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THE SCIENCE OF SCIENCE

AND INNOVATION POLICY

HEARING

BEFORE THE

SUBCOMMITTEE ON RESEARCH AND SCIENCE 

EDUCATION 

COMMITTEE ON SCIENCE AND 

TECHNOLOGY 

HOUSE OF REPRESENTATIVES

ONE HUNDRED ELEVENTH CONGRESS

SECOND SESSION

SEPTEMBER 23, 2010

Serial No. 111–109

Printed for the use of the Committee on Science and Technology

(

Available via the World Wide Web: http://www.science.house.gov 
(II)

COMMITTEE ON SCIENCE AND TECHNOLOGY 

HON. BART GORDON, Tennessee, Chair 

JERRY F. COSTELLO, Illinois 

EDDIE BERNICE JOHNSON, Texas 

LYNN C. WOOLSEY, California 

DAVID WU, Oregon 

BRIAN BAIRD, Washington 

BRAD MILLER, North Carolina 

DANIEL LIPINSKI, Illinois 

GABRIELLE GIFFORDS, Arizona 

DONNA F. EDWARDS, Maryland 

MARCIA L. FUDGE, Ohio 

BEN R. LUJA ́ N, New Mexico 

PAUL D. TONKO, New York 

STEVEN R. ROTHMAN, New Jersey 

JIM MATHESON, Utah 

LINCOLN DAVIS, Tennessee 

BEN CHANDLER, Kentucky 

RUSS CARNAHAN, Missouri 

BARON P. HILL, Indiana 

HARRY E. MITCHELL, Arizona 

CHARLES A. WILSON, Ohio 

KATHLEEN DAHLKEMPER, Pennsylvania 

ALAN GRAYSON, Florida 

SUZANNE M. KOSMAS, Florida 

GARY C. PETERS, Michigan 

JOHN GARAMENDI, California 

VACANCY 

RALPH M. HALL, Texas 

F. JAMES SENSENBRENNER JR., 

Wisconsin 

LAMAR S. SMITH, Texas 

DANA ROHRABACHER, California 

ROSCOE G. BARTLETT, Maryland 

VERNON J. EHLERS, Michigan 

FRANK D. LUCAS, Oklahoma 

JUDY BIGGERT, Illinois 

W. TODD AKIN, Missouri 

RANDY NEUGEBAUER, Texas 

BOB INGLIS, South Carolina 

MICHAEL T. MCCAUL, Texas 

MARIO DIAZ-BALART, Florida 

BRIAN P. BILBRAY, California 

ADRIAN SMITH, Nebraska 

PAUL C. BROUN, Georgia 

PETE OLSON, Texas 

SUBCOMMITTEE ON RESEARCH AND SCIENCE EDUCATION

HON. DANIEL LIPINSKI, Illinois, Chairman 

EDDIE BERNICE JOHNSON, Texas 

BRIAN BAIRD, Washington 

MARCIA L. FUDGE, Ohio 

PAUL D. TONKO, New York 

RUSS CARNAHAN, Missouri 

VACANCY 

BART GORDON, Tennessee 

VERNON J. EHLERS, Michigan 

RANDY NEUGEBAUER, Texas 

BOB INGLIS, South Carolina 

BRIAN P. BILBRAY, California 

RALPH M. HALL, Texas 

DAHLIA SOKOLOV Subcommittee Staff Director 

MELE ́ WILLIAMS Republican Professional Staff Member 

MARCY GALLO Democratic Professional Staff Member 

BESS CAUGHRAN Democratic Professional Staff Member 

MOLLY O’ROURKE Research Assistant 
(III)

C O N T E N T S 

September 23, 2010

Page 

Witness List ............................................................................................................. 2

Hearing Charter ...................................................................................................... 3

Opening Statements

Statement by Representative Daniel Lipinski, Chairman, Subcommittee on 

Research and Science Education, Committee on Science and Technology, 

U.S. House of Representatives ............................................................................ 8

Written Statement ............................................................................................ 9

Statement by Representative Vernon J. Ehlers, Minority Ranking Member, 

Subcommittee on Research and Science Education, Committee on Science 

and Technology, U.S. House of Representatives ............................................... 10

Written Statement ............................................................................................ 12

Witnesses:

Dr. Julia Lane, Program Director of the Science of Science and Innovation 

Policy Program, National Science Foundation 

Oral Statement ................................................................................................. 13

Written Statement ............................................................................................ 14

Biography .......................................................................................................... 24

Dr. Daniel Sarewitz, Co-Director of the Consortium for Science, Policy & 

Outcomes and Professor of Science and Society, Arizona State University 

Oral Statement ................................................................................................. 24

Written Statement ............................................................................................ 26

Biography .......................................................................................................... 37

Dr. Fiona Murray, Associate Professor of Management, Technological Innovation & Entrepreneur Group, MIT Sloan School of Management 

Oral Statement ................................................................................................. 37

Written Statement ............................................................................................ 39

Biography .......................................................................................................... 50

Dr. Albert H. Teich, Director of Science & Policy Programs, American Association for the Advancement of Science 

Oral Statement ................................................................................................. 51

Written Statement ............................................................................................ 52

Biography .......................................................................................................... 55

Appendix 1: Answers to Post-Hearing Questions

Dr. Julia Lane, Program Director of the Science of Science and Innovation 

Policy Program, National Science Foundation .................................................. 66

Appendix 2: Additional Material for the Record

Statement of the California Healthcare Institute (CHI) submitted by Representative Brian P. Bilbray ............................................................................... 68

(1)

THE SCIENCE OF SCIENCE AND INNOVATION 

POLICY 

THURSDAY, SEPTEMBER 23, 2010

HOUSE OF REPRESENTATIVES, 

SUBCOMMITTEE ON RESEARCH AND SCIENCE EDUCATION

COMMITTEE ON SCIENCE AND TECHNOLOGY

Washington, DC.

The Subcommittee met, pursuant to call, at 2:07 p.m., in Room 

2325 of the Rayburn House Office Building, Hon. Daniel Lipinski 

[Chairman of the Subcommittee] presiding.
2
3

HEARING CHARTER

COMMITTEE ON SCIENCE AND TECHNOLOGY

SUBCOMMITTEE ON RESEARCH AND SCIENCE 

EDUCATION

U.S. HOUSE OF REPRESENTATIVES 

The Science of Science and Innovation Policy 

THURSDAY, SEPTEMBER 23, 2010

2:00 P.M.–4:00 P.M.

2325 RAYBURN HOUSE OFFICE BUILDING

1. Purpose 

On Thursday, September 23, 2010, the Research and Science Education Subcommittee will hold a hearing to examine the current state of science and technology policy research, how this research informs policymaking, and the role of the 

federal government in fostering academic research and education in this emerging 

interdisciplinary field.

2. Witnesses

• Dr. Julia Lane, Program Director of the Science of Science and Innovation 

Policy program, National Science Foundation.

• Dr. Daniel Sarewitz, Co-Director of the Consortium for Science, Policy & 

Outcomes, Arizona State University.

• Dr. Fiona Murray, Associate Professor of Management in the Technological 

Innovation & Entrepreneurship Group, MIT Sloan School of Management.

• Dr. Albert H. Teich, Director of Science & Policy Programs, American Association for the Advancement of Science.

3. Overarching Questions

• What is the ‘‘science of science policy?’’ How can science and technology (S&T) 

policy research contribute to and inform evidence-based local and national 

policy decisions? To what extent are science and technology policies in the 

United States being shaped by what has been learned from S&T policy research?

• What new and continuing areas of research in this area could significantly 

improve our ability to design effective programs and better target federal research investments? What are the most promising research opportunities and 

what are the biggest research gaps? Is the Federal government, specifically 

the National Science Foundation, playing an effective role in developing the 

science of science policy?

• What is the state of education in science and technology policy at U.S. universities? What are the backgrounds of students pursuing graduate degrees in 

S&T policy? What career paths are sought by science and technology policy 

program graduates? What are the fundamental skills and content knowledge 

needed by science and technology policy practitioners? Is the National Science 

Foundation playing an effective role in fostering the development of science 

and technology policy programs at U.S. universities?

