The new NSF program

Loet Leydesdorff loet at LEYDESDORFF.NET
Sun Feb 25 03:00:17 EST 2007


http://www.nsf.gov/pubs/2007/nsf07547/nsf07547.htm:

The Directorate for Social, Behavioral and Economic Sciences (SBE) at the
National Science Foundation (NSF) aims to foster the development of the
knowledge, theories, data, tools, and human capital needed to cultivate a
new Science of Science and Innovation Policy (SciSIP).  SciSIP will
underwrite fundamental research that creates new explanatory models and
analytic tools designed to inform the nation's public and private sectors
about the processes through which investments in science and engineering
(S&E) research are transformed into social and economic outcomes.  Parallel
research and data development will help answer pressing questions, such as:
What are the critical elements of creativity and innovation?  What are the
likely futures of the technical workforce and what is its response to
different forces of change? What is the impact of globalization on
creativity and productivity in the science and engineering fields?  Are
there significantly different outcomes from federal and private investments
in R&D and innovative activities?  How does state support for public
universities influence the national innovation system?  

SciSIP's goals are to understand the contexts, structures and processes of
S&E research, to evaluate reliably the tangible and intangible returns from
investments in research and development (R&D), and to predict the likely
returns from future R&D investments within tolerable margins of error and
with attention to the full spectrum of potential consequences. Specifically,
the research and community development components of SciSIP's activities
will:  (1) develop usable knowledge and theories of creative processes and
their transformation into social and economic outcomes; (2) develop, improve
and expand models and analytical tools that can be applied in the science
policy decision making process; and (3) develop a community of experts at
academic institutions focused on SciSIP.  Characterizing the dynamics of
discovery and innovation is important for developing valid metrics, for
predicting future returns on investments, for constructing fruitful
policies, and for developing new forms of workforce education and training. 

Accomplishing these goals requires disciplinary and interdisciplinary
approaches to understanding knowledge generation and innovation processes.
Collaborative projects are encouraged, including those that build linkages
across disciplinary and national borders.  Research teams may also focus on
specific scientific domains or synthesize elements from disparate
disciplines to develop new models or tools.  For example, engineers and
behavioral scientists could collaborate on projects furthering the
understanding of cognitive pathways and interaction strategies that lead to
new discoveries, or on optimizing team strategies in the innovative process.
Chemists working with social and behavioral scientists might develop
theoretical frameworks that explain how chemists achieve new discoveries.
Mathematical biologists, behavioral scientists and economists might develop
computational models on how social agents might make strategic investments
in incremental or large-leap innovations.  In a different vein, a
multidisciplinary research team might be instrumental in investigating first
hand the productivity benefits and costs of interdisciplinary team
collaborations.   

The FY 2007 competition includes two emphasis areas:  Analytical Tools and
Model Building.  The emergent body of research will develop and utilize
techniques for retrospective and prospective analyses.  In addition,
research will provide insight into factors that propagate new ideas at
levels from the molecular functioning of the human brain to the
organizational, and at the state, national and international levels.  Future
solicitations will also target research that would improve and expand
science metrics and datasets.

The research objectives go beyond the traditional input-output linkages, to
broader outcomes, such as implications for national health, security,
education, and well-being.  New statistical and econometric tools for
estimating social and economic returns to science and engineering
investments are encouraged, including comparisons of public and private R&D
expenditures and returns within a given scientific discipline or field.  The
research is not limited to quantitative assessments.  Qualitative tools,
such as case studies, ethnographic studies, historical analyses and
cross-national comparisons are welcomed and interdisciplinary collaborations
are encouraged.  International collaboration among scholars is also
encouraged, since much can be learned about country-based methods of
scientific exploration and science policies, particularly as the scientific
community globalizes.  Collaborators from institutions outside the U.S.
should seek funding from their respective funding organizations or they
could be supported through a subcontract to a U.S. institution. 
 
________________________________

Loet Leydesdorff 
Amsterdam School of Communications Research (ASCoR)
Kloveniersburgwal 48, 1012 CX Amsterdam
Tel.: +31-20- 525 6598; fax: +31-20- 525 3681 
loet at leydesdorff.net <mailto:loet at leydesdorff.net> ;
http://www.leydesdorff.net/ <http://www.leydesdorff.net/>  

 
Now available: The Knowledge-Based Economy: Modeled, Measured, Simulated
<http://www.universal-publishers.com/book.php?method=ISBN&book=1581129378> .
385 pp.; US$ 18.95 
 
 



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