The causes of gender bias favoring men in scientific and scholarly systems are complex and related to overall gender relationships in most of the countries of the world. An as yet unanswered question is whether in research publication gender bias is equally distributed over scientific disciplines and fields or if that bias reflects a closer relation to the subject matter. We expected less gender bias with respect to subject matter, and so analysed 14 journals of gender studies using several methods and indicators. The results confirm our expectation: the very high position of women in co-operation is striking; female scientists are relatively overrepresented as first authors in articles. Collaboration behaviour in gender studies differs from that of authors in PNAS. The pattern of gender studies reflects associations between authors of different productivity, or “masters” and “apprentices” but the PNAS pattern reflects associations between authors of roughly the same productivity, or “peers”. It would be interesting to extend the analysis of these three-dimensional collaboration patterns further, to see whether a similar characterization holds, what it might imply about the patterns of authorship in different areas, what those patterns might imply about the role of collaboration, and whether there are differences between females and males in collaboration patterns.
Hanning, G, Kretschmer, H, Liu, Z. Distribution of co-author pairs ‘frequencies of the Journal of Information Technology. COLLNET Journal of Scientometrics and Information Management 2008 2 1 73–81.
Kretschmer, H. Similarities and dissimilarities in co-authorship networks; gestalt theory as explanation for well-ordered collaboration structures and production of scientific literature. Library Trends 2002 50 3 474–497.
Kretschmer, H, Aguillo, IF. Visibility of collaboration on the Web. Scientometrics 2004 61 3 405–426 .
Kretschmer, H, Kretschmer, T. Lotka's distribution and distribution of co-author Pairs’ frequencies. Journal of Informetrics 2007 1:308–337 .
Kretschmer, H., & Kretschmer, T. (2009). Invited keynote speech. Who is collaborating with whom? Explanation of a fundamental principle. In: H. Hou, B. Wang, S. Liu, Z. Hu, X. Zhang, M. Li (eds.), Proceedings of the 5th International Conference on Webometrics, Informetrics and Scientometrics and 10th COLLNET Meeting, 13–16 September 2009, Dalian, China (CD-ROM for all participants and for libraries).
Kundra, R, Beaver, D, Kretschmer, H, Kretschmer, T. Co- author pairs’ frequencies distribution in journals of gender studies. COLLNET Journal of Scientometrics and Information Management 2008 2 1 63–71.
Naldi, F., Parenti, I.V. (2002). Scientific and technological performance by gender: a feasibility study on patent and bibliometric indicators. Vol. II: methodological report. European Commission Research, EUR 20309.
Naldi, F, Luzi, D, Valente, A, Parenti, IV 2004 Scientific and technological performance by gender HF Moed eds. et al. Handbook of quantitative science and technology research Kluwer Academic Publishers The Netherlands 299–314.
Newman, M. E. J. (2002). Assortative mixing in networks. Physical Review Letters, 89, 208701.
Newman, MEJ. Power laws, pareto distributions and Zipf's law. Contemporary Physics 2005 46 5 323–351 .
Otte, E, Rousseau, R. Social network analysis: a powerful strategy, also for the information sciences. Journal of Information Science 2002 28:443–455 .
Pepe, A, Marko, AR. Collaboration in sensor network research: an in-depth longitudinal analysis of assortative mixing patterns. Scientometrics 2009 84 3 687–701 This article is published with open access at Springerlink.com.
Price, D. de Solla (1963). Little science, big science. New York: Columbia University Press.
Wasserman, S, Faust, K 1994 Social network analysis. Methods and applications Cambridge University Press Cambridge 1994 .