4. Background 

During his keynote address in 2005 at the American Association for the Advancement of Science’s Science and Technology Policy Forum, Dr. John Marburger, then 

science advisor to President Bush, called for the establishment of a ‘‘science of 

science policy.’’ The ‘‘science of science policy’’ (SoSP) as described by Dr. Marburger 

and others includes the development of scientific theories, analytical tools, and rigorous datasets that will assist policymakers in science policy decisions. The SoSP 

is an interdisciplinary field that draws together researchers from economics, political science, and the social and behavioral sciences to improve our understanding 

of the science and engineering enterprise, including the process of innovation in an 
4

1The Science of Science Policy: A Federal Research Roadmap http://www.whitehouse.gov/

files/documents/ostp/NSTC%20Reports/39924¥PDF%20Proof.pdf

effort to establish a more quantitative approach to science and technology policy decisions. 

While most believe that science, technology, and innovation are critical to the 

competitiveness and prosperity of the United States, we lack the rigorous tools to 

quantify that relationship. Therefore, it remains difficult to actually measure the 

economic impact, social benefits, and effectiveness of federal research and development (R&D) investments. In addition to improving our ability to target federal R&D 

investments, research in the area of SoSP holds the potential to provide insight into 

the effect of globalization on the U.S. science and engineering workforce, increase 

our understanding of technology development and diffusion, communicate the social 

and economic benefits of R&D spending to the general public, and shed light on the 

process of creativity and innovation. 

In 2006, in response to Dr. Marburger’s call to action, an interagency working 

group, co-chaired by the National Science Foundation (NSF) and the Department of 

Energy, was formed within the Subcommittee on Social, Behavioral, and Economic 

Sciences under the National Science and Technology Council. The interagency working group conducted an assessment of the state of SoSP research and surveyed the 

Federal agencies about the tools, methods, and data they were using to make investment decisions. This work resulted in the release of a Federal SoSP research roadmap 1 in 2008. The roadmap outlines three broad themes and poses 10 research 

questions to be addressed by federally-funded SoSP research. 

Theme 1: Understanding Science and Innovation

Question 1: What are the behavioral foundations of innovation?

Question 2: What explains technology development, adoption, and diffusion?

Question 3: How and why do communities of science and innovation form and 

evolve?

Theme 2: Investing in Science and Innovation

Question 4: What is the value of the Nation’s public investment in science?

Question 5: Is it possible to ‘‘predict discovery’’?

Question 6: Is it possible to describe the impact of discovery on innovation?

Question 7: What are the determinants of investment effectiveness?

Theme 3: Using the Science of Science Policy to Address National Priorities

Question 8: What impact does science have on innovation and competitiveness?

Question 9: How competitive is the U.S. scientific workforce?

Question 10: What is the relative importance of different policy instruments in 

science policy?

Role of the National Science Foundation 

In 2006, NSF’s Directorate for Social, Behavioral and Economic Sciences (SBE) 

held three workshops to ask for recommendations and guidance from the research 

community about the breadth of activities that should be supported under an NSFfunded SoSP program. In 2007, NSF allocated $6.8 million for a new Science of 

Science and Innovation Policy (SciSIP) program. SciSIP supports both single investigators and collaborations in two areas. First, the program supports research on 

data and the improvement of science metrics, including research to improve our 

ability to identify, characterize, and measure returns on federal R&D investments. 

Second, the program supports research directed toward the development of models 

and other statistical tools as well as qualitative studies that will improve our understanding of the process of innovation and science outcomes, both societal and economic. In addition to supporting research, the program supports workshops, conferences, and symposia to help foster a community of researchers in the SciSIP area. 

NSF’s SciSIP budget request for fiscal year 2011 was $14.25 million, of which 

$8.05 million will be devoted to SciSIP research and community building activities 

through SBE’s Office of Multidisciplinary Activities and $6.2 million will be for the 

development of data survey tools through SBE’s Division of Science Resource Statistics (SRS). The data compiled by SRS for the biennial Science and Engineering Indi-
5

2What Indicators for Science, Technology and Innovation Policies in the 21st Century? Blue 

Sky II Forum—Background http://www.oecd.org/dataoecd/9/48/37082579.pdf 3http://www.oecd.org/document/22/0,3343,en¥41462537¥41454856¥44979734¥1¥1¥1¥

1,00.html

cators report serve a vital role in the SoSP as a long-term source of unbiased information about the science and engineering enterprise. 

NSF’s current efforts in SciSIP are not its first. From the 1970’s through the early 

1990’s NSF had a modest-sized staff carrying out policy research and analysis. 

These analysts worked in the Office of Research and Development Assessment, later 

the Division of Policy Research and Analysis (PRA), on specific tasks requested by 

the Office of Management and Budget, the Office of Science and Technology Policy, 

the Congressional Office of Technology Assessment, and other federal agencies. Additionally, PRA had a small budget to support academic research in areas directly 

relevant to their policy analysis tasks. In 1992, PRA was involved in a scandal over 

the faulty assumptions used to predict a looming shortage in engineers. The scandal 

led to an investigation by the Committee on Science & Technology and the dismantling of PRA.

STAR METRICS 

The National Science Foundation and the National Institutes of Health are currently collaborating on a project known as STAR METRICS (Science and Technology 

for America’s Reinvestment: Measuring the Effect of Research on Innovation, Competitiveness and Science), which is the first federal-university partnership to develop a data infrastructure that documents the outcomes of science investments for 

the public. An initial pilot project was recently completed with a handful of regionally and otherwise diverse institutions of higher education through the National 

Academies’ Federal Demonstration Partnership. The pilot project validated the initiative’s concept and its ability to collect relevant data from existing university databases. The full-scale project will proceed in two phases: Phase I will develop uniform, auditable and standardized measures of job creation resulting from science 

spending included in the American Recovery and Reinvestment Act; Phase II will 

develop measures of the impact of federal R&D spending on economic growth, workforce development, scientific knowledge, and social outcomes.

International Efforts 

The Organization for Economic Cooperation and Development (OECD) has been 

developing and collecting science and technology indicators from their member nations for nearly 50 years. In 2004, the Science & Technology Ministerial called for 

a ‘‘new generation of indicators which can measure innovative performance and 

other related output of a knowledge-based economy’’ emphasizing ‘‘the data required 

for the assessment, monitoring and policy making purposes.’’ 2 Since that time the 

OECD has continued to refine its science and technology indicators, and improve the 

tools they use for analyzing the impact of science and technology. Earlier this year 

the OECD released a report entitled, ‘‘Measuring Innovation: A New Perspective.’’ 3

The report identifies five areas for which international action is needed: the development of innovation metrics that can be linked to aggregate measures of economic 

performance; investment in a high-quality and comprehensive statistical infrastructure to analysis innovation at the firm-level; the promotion of innovation metrics in 

public sector and for public policy evaluation; the identification of new approaches 

to understand knowledge creation and flow; and the promotion of the measurement 

of innovation on social goals. 

On April 14, Dr. Julia Lane spoke to the European Parliament about the STAR 

METRICS effort, emphasizing the global nature of science and engineering and the 

common need for better tools to assess and predict the impact of science, technology, 

and innovation. During her speech, Dr. Lane indicated that creating a universal researcher identification system could be an important first step in a global effort to 

understand and measure the return on scientific investment. Niki Tzavela, a Greek 

Member of the European Parliament, who serves as Vice-Chair of the European 

Parliament Delegation to the United States, and sits on the Parliament’s Industry, 

Research, and Energy Committee (ITRE), has been a leader on the issue of improved science metrics in the European Union. Having indicated that the EU 8th 

Framework Program represents an opportunity to evaluate and improve science policy, Mrs. Tzavela introduced an initiative to the ITRE Committee proposing that the 

EU collaborate on this topic with the United States. The EU is now considering initiatives that would complement the STAR metrics project, and the Scientific Tech-
6

4http://www.euractiv.com/en/science/eu-looks-to-us-model-for-measuring-rd-impact-news448950 5http://www.aaas.org/spp/sepp/

nology Options Assessment Panel within the EU has been designated to provide an 

in-depth analysis on Science Metrics.4

Education in Science & Technology Public Policy 

According to the AAAS Guide to Graduate Education in Science, Engineering and 

Public Policy 5 there are more than 25 U.S. universities that offer a graduate degree 

in the interdisciplinary field of science and technology public policy. These degree 

programs draw from a number of fields, including economics, sociology, political 

science, and engineering; however the coursework associated with each program 

varies and is dependent upon the academic department or school that houses the 

program. 

5. Questions for Witnesses

Dr. Julia Lane 

1. Please describe NSF’s Science of Science Policy and Innovation program, including a description of the Foundation’s overall vision and strategy for research and education in this area.

