Loading in 2 Seconds...
Loading in 2 Seconds...
New leading sciences and the changing boundaries between public and private. Andrea Bonaccorsi University of Pisa Member of the High Level Expert Group on Maximizing the wider benefit of basic research and the European Research Council European Commission, DG Research
New leading sciences and the changing boundaries between public and private
University of Pisa
Member of the High Level Expert Group on
Maximizing the wider benefit of basic research and the European Research Council
European Commission, DG Research
Six countries programme
Rotterdam, April 21, 2005
The new scientific landscape: the emergence of new leading sciences
The performance of European science in new leading sciences
Moving boundaries between public and private
A new scientific landscape has taken shape in the last 20 years or so. It results from the combination of several revolutionary advances:
- the molecular biology revolution, particularly after the recombinant DNA discovery and the development of PCR;
- the pervasive information technology revolution, resulting from advances in algorithms, computer science, microelectronics, and more recently from the convergence with telecommunication;
- new advances in materials science;
- new opportunities in nanotechnology, particularly after the invention of resonance microscopy.
Rate of growth
- fast growing vs slow growing
Degree of diversity
- convergent dynamics vs divergent dynamics
Level of complementarity
- physical infrastructure vs. human capital and
New leading sciences(materials science, life sciences, computer science, incl. biotech and nanotech): fast growing, divergent dynamics, human capital and institutional complementarity
HLEG: definition offrontier research.
Source: Bonaccorsi and Thoma (2005)
Number of occurrences of the word “Genetic algorithm” in the publications of the top 1000 scientists in computer science
Number of occurrences of the word “Neural network” in the publications of the top 1000 scientists in computer science
Number of occurrences of the word “Wireless” in the publications of the top 1000 scientists in computer science
Number of occurrences of the word “Atomic force microscope” in the publications of the top 1000 scientists in high energy physics
Number of occurrences of the word “Hadron collider” in the publications of the top 1000 scientists in high energy physics
Total number of keywords and number of newly-appearing keywords in publications of top 1000 high energy physicists
Total number of keywords and number of newly-appearing keywords in publications of top 1000 computer scientists
Ratio between newly appearing keywords and total number of keywords in high energy physics and computer science
High energy physics
First, scientific fields grow at very different rates after entry. As a first broad distinction, there are fields that grow extremely rapidly and fields characterized by slow growth after entry. Post-entry growth rates sharply differ.
Second, disciplines largely differ in the composition of fields characterized by different rates of growth. In some disciplines it seems that new fields are generated continuously, so that the turnover ratio is extremely high, while in other disciplines the turnover is much lower.
Units of analysis: research programme (Lakatos) combined with the network of socio-technical constructs (Callon-Latour-Laredo-Pickering).
Levels of diversity:
2. Research question, goal or problem
3. Experimental technique and equipment
4. Object or locus of observation
Diversity may take place at any level.
Because diversity is defined across all levels, our definition does not overlap with diversity in paradigms.
Paradigmatic change takes place mainly at the level of theories and research questions.
Within the same paradigm we may observe large diversity due to
- the use of different experimental infrastructure, with the associated procedures, practices and localized learning processes
- the selection of different objects or loci of observation, corresponding to different sub-hypotheses within the same general paradigm.
e.g. HIV, Alzheimer, molecular oncology, nanotechnology, computer languages, computational chemistry
Concentration of keywords in publications of top 1000 scientists in Computer science and High energy physics
Number of publications of top 1,000 scientists 9,062 41,770
Number of publications with keywords 6,401 34,379
Publications with keywords (%) 71% 82%
Number of different keywords 18,031 50,952
Average number of keywords per author 5.35 5.44
Concentration ratio (C250)* 26.5% 29.3%
* Cumulative market share of top 250 keywords (Number of occurrences ofthe top 250 keywords/ total number of occurrences in all publications)
Relative frequency of top keywords in High energy physics and Computer science
Plot of rank correlation of top 250 keywords in High energy physics (r=.79)
Plot of rank correlation of top 250 keywords in Computer science (r= .49)
(a) European science is strong in fields characterized by convergent search regimes and weak in fields characterized by divergent search regimes.
(b European science is strong in fields characterized by high levels of infrastructural complementarities while it is much less prepared in fields characterized by human capital and institutional complementarities.
