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Social capital in academia

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Abstract

This paper provides useful insights for the design of networks that promote research productivity. The results suggest that the different dimensions of social capital affect scientific performance differently depending on the area of knowledge. Overall, dense networks negatively affect the creation of new knowledge. In addition, the analysis shows that a division of labor in academia, in the sense of interdisciplinary research, increases the productivity of researchers. It is also found that the position in a network is critical. Researchers who are central tend to create more knowledge. Finally, the findings suggest that the number of ties have a positive impact on future productivity. Related to areas of knowledge, Exact Sciences is the area in which social capital has a stronger impact on research performance. On the other side, Social and Humanities, as well as Engineering, are the ones in which social capital has a lesser effect. The differences found across multiple domains of science suggest the need to consider this heterogeneity in policy design.

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Notes

  1. For this purpose, the ISI subject category of the papers was used. ISI uses 105 different subject category to classify papers/journals.

  2. The Mexican National System of Researchers was created in 1984 to enhance the quality and productivity of researchers in Mexico. It gives pecuniary compensation, as a complement of salary, to the most productive researchers. The selection process is done by peer review committees organized by the same areas of knowledge that are used in this paper, except that in SNI Humanities and Social Sciences are separate areas. However, both areas have similar ISI publication patterns.

  3. Researchers in SNI self-select their own area of knowledge.

  4. The publications were obtained by matching the database of researchers in SNI, with Mexican articles from the ISI database from 1981–2002 (ISI, 2003). This matching was done manually, first checking the last names and initials, then verifying the affiliation institution, and finally the field of knowledge. To verify the reliability of the matching process, names of researchers were randomly selected, and their productivity corroborated against their official CVs (CVU), in a joint effort with the National Council for Science and Technology (Conacyt).

  5. The threshold of no more than 8 authors was chosen to capture around 95 % of the total number of articles. According to the ISI database, only 4 % of the articles reported in the Mexican database had more than 8 authors. Most of these articles are in the Exact Sciences. The number of articles with no more than 7 authors is 94 % and with no more than 9 authors is 98 %.

  6. As a measure of reputation, the number of publications with a foreign address is used.

  7. The classification was constructed by considering 11 different fields of knowledge that match the 105 ISI categories into subject groups. This mapping was based on an analysis of journal usage by researchers working in different subject departments in UK universities (Adams, 1998). The categories used are the ones published by ISI in 2003.

  8. The “adjacent” matrix is a matrix composed of as many rows and columns as there are researchers, and where the elements represent the ties between actors, this is, the number of joint publications.

  9. We also run regressions using a 4 and a 5 year window. However, no significant differences were found in the coefficients of the network variables.

  10. This classification is the same one used by the Mexican System of Researchers (SNI).

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Acknowledgments

The author would like to thank the Instituto Tecnológico Autónomo de México (ITAM) and the Asociación Mexicana de Cultura AC for their support of this work.

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Correspondence to Claudia N. Gonzalez-Brambila.

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Gonzalez-Brambila, C.N. Social capital in academia. Scientometrics 101, 1609–1625 (2014). https://doi.org/10.1007/s11192-014-1424-2

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