Specifically,

How is NSF fostering collaboration between social and behavioral scientists and researchers from other disciplines, including computer scientists, engineers, and physical scientists, in science and technology 

policy research?

How is NSF fostering the development of science and technology policy 

degree programs and courses of study at colleges and universities? 

What is the current scope and level of support for such programs?

How is NSF encouraging the development of a community of practice 

in science of science policy and the dissemination of research results to 

policy makers?

2. As a Co-Chair of the Science of Science Policy Interagency Group under the 

National Science and Technology Council, please briefly describe the work of 

that group and how the various federal science agencies are collaborating on 

the development and implementation of science of science policy tools to improve the management and effectiveness of their R&D portfolios and other 

science and technology-related programs.

3. Please provide a brief description and update on the status of the OSTP led 

project on science metrics, known as STAR Metrics, including a description 

of international engagement and interest in this effort.

Dr. Albert Teich

1. How can research on innovation and the scientific enterprise also known as 

the science of science and innovation policy (SciSIP) be used to inform the 

design of effective federal programs and the management of federal research 

investments? Do you believe the results of science and technology policy research are being effectively incorporated into national policy decisions?

2. What are the challenges to the incorporation of science and technology research in the decision making process? What is AAAS’s role in mitigating 

those barriers? Specifically, how is AAAS helping to build a community of 

practice in the SciSIP? What recommendations, if any, do you have for the 

National Science Foundation’s SciSIP program? Do you believe SciSIP research is being effectively coordinated across the federal agencies? If not, 

what if any recommendations do you have regarding interagency coordination?

3. As you know there are more than 25 U.S. universities that offer graduate 

degrees in science, engineering and public policy. In your opinion, are these 

programs having the intended effect of producing graduates with the skills 

necessary to shape science and technology policies? What type of education 

and training should science and technology policy practitioners receive? Is 

the National Science Foundation playing an effective role in fostering the development of science and technology policy programs at U.S. universities? If 
7

not, what recommendations, if any, do you have for NSF and/or the universities with such programs?

Dr. Daniel Sarewitz

1. Please provide an overview of the research activities of the Consortium for 

Science, Policy, and Outcomes. How are you facilitating interdisciplinary collaborations within the Consortium? What new and continuing areas of research in the science of science and innovation policy (SciSIP) could significantly improve our ability to design effective programs and better target federal research investments? What are the most promising research opportunities and what are the biggest research gaps?

2. Is the Federal government, specifically the National Science Foundation, 

playing an effective role in fostering SciSIP research and the development 

of a community of practice in SciSIP? What recommendations, if any, do you 

have for the National Science Foundation’s SciSIP program?

3. Please describe the education and outreach activities of the Consortium for 

Science, Policy, and Outcomes.

4. How can the dissemination of SciSIP research findings be improved so that 

policymakers are better informed of the current state of research? Are there 

best practices that can be implemented by the Federal government and/or 

the research community to improve the incorporation of science and technology policy research into the decision making process?

5. What are the fundamental skills and content knowledge needed by SciSIP 

researchers and practitioners? What are the backgrounds of students pursuing graduate degrees in science and technology policy and what careers 

paths are sought by these graduates? Is the National Science Foundation 

playing an effective role in fostering the development of science and technology policy degree programs at U.S. universities? If not, what recommendations, if any, do you have for NSF and/or the universities with such 

programs?

Dr. Fiona Murray

1. Please provide an overview of your research. What new and continuing areas 

of research in the science of science and innovation policy (SciSIP) could significantly improve our ability to design effective programs and better target 

federal research investments? What are the most promising research opportunities and what are the biggest research gaps?

2. Is the Federal government, specifically the National Science Foundation, 

playing an effective role in fostering SciSIP research and the development 

of a community of practice in SciSIP? What recommendations, if any, do you 

have for the National Science Foundation’s SciSIP program?

3. What are the fundamental skills and content knowledge needed by SciSIP 

researchers and practitioners? What are the backgrounds of students pursuing graduate degrees in science and technology policy and what careers 

paths are sought by these graduates? Is the National Science Foundation 

playing an effective role in fostering the development of science and technology policy degree programs at U.S. universities? If not, what recommendations, if any, do you have for NSF and/or the universities with such 

programs?
8

Chairman LIPINSKI. This hearing will now come to order. Good 

afternoon and welcome to today’s Research and Science Education 

Subcommittee hearing on the Science of Science and Innovation 

Policy, also known as SciSIP. For those of you who may not be familiar with the phrase, the Science of Science Policy is a field of 

interdisciplinary research that focuses on understanding how our 

policy decisions impact innovation and science and engineering research. Given the magnitude of the federal investment in science 

and technology, there is a need for objective analysis and evaluation of federally funded R&D programs. And given the size of the 

budget deficit, Congressional decision makers need the best information possible to make sure we are spending taxpayer dollars optimally. 

Today we will be hearing from a diverse panel of witnesses about 

the current state of research and education in this emerging field. 

This topic is of particular interest to me since it goes to the core 

of why I joined the Science and Technology Committee when I first 

came to Congress. Like most members of this committee, I believe 

that science and engineering research, and education have driven 

long term economic growth and improved the quality of life for all 

Americans. I have viewed science and innovation policy as critical 

for maintaining our international competitiveness and creating 

jobs. 

But the best policies are not self-evident. As someone who was 

trained as an engineer and a social scientist, I believe we need data 

and proper analysis of this data to be able to determine as best we 

can the optimal policy. We are going to hear today about some of 

the research that is being done on science policy. I am eager to 

hear to the panel’s thoughts on what is being found, how well these 

findings are being disseminated, and whether research in this area 

is actually helping policymakers. 

While many of us would agree that science has had a positive impact on our lives, I think we know very little about how the process 

of innovation works. What kinds of research programs or institutional structures are most effective? How do investments in R&D 

translate to more jobs, improved health, and overall societal wellbeing? How should we balance investments in basic and applied research? With millions of Americans out of work it becomes more 

critical than ever that we find answers to these questions. 

We will also take a closer look at the state of education in science 

and technology policy and how these degree programs and courses 

of study are contributing by educating the next generation of researchers and science policy practitioners. There are a variety of 

science and technology programs that are popping up across the 

country. They can be found in public policy schools, economics departments, business schools, and other places, even philosophy departments. I am looking forward to hearing more about these programs, including what kinds of students they attract and where 

those students go upon graduation. 

Finally, I hope to hear recommendations from today’s witnesses 

about how the Federal Government, particularly the National 

Science Foundation, can foster interdisciplinary research in this 

area, and how it can continue to improved education and training 

for students who want to pursue a career at the intersection of 
9

science, technology, and public policy. I thank the witnesses for 

being here this afternoon, especially as we have had to move this 

hearing back from the morning. I look forward to your testimony. 

Now before I recognize Dr. Ehlers, I—this will likely be the last 

hearing of this subcommittee, the last meeting of this subcommittee. It may not be, but just in case it is the last for this Congress, I wanted to say that I think we should all recognize Dr. 

Ehlers for his contributions in Congress and especially on this committee through the years. It has been certainly—I have had a great 

partner working on this as I have chaired the Subcommittee for the 

last two years. He is someone who really, truly is dedicated to the 

issues that we are facing here and we deal with here in the Committee. Too many things right now are becoming partisan footballs, 

and Dr. Ehlers really has kept his eye on what is best and trying 

to find what is best for our country. And I want to thank you for 

the years that you have put in here and wish you the best in your 

next endeavors, but it has been a pleasure to work with you, especially over these last few years. 

[The prepared statement of Chairman Lipinski follows:]

PREPARED STATEMENT OF CHAIRMAN DANIEL LIPINSKI

Good afternoon and welcome to today’s Research and Science Education Subcommittee hearing on the science of science and innovation policy, also know as 

SciSIP. For those of you who might not be familiar with the phrase, the ‘‘science 

of science policy’’ is a field of interdisciplinary research that focuses on understanding how our policy decisions impact innovation and science and engineering research. Given the magnitude of the federal investment in science and technology, 

there is a need for objective analysis and evaluation of federally funded R&D programs. And given the size of the budget deficit, Congressional decision makers need 

the best information possible to make sure we are spending taxpayer dollars optimally. Today we’ll be hearing from a diverse panel of witnesses about the current 

state of research and education in this emerging field. 