(c) Consequently, European science is strong in fields characterized by slow growth and weak in fields characterized by turbulent growth.
(d) European science is only quantitatively comparable to US science but is weaker in the overall quality and is severely under-represented in the upper tail of scientific quality.
(Revealed Comparative Advantages, 1981-1994)
In materials science EU-15 produce 40,108 papers and receive 83,748 citations, while NAFTA produce 31,620 papers but receive 106,841 citations In the life sciences EU-15 produce 616,212 papers and US 529,608 in the period 1995-1999, but the citation impact (1993-1999) is 1.35 in USA and only 0.90 in EU-15 In computer science the citation impact (1993-1999) is 1.33 for Israel, 1.17 for US, but only in the range between 0.81 (Germany) and 0.95 (Italy) for the four largest countries Source: Third European Report on S&T Indicators (2003)
A divergent search regime
a dynamics of proliferating research programmes,often generated within the same paradigm,that increase the diversity of the fieldin terms of hypotheses, experimental techniques, objects of investigation.European science is strong in fields characterized by convergent search regimes and weak in fields characterized by divergent search regimes
A search regime characterized by new forms of complementarities
Not much physical infrastructure complementarity (big science)
But: - human capital complementarity
- institutional complementarity
European science is strong in fields characterized by high levels of infrastructural complementarities while it is much less prepared in fields characterized by human capital and institutional complementarities.
European science has developed separate institutions at national, intergovernmental and European level, for dealing with search regimes with strong physical infrastructure complementarities
(e.g. high energy physics, astronomy, space research, oceanography, nuclear technology).
It is much more difficult to provide emerging fields the required complementarities in terms of human capital within the common institutional framework.
There are few rapid growth mechanisms.
European science is strong in fields characterized by slow growth and weak in fields characterized by turbulent growth
Data on the most cited scientists worldwide have been recently made available by ISI on the basis of the analysis of 19 million papers in the period 1981-1999, authored by 5 million scientists.
They refer to around 5,000 scientists worldwide in all fields, selected as those 250 that receive the largest number of total citations in any subject area (0.1% of the total).
In all 21 fields US scientists largely dominate, with a proportion of highly cited scientists ranging from 40% in pharmacology and agricultural sciences to over 90% in economics/business and social sciences and an average around 60-70% of the total.
Among the 21 areas, only in other three areas non-US countries represent more than 40% of the total: physics, chemistry and plant and animal science (see Basu, 2004).
US scientists dominate in each of the 21 subject areas of science
Institutions awarding degrees of the top 1,000 scientists in Computer science. Top 10 list
Bachelor Master PhD
MIT University of CaliforniaUniversity of California
University of CaliforniaMITStanford University
Indian Institute of
UniversityHarvard UniversityHarvard University
Harvard UniversityUniversity of MassachusettsUniversity of Illinois
Cambridge UniversityCornell UniversityCarnegie-Mellon University
Yale UniversityCarnegie-Mellon UniversityCornell University
University of Michigan University of IllinoisUniversity of Michigan
UniversityPurdue UniversityUniversity of Wisconsin
California Institute of University of Michigan University of Texas
Plot of rate of growth (average number of personnel per each year of life, T_PERS/INSTAG) against size (number of personnel, T_PERS). CNR 1957-1997
Source: Bonaccorsi and Daraio (2003)
Plot of rate of growth (average number of researchers per each year of life, T_RES/INSTAG) against size (number of researchers, T_RES). CNR 1957-1997
Source: Bonaccorsi and Daraio (2003)
Traditional rationale for public intervention- market failures in the provision of quasi-public goods
(Nelson, 1959; Arrow, 1962).
Criticism to the linear model of science-technology interaction (Rosenberg, 1976; 1982; Kline and Rosenberg’s chain-linked model)
The problem of increasing returns, path-dependence and the public role as variety-preserving (Callon).
The notion of innovation as unfolding process and the public role against system failure (Metcalfe, 2005).
Under divergent search regimes, the trade-off between exploration and exploitation is not sustainable for private firms in the long run.
Private investment is not interested in reducing variety (Callon).
Rather, it is aimed to maximize the potential for exploration and the ability to absorb external knowledge via the acquisition of access rights.
Divergence forces a redefinition of the division of innovative labour between private and public.
The redefinition of the division of labour between public and private (2)