This document discusses the need to rebalance science and technology (STI) indicators to better capture the intrinsic value of STI beyond just economic impacts. It notes that STI statistics have become overly focused on the instrumental economic value of innovation. The document also examines expectations for the OECD's role in STI indicators, including considering contributions from a wider variety of scientific fields, advancing understanding of knowledge production processes beyond national impacts, and characterizing professional practice-based research. It emphasizes that innovation is a collective and cumulative process requiring long-term investment in education and research.

1. 1
Paul Gauguin,: D'où Venons Nous / Que Sommes Nous / Où Allons Nous. 1897
Museum of Fine Arts in Boston, Massachusetts, USA
What do we need to measure to foster “Knowledge as Our Common Future”?
Where Do We Come From? What Are We? Where Are We Going?

2. About OECD STI statistics:
“Statistics are among the most visible
and most extensively-used outputs of the
OECD. If the OECD were to close its doors
tomorrow, the drying up of its statistics
would probably make a more rapid and
bigger impact on the outside world than
the abandonment of any of its other
activities”
Robert Chabbal (1994)
Why we need the role of OECD to continue to be relevant in the area of S&T indicators?

3. Part 1: an overall observation/assessment
1. the number of indicators has exploded;
2. the pendulum has swung excessively towards the economic
dimension;
3. Following Freeman and Soete (2007): “the link between the
measurement of national STI activities and their national economic
impact (while always subject to debate, particularly within the context
of small countries), has now become so loose that national STI
indicators are in danger of no longer providing relevant economic
policy insights”
In other words, S&T statistics have moved excessively
towards capturing the “instrumental” value of S&T and
innovation (i.e., STI) and a rebalancing is required to fully
capture the “intrinsic” value of S&T and innovation.

4. 4
Some fifty years after John Ziman launched the discussion on
Public Knowledge and forty years after his work on Reliable
Knowledge, to appreciate the significance of scientific
knowledge one must understand the nature of science as a
complex whole. In Real Science, we are reminded that
“science is social”, referring to “the whole network of social
and epistemic practices where scientific beliefs actually
emerge and are sustained”.
J. Ziman (1968), Public Knowledge: The Social Dimension of Science,
Cambridge University Press
J. Ziman (1978), Reliable Knowledge: an exploration of the grounds for belief in science,
Cambridge University Press
J. Ziman (2000), Real Science: What it is, and what it means,

5. 'CPLP Conferência de C&T e Ensino Superior' (Lisboa, 29 de Agosto de 2009)
The need to consider 3 main issues:
• Scientific organizations
• Scientific culture
• Scientists
… and, always, political debate with scientists!
"Science is about pursuing
the truth:
proof, not authority;
it's about knowledge, not
ignorance; it's about
technical training,
not definitions..”
José Mariano Gago, 2014

6. …"Science is a battle ground, it's not
neutral. And if you know it's not neutral, it
becomes interesting. It can become part of
the modern youth culture. You must
choose between generosity and greed,
between peace and war, and choose
between disclosing or hiding the truth”…
José Mariano Gago, 2014

7. 1. Defining “measurement standards” (i.e., Frascati, Oslo, Canberra
Manuals): requires continuous work in connection with education and
skills statistics and the emergence of global research networks;
what governments and policy makers expect from OECD ?
2. Compiling statistical information produced by national statistics
offices, based on those Manuals (e.g., MSTI): requires better
addressing the basic issues of advanced training, recruitment,
mobility and employment of scientist and engineers at a global level,
to better understand knowledge production and absorption processes
beyond national impacts;
3. Building an “indicators production infrastructure” in STI: requires
entering directly in “international data collection”, to be supported in
panels of representatives of R&D and higher education institutions,
STI policymakers, and individual researchers, making use of online
survey techniques to get rapid responses;
4. Teaching and helping the users of indicators: to better understand
the differences between events and occurrences.

8. Expectations from the 3rd OECD Blue Sky Forum (1)
…a throughout revision of OECD STI statistics with emphasis on
unexplored but relevant areas of knowledge:
• Emphasizing the role of research and education beyond driving
innovation for sustainable productive economic growth;
• promoting a culture of learning and knowledge;
• driving better public services, improving health, prosperity and the
quality of life, and protecting the environment.
1. “production-side” of indicators: consider
contributions from a wider variety of scientific
backgrounds to better reflect a complex web of
impacts that go well beyond economic aspects;
2. “user-side” of indicators: advancements how to
safely navigate in existing OECD data sets;

9. Expectations from the 3rd OECD Blue Sky Forum (2)

10. After many years hit by recession and economic
and budgetary problems:
- Which is the evolving path of R&D funding?
- Which policies to foster knowledge
towards long-term growth?
Parte II: on emerging Policy Questions…
…today!