This topic is of particular interest to me since it goes to the core of why I joined 

the Science and Technology Committee when I came to Congress. Like most Members of this committee, I believe that science and engineering research and education have driven long-term economic growth and improved the quality of life for 

all Americans. I view science and innovation policy as critical for maintaining our 

international competitiveness and creating jobs. 

But the best policies are not self-evident. As someone who was trained as an engineer and a social scientist, I believe we need data and proper analysis of this data 

to be able to determine—as best we can—the optimal policy to implement. We are 

going to hear today about some of the research that is being done on science policy, 

and I am eager to hear the panel’s thoughts on what is being found, how well the 

findings of this research are being disseminated, and whether research in this area 

is actually helping policy makers. 

While many of us would agree that science has had a positive impact on our lives, 

I think we actually know very little about how the process of innovation works. 

What kinds of research programs or institutional structures are most effective? How 

do investments in R&D translate to more jobs, improved health, and overall societal 

wellbeing? How should we balance investments in basic and applied research? With 

millions of Americans out of work, it becomes more critical than ever that we find 

answers to these questions. 

We’ll also take a closer look at the state of education in science and technology 

policy and how these degree programs and courses of study are contributing by educating the next generation of researchers and science policy practitioners. There are 

a variety of science and technology policy programs that are popping up across the 

country. They can be found in public policy schools, economics departments, business schools, and other places, even philosophy departments. I’m looking forward to 

hearing more about these programs, including what kind of students they attract 

and where those students go upon graduation. 

Finally, I hope to hear recommendations from today’s witnesses about how the 

Federal government, particularly the National Science Foundation, can foster inter-
10

disciplinary research in this area and how it can contribute to improved education 

and training for students who want to pursue a career at the intersection of science, 

technology, and public policy. 

I thank the witnesses for being here this afternoon and look forward to their testimony.

Chairman LIPINSKI. And with that I will now recognize Dr. 

Ehlers for an opening statement. 

Mr. EHLERS. Thank you for those kind words, Mr. Chairman. I 

think my biggest challenge will be learning how to sleep in, but I 

very much appreciate those comments. I always just try to do a 

good job wherever I am. It is a trade I learned from my parents 

and I never, never, never, ever expected to be in the Congress or 

in politics. My mother never quite got over it. As she put it, what 

are you doing with all those nasty people? But it turns out my colleagues are not nasty people, and I appreciate your leadership on 

the Subcommittee. And you have done a great job of leading us in 

the right direction, and it has been a pleasure to work with you. 

Thank you. 

With that I will proceed to the opening statement. Today we will 

explore the current state of science and technology policy research 

and the role it plays in informing our policy decisions. And I have 

to insert a little comment in here, that is, when I first arrived here 

and was assigned to the Science Committee, which made obvious 

sense since I was at that time I think one of the very few, if the 

only, scientist in the Congress, at least on the Republican side. And 

at the first meeting of the Science Committee I asked the Chair, 

how many scientists do you have on staff? And the answer was 

none. And I said really? How can you function without—and he 

said well, we don’t really need people who understand science. We 

need people who understand science policy. 

Well, as a scientist I had never thought much about science policy and little did I know that in conversation with Newt Gingrich 

where I commented that I thought it a bit strange that the science 

policy we were operating under in the government and in the Congress was by Vannevar Bush’s 1945 book, and I said that is a little 

out of date. Things change rapidly in science. It is a great book, 

‘‘The Endless Frontier’’. Vannevar Bush was a great man. He had 

done a lot of good works especially during World War II. But I 

talked to Newt Gingrich about that, that that was the latest 

science policy book that was guiding the Government, so he did as 

Newt Gingrich always did and said hey, it is time to get another 

one. Why don’t you do it? So I learned after a couple of years never 

to suggest anything to Newt because he always dumped the burden 

on me. 

In any event, I did proceed to work on a book, which just walked 

in the door with my aide, and some of you have seen it already. 

It is called ‘‘Unlocking Our Future’’. Now this is not a great science 

policy book. I knew absolutely nothing about science policy when 

we proceeded to write it but it seemed to me that there were certain things that were obvious and we put them in here. And I deliberately said ‘‘Unlocking Our Future’’ because I felt we had so 

much to do and I was not able to do it in this thin little volume. 

It did get some notice, and it inspired some science policy individuals to engage more seriously in this. And some of them, many of 

them are represented here. But it was a real education to me. You 
11

should try that sometime, writing a book about something you 

know nothing about. It is a great way to learn and fortunately as 

a child I was homeschooled because of illness, so all the learning 

I did was things that I learned and learned on my own. So that 

was good preparation for this. 

We clearly, badly need something like this again and it is one 

case where the author is delighted to say this is too old now. It is 

time to get busy. Someone else better start writing a better thing. 

Let me continue with my opening statement. When Dr. John 

Marburger, who was science advisor to President Bush, called for 

the establishment of a Science of Science Policy in 2005, we embarked on a new journey into this emerging field of interdisciplinary research by establishing an interagency working group, the 

Science and Science of Innovation Policy program at the National 

Science Foundation—the shorthand for it was SciSIP—and most recently, the Science and Technology for America’s Reinvestment, 

which is the emphasis that I and others, including the authors of 

‘‘The Gathering Storm,’’ have been emphasizing, because it is important for us to measure the effects of research and innovation 

competitiveness and science which has come to be called STAR 

METRICS. I hope this hearing will provide us with a detailed 

measurement of how far we have come on that journey as well as 

an encouraging picture of the progress we have made. 

I have spent many years on this Committee working to strengthen U.S. innovation and science education, and I have been a long 

time advocate of increased federal funding for basic research. I 

wish the entire Congress was receptive to that notion as they—but 

this funding produces the technological innovations that will keep 

America competitive in the global market and it is essential for us 

to educate American workers in the skills needed for 21st century 

jobs. 

As with any program, sustained Congressional oversight is required to insure that the Science of Science Policy Programs are effective and that they progress in a timely and fiscally responsible 

manner. I am encouraged by efforts which seek to maximize our 

current investments in scientific research, and I believe it is very 

important that those are the investments that provide us with 

measureable returns. And that is why I have worked so hard to try 

and make the research and development tax credit permanent, because that is one good way to encourage industry to work on these 

issues. We must be mindful of that fact as Congress deliberates the 

best ways to use American taxpayer funds in this difficult economic 

climate. 

To that end I am very interested in learning more about the 

progress and potential of the STAR METRICS program and its recently completed project. I hope—I look forward to learning more 

about the status of science affecting science policy and the advancements which have been made since 2005. And I wanted to thank 

our panel of witnesses for being here today, for accommodating our 

last second scheduling change, and I look forward to hearing their 

insights on this topic. There is much work to be done to help our 

nation recover its lead in technological development, and in manufacturing, and in science in general. 
12

And so I am looking forward to the testimony today and I hope 

you can enlighten us, and out of this will come first of all a new 

version of this, and secondly there is some improvement in our 

judgments about science and also science education in this Nation. 

Thank you very much. 

[Statement of Mr. Ehlers follows:]

PREPARED STATEMENT OF REPRESENTATIVE VERNON J. EHLERS

Today, we will explore the current state of science and technology policy research, 

and the role it plays in informing our policy decisions. When Dr. John Marburger, 

then science advisor to President Bush, called for the establishment of a ‘‘science 

of science policy’’ (SoSP) in 2005, we embarked on a new journey into this emerging 

field of interdisciplinary research by establishing an interagency working group, the 

Science of Science and Innovation Policy (SciSIP) program at the National Science 

Foundation (NSF), and, most recently, the Science and Technology for America’s Reinvestment: Measuring the Effect of Research on Innovation, Competitiveness and 

Science (STAR METRICS) project. I hope this hearing will provide us with a detailed measurement of how far we have come on that journey, as well as an encouraging picture of the progress we have made. 

I have spent many years on this committee working to strengthen U.S. innovation 

and science education, and I have been a long time advocate of increased federal 

funding for basic research. This funding produces the technological innovations that 

will keep America competitive in the global market, and it is essential for us to educate American workers in the skills needed for 21st-century jobs. 

As with any program, sustained Congressional oversight is required to ensure the 

SoSP programs are effective, and that they progress in a timely and fiscally responsible manner. I am encouraged by efforts which seek to maximize our current investments in scientific research, and I believe it is very important that those R&D 

investments provide us with measurable returns. We must be mindful of that fact 

as Congress deliberates the best ways to use American taxpayer funds in this difficult economic climate. To that end, I am very interested in learning more about 

the progress and potential of the STAR METRICS program and its recently completed pilot project. 

