Abstract
This paper studies the production of dissertations in eight research fields in the natural sciences, the social sciences and the humanities. In using doctoral dissertations it builds on De Solla Prices seminal study which used PhD dissertations as one of several indicators of scientific growth (Price, Little science, big science, 1963). Data from the ProQuest: Dissertations and Theses database covering the years 1950–2007 are used to depict historical trends, and the Gompertz function was used for analysing the data. A decline in the growth of dissertations can be seen in all fields in the mid-eighties and several fields show only a modest growth during the entire period. The growth profiles of specific disciplines could not be explained by traditional dichotomies such as pure/applied or soft/hard, but rather it seems that the age of the discipline appears to be an important factor. Thus, it is obvious that the growth of dissertations must be explained using several factors emerging both inside and outside academia. Consequently, we propose that the output of dissertations can be used as an indicator of growth, especially in fields like the humanities, where journal or article counts are less applicable.
Similar content being viewed by others
Notes
History is often seen as a discipline on the border between the humanities and the social sciences.
In this case, sociology can be seen both as a pure field, sociological theories and models, as well as an applied field focusing on education of professionals and social work.
The data was gathered from two reports: Number of U.S. doctorates awarded rise for sixth year, but growth slower was used for the latest years and US doctorates in the twentieth century. Special report for the years 1950–2000.
References
Bazeley, P. (1999). Continuing research by PhD Graduates. Higher Education Quarterly, 53(4), 333–352.
Becher, T., & Trowler, P. R. (2001). Academic Tribes and territories: Intellectual enquiry and the culture of disciplines (2nd ed.). Buckingham: The Society for Research into Higher Education and Open University Press.
Bornmann, L., Mutz, R., & Daniel, H.-D. (2008). Are there better indices for evaluation purposes than the h index? A comparison of nine different variants of the h index using data from biomedicine. Journal of the American Society for Information Science and Technology, 59(5), 830–837.
Egghe, L., & Rao, I. K. R. (1992). Classification of growth models based on growth rates and its applications. Scientometrics, 25(1), 5–46.
Fernández-Cano, A., Torralbo, M., & Vallejo, M. (2004). Reconsidering Price’s model of scientific growth: An overview. Scientometrics, 61(3), 301–321.
Gupta, B. M., & Karisiddappa, C. R. (2000). Modelling the growth of literature in the area of theoretical population genetics. Scientometrics, 49(2), 321–355.
Han, C.-s., Lee, S. K., & England, M. (2010). Transition to postmodern science-related scientometric data. Scientometrics, 84(2), 391–401. doi:10.1007/s11192-009-0119-6.
Hartwich, K., & Fick, E. (1993). Hopf bifurcations in the logistic map with oscillating memory. Physics Letters A, 177(4–5), 305–310. doi:10.1016/0375-9601(93)90005-K.
Larviére, V., Archambault, E., Gringas, Y., & Gagné, V. (2006). The place of serials in referencing practices: Comparing natural sciences and engineering with social sciences and humanities. Journal of the American Society for Information Science and Technology, 57(8), 997–1004.
Leydesdorff, L. (2009). How are new citation-based journal indicators adding to the bibliometric toolbox? Journal of the American Society for Information Science and Technology, 60(7), 1327–1336.
Lundberg, J. (2007). Lifting the crown—citation z-score. Journal of Informetrics, 1(2), 145–154. doi:10.1016/j.joi.2006.09.007.
Mabe, M., & Amin, M. (2001). Growth dynamics of scholarly and scientific journals. Scientometrics, 51(1), 147–162.
Morris, A., & van Der Veer, M. (2008). Mapping research specialities. Annual Review of Information Science and Technology 2, 42(1), 213–295.
Price, D. J. de Solla (1963). Little science, big science (p. 119). New York, NY: Columbia University Press.
R Development Core Team. (2010). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing.
Ritz, C., & Streibig, J. C. (2005). Bioassay analysis using R. Journal of Statistical Software, 12(5).
Thurgood, L., Golladay, M. J., & Hill, S. T. (2006). U.S. doctorates in the 20th century: Special report. National Science Foundation: Division of Science Resources Statistics.
Tsoularis, A., & Wallace, J. (2002). Analysis of logistic growth models. Mathematical Biosciences, 179(1), 21–55.
Whitley, R. (1984). The intellectual and social organization of the sciences. Oxford: Clarendon Press.
Wood, J. B. (1988). The growth of scholarship—An online bibliometric comparison of dissertations in the sciences and humanities. Scientometrics, 13(1–2), 53–62.
Acknowledgments
The authors wish to acknowledge the role of the Nordic Research School in Library and Information Science (NORSLIS) for initiating collaboration between researchers in the Nordic and Baltic countries.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Andersen, J.P., Hammarfelt, B. Price revisited: on the growth of dissertations in eight research fields. Scientometrics 88, 371–383 (2011). https://doi.org/10.1007/s11192-011-0408-8
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11192-011-0408-8