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A Few Special Cases: Scientific Creativity and Network Dynamics in the Field of Rare Diseases

  • Massimo Riccaboni
  • Maria Laura Frigotto

We develop a model of scientific creativity and test it in the field of rare diseases. Our model is based on the results of an in-depth case study of the Rett syndrome. Archival analysis, bibliometric techniques and expert surveys are combined with network analysis to identify the most creative scientists. First, alternative measures of generative and combinatorial creativity are compared. Then, we generalize our results and present a stochastic model of socio-semantic network evolution. The model predictions are tested with multiple networks of rare disease specialties. We find that new scientific collaborations among experts in a field enhance combinatorial creativity. Instead, high entry rates of novices are negatively related to generative creativity. By extending the set of useful concepts, creative scientists gain in centrality. At the same time, by increasing their centrality in the scientific community, scientists can replicate and generalize their results, thus contributing to a scientific paradigm.

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Paper provided by Department of Computer and Management Sciences, University of Trento, Italy in its series DISA Working Papers with number 2011/03.

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Length: 35 pages
Date of creation: Mar 2011
Date of revision: 24 May 2011
Handle: RePEc:trt:disawp:2011/03
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  1. Lambiotte, R. & Panzarasa, P., 2009. "Communities, knowledge creation, and information diffusion," Journal of Informetrics, Elsevier, vol. 3(3), pages 180-190.
  2. Lane, David, et al, 1996. "Choice and Action," Journal of Evolutionary Economics, Springer, vol. 6(1), pages 43-76, February.
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  5. David W. Galenson & Bruce A. Weinberg, 2001. "Creating Modern Art: The Changing Careers of Painters in France from Impressionism to Cubism," American Economic Review, American Economic Association, vol. 91(4), pages 1063-1071, September.
  6. Bruckner, E, et al, 1996. "Nonlinear Stochastic Effects of Substitution--An Evolutionary Approach," Journal of Evolutionary Economics, Springer, vol. 6(1), pages 1-30, February.
  7. Martin L. Weitzman, 1995. "Recombinant Growth," Harvard Institute of Economic Research Working Papers 1722, Harvard - Institute of Economic Research.
  8. Nigel Gilbert, 1997. "A Simulation of the Structure of Academic Science," Sociological Research Online, Sociological Research Online, vol. 2(2), pages 3.
  9. Orsenigo, L. & Pammolli, F. & Riccaboni, Massimo, 2001. "Technological change and network dynamics: Lessons from the pharmaceutical industry," Research Policy, Elsevier, vol. 30(3), pages 485-508, March.
  10. Rinia, E. J. & van Leeuwen, Th. N. & van Vuren, H. G. & van Raan, A. F. J., 1998. "Comparative analysis of a set of bibliometric indicators and central peer review criteria: Evaluation of condensed matter physics in the Netherlands," Research Policy, Elsevier, vol. 27(1), pages 95-107, May.
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