I look forward to learning more about the status of science affecting science policy 

and the advancements which have been made since 2005. I want to thank our panel 

of witnesses for being here today, for accommodating our last-second scheduling 

change, and I look forward to hearing their insights on this topic.

Chairman LIPINSKI. Thank you, Dr. Ehlers. Maybe we can make 

that a best seller now. Now if there are Members who wish to submit additional opening statements, their statements will be added 

to the record at this point. And at this time I want to introduce 

our witnesses. Dr. Julia Lane is the Program Director of the 

Science of Science and Innovation Policy program at the National 

Science Foundation. Dr. Daniel Sarewitz is the Co-Director of the 

Consortium for Science, Policy & Outcomes and Professor of 

Science and Society at Arizona State University. Dr. Fiona Murray 

is an Associate Professor of Management in the Technological Innovation & Entrepreneur Group at MIT Sloan School of Management. 

And Dr. Albert H. Teich is the Director of Science & Policy Programs at the American Association for the Advancement of Science. 

As our witnesses should know, you will each have five minutes 

for your spoken testimony. Your written testimony will be included 

in the record for the hearing. When you all have completed your 

spoken testimony we will begin with questions. Each Member will 

have five minutes to question the panel. And before we begin I just 

want to mention that we will be having votes coming up soon, so 

probably what the most important thing is if everyone could hold 

to their five minutes it will help us so we don’t have—hopefully 
13

won’t have an interruption in the—at least in the testimony part 

here. But with that, we will start with Dr. Lane. 

STATEMENT OF JULIA LANE, PROGRAM DIRECTOR OF THE 

SCIENCE OF SCIENCE AND INNOVATION POLICY PROGRAM, 

NATIONAL SCIENCE FOUNDATION 

Dr. LANE. Chairman Lipinski, Ranking Member Ehlers, Members 

of the Subcommittee, it is my distinct pleasure to be with you here 

today to discuss NSF’s Science of Science and Innovation Policy 

Program, the activities of the Science of Science Policy Inter-Agency Group, and the STAR METRICS program, the last of which is 

a new federal and university partnership to document the scientific, social, economic, and work force outcomes of science investments to the public. I am Dr. Julia Lane. I am the Program Director of the SciSIP program at NSF and Co-Chair of NSTC working 

group on the Science of Science Policy. 

I submitted a written statement to supplement or to accompany 

my oral testimony. So the focus of these three efforts is to provide, 

as you noted, better methods and data to inform science—federal 

science investment decisions. They represent the first efforts to 

construct a scientific framework that is supported by multiple 

agencies and multiple institutions, all jointly engaged. It represents 

a true all-out effort to providing an evidence basis for U.S. science 

policy. Its success is important for policy makers because, in a nutshell, you can’t manage what you can’t measure, and what you 

measure is what you get. 

Developing a scientific framework involves several things. It requires the engagement of scientists from many disciplines to address science policy issues. The NSF does this through the SciSIP 

program. The overarching goal of this effort is to conduct basic research that creates new objective models, analytical tools, and data 

sets to inform our nation’s basic research, and to inform public and 

private sectors about the processes through which investments in 

science and engineering work their way through the outcomes we 

have mentioned. It funds researchers from a wide range of disciplines and it funds students to study science policy issues in a 

scientific manner. As you also know, it supports the redesign of 

surveys undertaken by the National Science Foundation’s Science 

Resource Statistics. It is the statistical agency charged with describing the science and innovation enterprise. For example, the 

new business and innovation survey, the BRDIS [Business R&D 

and Innovation Survey] survey, has been completely redesigned 

from a 1950s structure to something that captures the new R&D 

innovation activities. 

So it is not just the academic community that is advancing the 

Science of Science Policy. It is also policymakers in the Executive 

and Legislative branches who recognize that we need these better 

approaches. That is why the National Science and Technology 

Council established the Science of Science Policy Inter-Agency Task 

Group. That task group, the science policy Agencies that were represented on that, created a road map that characterized our current system of measuring the science and engineering enterprise as 

inadequate. We can do better. There is enormous potential to do 

better. The first step to doing better is to get better data. Just as 
14

good bricks need straw, good research in an empirical field like 

science and innovation policy requires good data. So to that end, 

the SciSIP Program and the Science of Science Policy Inter-Agency 

Group initiated the development of the STAR METRICS program 

to which you have already alluded. The benefits of this program is 

that rather than having organized data sets that different agencies 

and different institutions use to answer the types of questions that 

the American people are asking, we can develop a common, bottomup, empirical infrastructure that will be available to all recipients 

of federal funding and to science agencies to quickly respond to 

state, congressional, and OMB requests. It is critical that we take 

a bottom-up effort in order to develop these approaches—one that 

is domain specific, generalized, and replicable. 

Phase one started in March, jointly sponsored by NIH, the lead 

agency, NSF, and OSTP. And that is collecting the data required 

to, with no burden, respond to questions about the jobs associated 

with science funding. Phase two, which is trying to collect broader 

data on a wide range of outcomes--not just jobs, but social, scientific, economic, and work force outcomes—is beginning this fall 

with formal consultations with research institutions. 

Furthermore, science is fundamentally an international endeavor. We have engaged with the European Union, with the Japanese, 

with the Brazilians, with many countries in order to document the 

impact of science investments. In fact, the Japanese Government 

has recently set aside funding for a Japanese equivalent of a 

SciSIP program. The European Union has also shown considerable 

interest in what we have been up to, and is considering emulating 

the bottom-up, no burden endeavor that the SciSIP, the Science of 

Science Policy, and the STAR METRICS Program have pushed forward. And the Brazilian Government has also requested briefings 

on the SciSIP, Science of Science Policy, and STAR METRICS Program. 

This concludes my testimony, Mr. Chairman. I look forward to 

answering any questions you or the Members of the Committee 

might have. 

[The prepared statement of Dr. Lane follows:]

PREPARED STATEMENT OF JULIA I. LANE

Chairman Lipinski, Ranking Member Ehlers, and Members of the Subcommittee, 

it is my distinct privilege to be here with you today to discuss NSF’s Science of 

Science and Innovation Policy (SciSIP), the activities of the Science of Science Policy 

Interagency Group, and the STAR METRICS program—a new federal effort designed to create a scientific quantifiable measurement of the economic and social impacts of federal research spending. I am Dr. Julia Lane, the program Director of the 

SciSIP program at the National Science Foundation, and co-chair of the NSTC working group on Science of Science Policy (SOCP). 

At the outset, I would like to express my appreciation to all the Members on the 

House Committee on Science and Technology for their unstinting support to advance 

both the cause, and the frontiers of science. This Committee has long held steadfast 

in the knowledge that America’s present and future strength, prosperity and global 

preeminence depend directly on fundamental research. 

The National Science Foundation has always believed that optimal use of limited 

Federal funds relies on two conditions: Ensuring that research is aimed—and continuously re-aimed—at the frontiers of understanding; and certifying that every dollar goes to competitive, merit-reviewed, and time-limited awards with clear criteria 

for success. When these two conditions are met, the nation gets the most intellectual 

and economic leverage from its research investments. 
15

Yet our portfolio keeps changing. We have a minimal vested interest in maintaining the status quo, and pride ourselves on an ability to shift resources quickly to 

the most exciting subjects and most ingenious researchers. 

Moreover, we regard it as an essential part of our mission to constantly re-think 

old categories and traditional perspectives. This ability is crucial now, because conventional boundaries are disappearing—boundaries between nations, boundaries between disciplines, boundaries between science and engineering, and boundaries between what is fundamental and what is application. At the border where research 

meets the unknown, the knowledge structures and techniques of life science, physical science, and information science are merging. 

Additionally, our scope is extremely wide, extending across all the traditional 

mathematics, science and engineering disciplines. That is a major advantage in today’s research climate, where advances in one field frequently have immediate and 

important applications to another. The same mathematics used to describe the physics of turbulent air masses may suddenly explain a phenomenon in ecology or in the 

stock market, or the changes in brain waves preceding an epileptic seizure. The 

same algorithms used by astronomers to discern patterns in the distant heavens can 

aid radiologists to understand a mammogram, or intelligence systems to identify a 

threat. Only an agency that sees the ‘‘big picture’’ can assure this kind of interdisciplinary synergy. 

