Scientific Capabilities, Fitness & Complexity
Scientific Capabilities, Fitness & Complexity
Embedded Files
Measuring the quality of scientific research on the national scale is nowadays a common practice that can affect policymaking on funding allocations and scientific priorities. The gold standard in the field is to use metrics based on citation shares, possibly normalized to account for field differences. However, a purely citation-based approach fails to capture important aspects of the scientific system of a nation.
In this paper we study the average performance of nations and their temporal dynamics (for the period 2004-2012) in the space defined by three variables: scientific success as measured by citations, level of research funding and rate of international collaboration. We find significant differences among nations in terms of efficiency in turning (financial) input into bibliometrically measurable output, and we confirm that growth of international collaboration positively correlates with scientific success (with significant benefits brought by EU integration policies). Moreover, in this paper we cross correlate measures of national scientific success based on citation data by research papers and by patents, which respectively represent the influence of a scientific system on further advancements in science and on the introduction of new technologies. Our analysis highlights the presence of geo-cultural clusters of nations with similar innovation system features.
Relation between HERD/GDP and scientific success of nations, averaged over years 2000–2012.
Relation between internationalization and scientific success of nations, averaged over years 1996–2013.
Temporal trajectories of Science versus Technology relevance of nations over years 1998−2012.
In this seminal paper we reveal two key features of national research systems.
First, nations do not specialize in a few research fields, but tend to diversify their activity into as many fields as possible. This pattern is explained by the capability model. Similarly to what happens with technological innovation and economic growth, scientific progress requires appropriate capabilities in terms of human capital, resources, knowledge, technologies, infrastructures, and so on. Each nation hosts a different set of capabilities and is active (or competitive) in all research fields enabled by these capabilities. Therefore, the scientific output of a nation reflects the set of relevant capabilities available. Since capabilities are heterogeneously distributed, nations have a heterogeneous level of diversification.
Second, while nations with many capabilities (typically, the developed economies) are competitive in almost all research fields, nations with fewer capabilities perform well only in a few fields with a lower degree of sophistication. Such a nested structure, induced by the capability scheme, indicates the presence of a competitive mechanism shaping the global research system – akin to what is observed in natural ecosystems or in human productive activities.
Overall, the nested pattern that emerges from the comparison of national research systems suggests that the diversification and composition of the scientific research basket can be used to measure the scientific competitiveness (or Fitness) of a nation; at the same time, the Complexity of a research field depends on its ubiquity and on the Scientific Fitness of nations that are competitive in that field. The Economic Fitness and Complexity (EFC) algorithm is the ideal tool to estimate the fixed point of this circular relation. In this paper we implemented a framework for quantifying scientific competitiveness by leveraging the EFC toolbox. We showed that the evolution of research systems can be properly described using two dimensions, Scientific Fitness and R&D expenditure.
Map of the Scientific Fitness of nations and of regions within selected areas, averaged over between 1998 and 2018.
In this paper we further reveal a trend of the nested structure of science that is becoming more and more modular, as the most developed nations become less active in the scientific fields of low complexity, where emerging countries acquire prominence. This observation is again explained by the capability model in the presence of resource constraints, resulting in a trade-off between the need to diversify in order to evolve and the need to allocate resources efficiently. Indeed,. collaborative patterns among developed countries reduce the necessity to be competitive in the less sophisticated research fields, freeing resources for the more complex ones.
Overall, our analysis points diversification out as the key element for nations to achieve a successful and competitive research system, suggesting that excellence comes out as a natural side effect of a heterogeneous and therefore healthy, system. Strategies targeting diversity, rather than excellence, are likely to be more effective.
Resources
G. Cimini, A. Zaccaria, A. Gabrielli. Investigating the interplay between fundamentals of national research systems: performance, investments and international collaborations. Journal of Informetrics 10(1), 200-211 (2016)
A. Patelli, G. Cimini, E. Pugliese, A. Gabrielli. The scientific impact of nations on scientific and technological development. Journal of Informetrics 11(4), 1229-1237 (2017)
G. Cimini, A. Gabrielli, F. Sylos Labini. The scientific competitiveness of nations. PLoS ONE 9(12): e113470 (2014)
A. Patelli, L. Napolitano, G. Cimini, A. Gabrielli. Geography of science: Competitiveness and inequality. Journal of Informetrics 17(1): 101357 (2023)
A. Patelli, L. Napolitano, G. Cimini, E. Pugliese, A. Gabrielli. Capability accumulation patterns across economic, innovation, and knowledge-production activities. Scientific Reports 13, 12988 (2023)
Blog posts by Il Fatto Quotidiano (in Italian)
Page updated
Google Sites
Report abuse