This Week’s Discoveries | 5 December 2017
- Jian Wang
- Almut Schüz
- dinsdag 5 december 2017
Niels Bohrweg 2
2333 CA Leiden
- De Sitterzaal
Bias against novelty in science: A cautionary tale for users of bibliometric indicators
Jian Wang (LIACS, SBB)
Jian is an assistant professor at the Science Based Business Program, Leiden Institute of Advanced Computer Science (LIACS). He studies science and innovation and in particular the interface between them, integrating various disciplinary perspectives, such as economics, sociology, management, and public policy. His recent research focuses on novelty in science and innovation, factors stimulating novel research, such as funding schemes and team/network structure, and the translation of science into innovation.
'We examine the combinatorial novelty of scientific publications and its relationship with citation impact. We find that novel publications demonstrate a high risk/high gain profile: novel papers are more likely to be among the top 1% highly cited papers in the long run, to inspire follow on highly cited research, and to be cited in a broader set of disciplines, but at the same display a higher variance in their citations. We also observe delayed recognition of novel papers which are less cited in the short run. In addition, novel research is more highly cited in "foreign" fields but not in their "home" field. Finally, novel papers are published in journals with a lower impact factor, compared with non-novel papers, ceteris paribus.'
- Wang, J., Veugelers, R., & Stephan, P. E. (2017). Bias against novelty in science: A cautionary tale for users of bibliometric indicators. Research Policy, 46(8), 1416-1436. https://doi.org/10.1016/j.respol.2017.06.006
- Stephan, P. E., Veugelers, R., & Wang, J. (2017). Blinkered by bibliometrics. Nature, 411-412. https://doi.org/10.1038/544411a
Second Lecture, Lorentz Center highlight
What the structure of the cortex tells us about its particular function
Almut Schüz, (Max-Planck-Institute for Biological Cybernetics, Tübingen)
Almut is professor at the Max-Planck-Institute for Biological Cybernetics in Tübingen. Her research area is Brain Research, by way of quantitative-neuroanatomical methods in connection with brain theory. Her main research topic is the structure and function of the cerebral cortex.
'The cerebral cortex is responsible for the large variety of higher cognitive functions, such as learning, thinking, perception, language etc. I will give a brief insight into its connectivity, based on our quantitative neuroanatomical studies. They show why this part of the brain provides the ideal basis for associations as required for higher cognitive functions.'