For all of these reasons, the National Science Foundation is fostering the development of the knowledge, theories, data, tools and human capital needed to cultivate 

a Science of Science and Innovation Policy program. The program has three major 

aims: advancing evidence-based science and innovation policy decision making; developing and building a scientific community to study science and innovation policy; 

and developing new and improved datasets. 

The overarching goal in this effort, however, is to conduct basic research that creates new objective models, analytic tools, and datasets to inform our nation’s public 

and private sectors about the processes through which investments in science and 

engineering research may be transformed into scientific, social and economic outcomes. We need to better understand the contexts, structures, and processes of scientific 

and engineering 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. 

It is not only leaders in the scientific and engineering fields, but policymakers as 

well in the Executive and Legislative Branches who recognize that we need better 

approaches for developing science policy, which is why the National Science and 

Technology Council established the Science of Science Policy Interagency Task 

Group. That task group’s roadmap characterized our current systems of measurement of the science and engineering enterprise as inadequate. There is enormous 

potential to do better. 

To begin to create a scientific, quantifiable measurement of the economic and social impacts of our federal research investments, this Administration has initiated 

an innovative new program, STAR METRICS (Science and Technology in America’s 

Reinvestment—Measuring the EffecTs of Research on Innovation, Competitiveness 

and Science). This initiative is led by the National Institutes of Health and the National Science Foundation under the auspices of the White House Office of Science 

and Technology Policy. The goal is to develop a system that can be used to track 

the impact of federal science investments. I will return to the topic of STAR 

METRICS later in my testimony.

1) The overall vision and strategy for research and education in the 

‘Science of Science and Innovation Policy. 

Federally funded basic and applied scientific research has had a significant impact on innovation, economic growth and America’s social well-being. We know this 

in the broad sense from numerous economic analyses but it is difficult to disentangle the impact of Federal investment versus private, state and industrial investments. We have little information about the impact of individual projects and 

programs, whether federally or privately funded. We have little information about 

the impact of science agencies. Thus, although determining which federally funded 

research projects yield solid results and which do not is a subject of high national 

interest, since American taxpayers invest more than $140 billion annually in research and development (R&D), there is little evidence to support such analysis. In 

short, although Congressional and Executive Branch policy decisions are strongly 

influenced by past practices or data trends that may be dated, or have limited relevance to today’s economic situation. A deeper understanding of the changing framework in which scientific and technical innovation occurs would help policymakers 
16

decide how best to make and manage limited public R&D investments to exploit the 

most promising and important opportunities. 

The lack of analytical capacity in science policy is in sharp contrast to other policy 

fields that focus on workforce, health and education. Debate in these fields is informed by the rich availability of data, high quality analysis of the relative impact 

of different interventions and computational models that often allow for forwardlooking analyses with impressive results. For example, in workforce policy, the evaluation of the impact of distinct education and training programs has been transformed by careful attention to issues such as selection bias and the development of 

appropriate comparison groups. The analysis of data about geographic differences in 

health care costs and health care outcomes has featured prominently in guiding 

health policy debates. And education policy has moved from a ‘‘invest more money’’ 

and ‘‘launch a thousand pilot projects’’ imperative to a more systematic analysis of 

programs that actually work and that promote local and national reform efforts. 

Each of those efforts, however, has benefited from an understanding of the systems that are being analyzed. In the case of science policy, no such agreement currently exists. NSF’s Science of Science & Innovation Policy (SciSIP) program is designed to advance the scientific basis of science and innovation policy.

Vision 

The principal goal is to advance the scientific basis of making science policy decisions, particularly those involving budgets, through the development of improved 

data collection, theoretical frameworks, computational models and new analytic 

tools. 

A major component of the SciSIP program is the funding of investigator initiated 

research. Through direct engagement of the federal policy community with the research community, it is hoped that future policy decisions can be informed by empirically validated hypotheses and informed judgment. Our aim, as noted in the program’s description, is to ‘‘engage researchers from all of the social, behavioral and 

economic sciences as well as those working in domain-specific applications such as 

chemistry, biology, physics, or nanotechnology in the study of science and innovation 

policy. The program welcomes proposals for individual or multi-investigator research 

projects, doctoral dissertation improvement awards, conferences, workshops, 

symposia, experimental research, data collection and dissemination, computer equipment and other instrumentation, and research experience for undergraduates. The 

program places a high priority on interdisciplinary research as well as international 

collaboration.’’

The program explicitly fosters a multi-level science (in addition to more obviously 

being an interdisciplinary science) that spans from the study of cognitive phenomena in individual scientists (e.g., the study of fixation, insight, reasoning, and 

decision making) to the study of whole industries and policies at the industry level. 

What makes the overall effort a potentially transformative effort is the support of 

research at multiple levels: industry level policies are only successful if it has individual-level effects (i.e., that engineers and scientists change), and individual-level 

effects are only important if they scale to produce industry-level differences. 

Another focus of the SciSIP program is the redesign of the surveys undertaken 

by NSF’s Science Resources Statistics, the federal statistical agency responsible for 

collecting and disseminating data on the U.S. science and engineering enterprise. 

The most visible activity has been the redesign of the Business R&D and Innovation 

Survey (BRDIS) which collects information from a nationally representative sample 

of about 40,000 companies, including companies in both manufacturing and nonmanufacturing industries. This survey is the primary source of information on business, domestic and global R&D expenditures, and workforce. The new structure enables respondents to provide detailed data on the following:

• How much is a company investing in its domestic and worldwide R&D relationships, including R&D agreements, R&D ‘‘outsourcing,’’ and R&D paid for 

by others?

• What is the strategic purpose of a company’s worldwide R&D activities and 

what are their technology applications?

• What are the details of a company’s patenting, licensing, and technology 

transfer activities, and companies’ innovative activities?

In addition, a limited number of questions are asked about activities related to 

new or improved products or processes. These are intended to serve as basis for collecting an expanded set of innovation metrics in the future. The results of this data 

collection are now being published as part of SRS’s ongoing reporting activity:
17

1http://www.ncseonline.org/NLE/CRSreports/08Aug/RL31181.pdf, CRS–3

Strategy 

The focus of the program’s strategy has been to convince the academic community 

that the study of science policy is a worthwhile academic endeavor. This has taken 

three main forms. The first has been to engage in a substantial amount of outreach 

through presenting at professional workshops and conferences (an average of five 

or six a year), through supporting specific workshops on various science policy topics 

(two or three a year), through establishing a very active listserv (which has grown 

to over 720 members in less than two years) and through supporting a Science of 

Science Policy website (http://scienceofsciencepolicy.net). 

The second part of the strategy has been to invest in high quality research 

datasets. Good bricks need straw, and good research in an empirical field like 

science and innovation policy requires good data. Fields as disparate as biotechnology, geosciences, and astronomy have been transformed by both data and 

knowledge access. NSF hopes to similarly transform the study of science policy by 

improving science data. Such a transformation will occur in three ways. First, the 

scientific challenge is compelling: the way in which scientists create, disseminate 

and adopt knowledge in cyberspace is changing in new and exciting ways. Collaborations between computer scientists and social scientists, fostered by SciSIP, can capture these activities using new cybertools. Second, new and exciting data attract 

new researchers to the field. This in turn attracts new graduate students, who see 

new ground being broken and exciting opportunities for research. Finally, we aim 

to actively engage the federal science policy community through a variety of workshops, as well as direct engagement through the Science of Science Policy Interagency Group. 

The program has made a total of 99 awards: 19 in 2007, 23 in 2008, 31 in 2009, 

and 26 in 2010. The program began to accept doctoral dissertation proposals in 

2010; five of those were funded. The success rate for standard proposals is currently 

about 25%; higher for doctoral dissertation proposals. A total of 182 principal investigators have been supported—of those 147 are scientists from Social, Behavioral 

and Economic Science domains and the balance are from areas as diverse as Computer and Information Sciences, Education, Physics, Biology and Law.

