
In both Japan and the United States, there was no significant response bias on almost all basic measures, including single-author versus team-authored papers, mean number of citations, or publication year. The few differences that were statistically significant tended to be substantively small (e.g., the mean number of affiliations among the respondents was 2.3 in the United States and 2.6 in Japan, while among non-respondents it was 2.5 in the United States and 2.8 in Japan). In particular, there was a concern that a productive scientist with many good papers may not respond, since he or she is busy. However, we found that in both countries, survey targets producing one or more highly cited papers were more likely to respond to this survey.
There was also the concern that among papers with multiple authors, there would be a low response rate. For both countries, there was no difference in response for single-author versus multi-author papers. However, in each country, the survey targets producing focal papers written by many authors or by authors in multiple countries seemed reluctant to respond to this survey. For example, the response rate of the survey targets that produced a focal paper written by 50 or more authors was 17 % in Japan and 21 % in the United States; this was significantly lower than the mean response rate, although these survey targets accounted for less than 1 % of the samples.
Finally, survey targets in some sectors or with certain types of affiliations seemed less willing to respond the survey. In Japan, the response rates of survey targets staying in foreign countries, working at hospitals, and affiliated with business firms were 11, 17 and 23 %, respectively; these figures were lower than the mean. We also experienced below-mean response rates for firms (but not hospitals) in the United States. The response rate in clinical medicine and psychiatry/psychology was 21 % in both countries and the lowest. These differences should be borne in mind when interpreting the results.
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Igami, M., Nagaoka, S. & Walsh, J.P. Contribution of postdoctoral fellows to fast-moving and competitive scientific research. J Technol Transf 40, 723–741 (2015). https://doi.org/10.1007/s10961-014-9366-7
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