11. …facing many myths!
How can we effectively help debunking
these myths and guarantee better
policies?
Public vs private
R&D vs innovation
Higher education vs training labor
…we live on times of increasing
socialization of risks and the
privatization of rewards

12. Francisco de Goya, 1797-1799
El sueño de la razon produce monstruos, Museo del Prado
1. Research assessment practices
and scientific careers, together
with “open science”:
• call for a major action of
OECD to characterize those
processes and guarantee
the adoption of best
practices worldwide;
• Conduct survey, discuss
new indicators and develop
a user manual
After Ottawa 2006:
• San Francisco Declaration, 2012
• DFG, 2013
• Leiden Manifesto, 2014

13. 2. Migratory flows of highly skilled human resources:
• The systematic provision of official data on
migratory flows of highly skilled human resources
around the world, including intra-European data, in
order to guide policy making to better balance brain
circulation and migratory flows of skilled people,
including the critical need to better consider and
measure incentives;
• The provision of data on refugees, students and
scholars who belong to communities and/or
countries at risk in need of humanitarian assistance,
to foster a Rapid Response Mechanism for Research
and Higher Education in Emergencies;

14. 3.Practicesandinstitutionstodiversify
researchandeducation:practicebased
research&intermediaries
Seringueiros, 1938
Candido Portinari, 1903-1962

16. Design Thinking
Human-centred policies towards capabilities development
Design
Development
Capabilities
Production
Capabilities
Design Process
Development
Production
Experience
Knowledge Required
for Design Process Development
Knowledge about
Production Problems
and Conditions
Learning before
Doing
Learning by Doing
Capabilities Required
for Production
New Process
Technology
...diversfiy research profiles, promoting practice-based research together with problem-based
learning, to foster industry-science relationships and innovation!

17. 3. Practices and institutions to diversify research and education
• adequate characterization of “professional practice-
based research” oriented towards professional
developments, in order to guide policymaking, as
well as training students for new jobs, which
requires building distinct learning and research
profiles that are increasingly problem-oriented and
research-based;
• institutional diversification, together with data on
connectivity, links and associations among public
and private institutions and new institutional
players and employers and related risk-sharing
mechanisms to foster skilled job creation.

18. How do people
understand science?
How do they feel about
science, how do they
relate to it, what do
they hope from it and
what do they fear
about it?
4. participatory processes of R&D agenda setting
From the public understanding of
science, to participatory R&D
agenda setting…

19. 19
Relevance : stakeholder engagement for community building
4. participatory processes of R&D agenda setting
• Requires new theoretical advancements
• Conduct survey, discuss new theoretical
advancements and develop a user manual

20. Expectations from the 3rd OECD Blue Sky Forum (3)

21. Francisco Díaz Carreño, 1890
“Posición probable del globo antes del diluvio”
Museo del Prado
Why Science and Innovation?
The future requires addressing two key emerging
issues everywhere:
• EXTERNAL – multilateral:
– Multiply global R&D and HE networks
– Develop international R&D
organisations and programmes
– Promote the international debate for
new research agendas
• INTERNAL:
– Better understanding of “policy mix”:
• Exploration and exploitation
• Extended BERD across small,
medium and large companies
• The key role of local productive
arrangements for global markets
– Invent jointly new economic drivers
– Diversify and combine funding sources
Public Policy is critical:
but, how far can we rely in STI indicators
to help building a common vision of the
future of STI?
… indicators for a
curiosity-driven, knowledge-
based, learning society?

23. annexes

24. World share of GDP and GERD for the G20
over the last decade (2002-2012); values in %

25. Cumulative R&D expenditure, 30 years, per RESEARCHER
(thousands U.S. Dollars 2005 constant prices and PPP)
Source: OECD Statistics.
0
1000
2000
3000
4000
5000
6000
CumulativeGrossDomesticExpenditureonR&Dper
researcher(thousandsUSDollars2005constantpricesand
PPP)
United States EU-28
Undoubtedly there was considerable
progress in Science, Technology and
Higher Education.
…But Europe, as a whole, has met
neither its goals nor its promises in
this area.