Results 

The program is beginning to achieve some of its ambitious goals. A SciSIP Principal Investigator (PI), who is a Business School Dean at a university with a strong 

focus on publicly-funded research, has noted ‘‘I know full well that this new program 

provides unique grant opportunities for faculty members in management, information systems, and other fields of business administration. He cites the following 

from his personal experience ‘‘ . . . in the field of business research, and business 

management, the Science of Science & Innovation Policy papers are featured in 

some of the best sessions at the Academy of Management Meetings. This innovative 

program has sparked considerable interest in public policy among management 

scholars, and particularly in business schools. The impact of the research you are 

funding struck home when I read the latest issue of BizEd, the magazine of The 

Association to Advance Collegiate Schools of Business (AACSB, an association of 

educational institutions, businesses, and other organizations devoted to the advancement of higher education in management education. It is also the premier accrediting agency of collegiate business schools and accounting programs worldwide. The 

research you have funded was prominently featured in their magazine, which is circulated to thousands of business schools worldwide.’’

Additionally, the impact of the SciSIP program has influenced several National 

Research Council studies, and thus impacted public policy with respect to technology commercialization and academic and public sector entrepreneurship. One is 

the Congressionally-mandated evaluation of the Small Business Innovation Research Program. Another is a committee entitled ‘‘Best Practices in National Innovation Programs for Flexible Electronics’’ and a third is ‘‘Management of University 

Intellectual Property: Lessons from a Generation of Experience, Research, and Dialogue’’

In another example, a major part of the science and innovation policy debate has 

been the role of R&D and research tax credits whose budgetary cost is about $15 

billion each year 1. The obvious policy question is how effective are these tax credits 

in stimulating innovation? SciSIP funded PIs have examined changes in R&D tax 

credit generosity across countries and US states over time to evaluate business 

firms’ response. They estimate that for every $1 of tax credits firms spend about 

$1 more on R&D. However, the research also extends to the impact of firms’ re-
18

sponse to the uncertainty about the duration of the federal Research and Experimentation (R&E) tax credit, which is not currently permanent and in fact expired 

at the end of 2009. The uncertainty about renewal has offsetting effects—one is to 

increase short-term expenditures because firms think they need to do R&D now to 

get the credit. The reverse is to reduce overall R&D expenditures since uncertainty 

is detrimental to the expected payoffs from long-term investments such as fundamental R&D. The sign of the net effect is an empirical question, and again something the SciSIP PI has been working on—he finds a strong negative effect of uncertainty on general investment and employment, and is currently extending this work 

to R&D. The same PI presented in September 2009 to the Federal Reserve Bank 

Board of Governors, including Governor Bernanke; the Fed was trying to understand why the IT ‘‘productivity miracle’’, which was a major driver of US economic 

growth in the late 1990s, has slowed down by the late 2000s. One possible reason 

is that better use of IT is associated with organizational change, and the rate of organizational change has potentially slowed down; a major SciSIP-funded grant supports collecting a large national survey to try to examine why and how that change 

has occurred. 

We can also learn from history. Another SciSIP PI has looked at two case studies 

in depth: the invention of the airplane and Edison’s invention of the electric light. 

In both cases, the invention took a long period of time—110 years and 80 years, respectively. In both cases even the earliest attempts were based on many years [of 

work on mathematics and technology and hundreds of years of work of science. To 

illustrate, Sir Humphry Davy first demonstrated incandescence of materials in 

1808. His work drew on the Voltaic pile (battery) invented in 1800, the Leyden jar 

developed in 1744, and carbon produced as charcoal during the Roman Empire no 

later than 25 A.D. Leyden jars depended on work by the ancient Greeks in 600 B.C. 

Thus, the foundation of the science behind electric light dates back 2400 years before incandescence, after which it took 80 more years of R&D to develop an effective 

electric light. The airplane also has a similarly long foundational period and duration of invention. In looking at various inventions, research has shown that there 

are several different weak methods but also some powerful strategies that vastly 

speed things along. Edison succeeded simply because he had enormous resources 

(the Edison Electric Light Company was capitalized at $300,000—about $30 million 

today. The Wright Brothers were far more efficient at developing the airplane than 

Edison was in developing the electric light.

How is the NSF fostering collaboration between social and behavioral scientists and researchers from other disciplines, including computer 

scientists, engineers and physical scientists in science and technology policy research? 

This is being done in a number of ways: through the program call, through workshops, and through successful and visible interdisciplinary projects.

Program Description 

The SciSIP program explicitly encourages interdisciplinary cooperation in the program description. In particular, the program states

‘‘The SciSIP program invites the participation of researchers from all of the social, behavioral and economic sciences as well as those working in domain-specific applications such as chemistry, biology, physics, or nanotechnology. The 

program welcomes proposals for individual or multi-investigator research 

projects, doctoral dissertation improvement awards, conferences, workshops, 

symposia, experimental research, data collection and dissemination, computer 

equipment and other instrumentation, and research experience for undergraduates. The program places a high priority on interdisciplinary research as well 

as international collaboration.’’

Workshops 

Most of the workshops that have been hosted have been explicitly interdisciplinary in nature, bringing together domain scientists and social, behavioral and economic scientists, and have resulted in calls for proposals (called Dear Colleague Letters) supported by multiple NSF programs. 

Examples include:

• A two-day workshop to advance the scientific study of federally funded centers and institutes as key elements in the innovation ecosystem. The workshop brought together engineers and natural, physical, and social scientists 
19

to address central questions relating to the role of NSF-funded centers and 

institutes in science and innovation policy.

• Two separate workshops studying innovation in organizations. One of these, 

hosted by the Conference Board and supported by four Social, Behavioral and 

Economic (SBE) Sciences and three Computer and Information Science and 

Engineering (CISE) programs, was attended by computer scientists, SBE scientists and representatives from the business community to examine the potential for cyber data to better inform our understanding of innovation. A second conference brought together 20 leading computer scientists (from the 

fields of data management, data mining, security/privacy, social networks) 

and social/organizational scientists (that included economists, sociologists, 

psychologists, anthropologists) to identify emerging major challenges in the 

collection and use of confidential data collection for the study of innovation 

in organizations. SciSIP led the reusulting development of a Dear Colleague 

Letter whose purposes was to gather and create new Cyber-enabled data on 

innovation in organizations, supported by six SBE and four CISE programs 

as well as the Office of Cyber Infrastructure.

• A workshop in conjunction with the NSF’s Chemistry Division that examined 

the impact of science R&D in the United States, focusing on chemical sciences 

and related industries. This led to a Dear Colleague Letter from SciSIP and 

the Chemistry Division reaching out to the chemistry and the social science 

communities advising them of funding opportunities related to assessing and 

enhancing the impact of R&D in the chemical sciences in the United States.

• An interdisciplinary workshop which examined the potential for new visualization tools to track the impact of investments in science. These possibilities 

include tracing the impact of basic research on innovation, examining the 

changing structure of scientific disciplines, studying the role of social networks in the dispersion of scientific innovations as well as making comparisons of how the U.S. compares internationally in science. That workshop 

brought together researchers from a broad range of disciplines to examine 

such key questions, and to engage the federal science community in a discussion about whether and how the tools could be used in the federal context.

• Three workshops have directly engaged CISE and SBE researchers in enhancing NSF’s ability to describe its research portfolio. The SciSIP program 

worked with the CISE directorate to form an Advisory subcommittee to provide advice on approaches to improving the way NSF interacts with its proposal and award portfolio. Although NSF staff still rely on traditional methods to do their jobs, such methods are becoming less practical given the rapidly changing nature of science, the increased recognition of the importance 

of funding interdisciplinary and potentially transformative research, and the 

significant increase in the number of proposals submitted. Individuals with 

research expertise in machine learning, data mining, information visualization, human-centered computing, science policy, and visual analytics were recruited for this effort. Nine teams were put together and charged with providing advice to NSF on identifying and demonstrating techniques and tools 

that characterize a specific set of proposal and award portfolios. Their report, 

in turn, will advise NSF on how to better structure existing data, improve use 

of existing machine learning, analysis, and visualization techniques to complement human expertise and better characterize its programmatic data. The 

results should help NSF identify tools that will help fulfill its mission including identifying broader impacts, as well as funding transformative and interdisciplinary research. NSF has also engaged program managers across the 

federal government so that our collective approaches can inform not only us, 

but other science agencies.