26. Government Budget Appropriations or Outlays for R&D (GBOARD)/capita - 1995
(Purchasing Power Standard (PPS) per inhabitant at constant 2005 prices)
Source: Eurostat

27. Government Budget Appropriations or Outlays for R&D (GBOARD)/capita - 2000
(Purchasing Power Standard (PPS) per inhabitant at constant 2005 prices)
Source: Eurostat

28. Government Budget Appropriations or Outlays for R&D (GBOARD)/capita - 2005
(Purchasing Power Standard (PPS) per inhabitant at constant 2005 prices)
Source: Eurostat

29. Government Budget Appropriations or Outlays for R&D (GBOARD)/capita - 2009
(Purchasing Power Standard (PPS) per inhabitant at constant 2005 prices)
Source: Eurostat

30. Government Budget Appropriations or Outlays for R&D (GBOARD)/capita - 2010
(Purchasing Power Standard (PPS) per inhabitant at constant 2005 prices)
Source: Eurostat

31. Government Budget Appropriations or Outlays for R&D (GBOARD)/capita - 2011
(Purchasing Power Standard (PPS) per inhabitant at constant 2005 prices)
Source: Eurostat

32. Government Budget Appropriations or Outlays for R&D (GBOARD)/capita - 2012
(Purchasing Power Standard (PPS) per inhabitant at constant 2005 prices)
Source: Eurostat

33. Government Budget Appropriations or Outlays for R&D (GBOARD)/capita - 2013
(Purchasing Power Standard (PPS) per inhabitant at constant 2005 prices)
Source: Eurostat

34. Government Budget Appropriations or Outlays for R&D (GBOARD)/capita - 2014
(Purchasing Power Standard (PPS) per inhabitant at constant 2005 prices)
Source: Eurostat

35. Government Budget Appropriations or Outlays for R&D (GBOARD)
Sample of large EU countries
(million current PPP $)
Source: OECD; Netherlands is included in the large sized countries because of the size of the budget
0
5000
10000
15000
20000
25000
30000
35000
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
GBOARD,MillionsofUSDollars,currentPPP$
France Germany Italy Netherlands Poland Spain United Kingdom
In the year 2000, Germany and France presented
similar national R&D budgets; one decade later,
Germany outpaces France by 50%. Italy budgets have
declined since 2007, and in real terms are 15% lower
than in 2000.
…the quasi stagnation of R&D public investment
in Europe during the last decade hides a major
trend of internal divergence inside Europe
itself.

36. …but,
what has
changed?

37. Note: total number of PhD’s (vertical) and the yearly number of new PhD’s (horizontal) by
10.000 inhabitants. Source: OECD
“Stock” versus “Flux” of doctorates: 2004-2012

38. The 500 largest EU firms investing in R&D
(Following ICB - Industry Classification Benchmark; Source: EU Industrial R&D Investment Scoreboard
0
20000
40000
60000
80000
100000
120000
140000
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
MillionsofEuros
Automobiles & Parts Pharmaceuticals & Biotechnology Technology Hardware & Equipment
Aerospace & defence Industrial Engineering Electronic & Electrical Equipment
Banks Software & Computer Services Chemicals
Oil & Gas

39. 0.0009
0.001
0.0011
0.0012
0.0013
0.0014
0.0015
0.0016
0.0017
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
France Germany Italy Poland Spain UK
Levels of diversification of economic struture: 1980-2010
Large countries
(Inverse Hirshman-Herfindahl Index)
Data Source: OECD

40. Total exports versus R&D accumulated expenditure per capita
(millions of U.S. Dollars 2005 constant prices and PPP)
Source: OECD

41. Europe presents a large diversity in
R&D investment and accumulation
across countries,
with an average cumulative R&D
expenditure per researcher about 50%
smaller than in USA.
A critical observation - 1:

42. A critical observation - 2:
In many other EU countries, beyond notable
exceptions (including Germany), the stagnation
and/or recent decrease in public R&D and HE
budgets has been justified by the need to
change policies, including:
• Increase public funding to support firms and
business activities;
• Increase the selectivity of public funding,
decreasing public support for advanced
training and scientific employment.

43. Emerging major EU vulnerabilities:
• New migratory flows of skilled people:
…the growing scientific and technological
capacity of less industrialized regions is now
associated with, also, a growing vulnerability
associated with a increasing international
competition for skilled human resources.
• High rates of young unemployment:
…weak new job creation in less industrialized
regions.
• Accelerated rate of aging of population…

44. Science, its impact and the presence of
innovation, result from a cumulative, long-term,
collective and uncertainty process, involving an
extensive divison of labour, which requires
massifying the training of human resources and
qualifying the labour force in many economic
sectors, in a way that depends on the structure
of the economy
A new hypothesis:
Public Policy is critical:
but, is there room for a common vision of the future of S&I?

45. Ziman takes
government funding
of science as a given,
because the market
cannot be trusted to
allocate resources
wisely and, anyway,
research now costs
so much that only
government can pay
the bill.

46. the process matters!…
The continuous development of R&D and Higher
Education requires counter-cycle policy measures,
with emphasis on the advanced training of human
resources and the systematic opening of the social
basis for education and science across all EU.
Innovation must be considered a collective and
cumulative process