• A workshop responding to Congressman Holt’s request for better ways to 

measure the economic impact of federal research investments. SciSIP, together with NIH and other agencies, is supporting the National Academy of 

Sciences’ Board on Science, Technology, and Economic Policy (STEP) and 

Committee on Science, Engineering, and Public Policy (COSEPUP) 2011 

workshop on science measurement. This workshop is aimed at discussing new 

methodologies and metrics that can be developed and utilized for assessing 

returns on research across a wide range of fields (biomedical, information 

technology, energy, and other biological and physical sciences, etc.), while 

using background papers that review the methodologies used to date as a 

starting point.
20

As one SciSIP PI has noted, ‘‘SciSIP.. creates a domain around which researchers 

from a variety of disciplines—biology and physics and economics as well as information science and public policy—can coalesce to pursue research topics in this domain 

for their own sake, rather than in the interstices of other projects in their home disciplines. As such, it acts as an attractor for top researchers across the natural and 

social sciences, allowing them to pursue their interests in SciSP topics’’

Successful Examples 

There are a number of examples of the fruits of these activities. For example, 

SciSIP funded research supports a University of Michigan research team consisting 

of a sociologist, a bioethicist specializing in informed consent and stem cell regulation, a bioethicist trained as a molecular biologist who is working on cell banking, 

and a post-doc in stem cell biology. The combination is a powerful one as it matches 

expertise with social scientific data and analysis methods, with deep knowledge 

about both the policy and the science. 

Similarly, the interdisciplinary work of two SciSIP Pis has helped developed new 

metrics of the transmission of knowledge. These metrics go beyond citation metrics 

to usage metrics and help us better understand the impact that federal investment 

in research is having on research results. By mapping the structure of science and 

looking at how this structure changes over time, we can see the shifting landscape 

of scientific collaboration and understand the new emerging disciplines. That will 

enable us to to anticipate these changes and properly target research funding to 

new and vibrant areas. For instance, their work provides a striking example of the 

emergence of neuroscience over the past decade—changing from an interdisciplinary 

specialty to a large and influential stand alone discipline on a par with physics, 

chemistry, or molecular biology.

How is NSF fostering the development of science and technology policy degree programs and courses of study at colleges and universities? 

What is the current scope and level of support for such programs? 

As with many NSF programs, the SciSIP program explicitly encourages submissions that support graduate student development. While there is no direct targeting 

of funds to policy programs, SciSIP supported 28 researchers from science and technology policy programs. In an example of the type of support that has been provided 

to expand the course of study, over 250 undergraduate students from Economics (behavioral economics), Cognitive Science, Electrical and Computer Engineering, and 

Industrial Engineering have participated in a project at Purdue University, which 

is an interdisciplinary collaboration linking social scientists and computer scientists 

and engineers. 

A further example is the work done by Marcus Ynalvez at Texas A&M International University, which has the explicit goal of mentoring TAMIU Graduate Students (Students from Historically Underrepresented Populations): The hands-on 

training and mentoring of TAMIU graduate students represents an attempt to engage Hispanic students in international scientific research activities with the intention of introducing them to the possibilities of developing professional careers in 

science and technology. These students are currently gathering, synthesizing and reviewing literature materials for the project’s manuscripts, publications, and reports. 

With the data from the Japan, Singapore, and Taiwan surveys, these students will 

be analyzing data using a number of statistical software such as: Statistical Packages for the Social Sciences (SPSS), STATA, and Statistical Analysis System (SAS). 

They will learn how to interpret statistical results associated with the family of generalized linear regression models, namely: linear, logistic, and negative binomial regression models, analysis of variance, and path analysis. Not only have the TAMIU 

graduates gained actual research experience, they have also developed professional 

relationships with students and professors from the prestigious National University 

of Singapore

How is NSF encouraging a community of practice in science of science policy and the dissemination of policy to policy makers 

A major avenue has been the linkage with the Science of Science Policy Interagency group, which is discussed in more detail below. In addition, the listserv and 

the website have been very important dissemination vehicles. 

However, the most important vehicle has been two PI workshops with the explicit 

goal of fostering further collaboration among the PIs actively engaged in the study 

of Science of Science & Innovation Policy and the link to the federal community. 

The 2009 workshop had three overarching goals:
21

• to provide NSF with an early opportunity to organize a collegial discussion 

of work in progress under SciSIP’s two rounds of awards well before this work 

will begin to appear in professional forums and publications;

• to begin to develop from among the purposefully diverse set of disciplinary 

perspectives reflected in SciSIP’s two solicitations and subsequent awards, a 

‘‘community of experts across academic institutions and disciplines focused on 

SciSIP;’’ and

• To identify new areas of emphasis for support in future SciSIP solicitations.

The 2010 workshop, scheduled for October 19, 2010 seeks to focus on two objectives that flow from the National Science and Technology Council’s 2008 report: The 

Science of Science Policy: A Federal Research Roadmap. The first task, as called for 

in the Roadmap report, is ‘‘to advance the scientific basis of science policy so that 

limited Federal resources are invested wisely.’’ The second is to build a ‘‘community 

of practice’’ between Federal science and technology policymakers and researchers 

engaged in the development of new theories, tools of analysis, and methods for collecting and analyzing data. 

This October 2010 workshop will consist of brief presentations by a number of 

SciSIP grantees who have been invited to participate via a competitive peer review 

of abstracts previously submitted based on their ongoing research. These presentations will be followed by roundtable discussions led by federal policymakers who 

will comment on the relevance of the research, followed then by open discussions 

among all participants. A networking session will be scheduled at the close of the 

formal sessions to allow for continued discussion.

2) As a Co-chair of the Science of Science Policy Interagency Group under 

the NSTC please briefly describe the work of that group and how 

the various federal science agencies are collaborating on the development and implementation of science of science policy tools to 

improve the management and efficiency of their R&D portfolios 

and other science and technology related programs. 

In 2006, the National Science and Technology Committee’s Subcommittee on Social, Behavioral and Economic Sciences (SBE) established an Interagency Task 

Group on Science of Science Policy (ITG) to serve as part of the internal deliberative 

process of the Subcommittee. In 2008, this group developed and published The 

Science of Science Policy: A Federal Research Roadmap which outlined the Federal 

efforts necessary for the long-term development of a science of science policy, and 

presented this Roadmap to the SoSP Community in a workshop held in December 

2008. The ITG’s subsequent work has been guided by the questions outlined in the 

Roadmap and the action steps developed at the workshop. 

The development of the STAR METRICS (Science and Technology for America’s 

Reinvestment: Measuring the EffecT of Research on Innovation, Competitiveness 

and Science) program is the number one priority of the interagency group. The initiative is a multi-agency venture led by the National Institutes of Health, the National Science Foundation (NSF), and the White House Office of Science and Technology Policy (OSTP). 

Another major activity is sponsoring a series of workshops to bring the science 

agencies together to share what is already established in the field, identify gap 

areas and outline steps forward for the creation of better tools, methods, and data 

infrastructure. 

The first of these workshops was held in October, 2009 to delve into the issues 

surrounding performance management of federal research and development portfolios. The focus was on sharing current practices in federal R&D prioritization, 

management, and evaluation. Over 200 agency representatives attended. The conference featured 27 speakers and panelists, representing 20 federal agencies, offices, 

and institutions, and over 30 poster presenters, representing more than 25 agencies 

and institutions. Topics that were discussed included:

• Methods to set federal research priorities and strategic directions;

• The use of metrics to improve federal R&D efficiency; and

• Ways in which research evaluations can inform current and future R&D decisions.

It addressed the following key questions:

• How do federal science and technology agencies systematically identify and 

prioritize research and development alternatives? How can these processes be 

strengthened?
22

2http://www.whitehouse.gov/sites/default/files/microsites/ostp/STAR%20METRICS

%20FINAL.pdf

• How can research-performance metrics be used to improve research efficiency? How can these metrics be improved?

• How do research-performance evaluations inform and improve R&D investment decisions? How can these feedback loops be reinforced?

While the 2009 workshop developed a dialogue within the federal science policy 

community, the ITG has a workshop planned for December 2010 that engages the 

federal community with the academic community in advancing the ‘‘Science of 

Science Measurement’’. The first goal is to create a dialogue between the Federal 

S&T agencies and the research community about relevant models, tools, and data 

that advance scientific measurement in key areas of national S&T interest. The second objective is to identify a joint Science of Science Policy (SoSP) research agenda 

for the Federal S&T agencies and the research community. The workshop has four 

modules intended to advance measurement in: 1) Economic benefits; 2) Social, 

health and environmental benefits; 3) S&T workforce development; and 4) Technology development and deployment. Four academic researchers will be presenting 

in each module, with a rapporteur synthesizing the presentation at the end of each 

module. 

The audience will be primarily science policy practitioners from the Federal agencies who are interested in very practical issues, such as: getting new ideas about 

how to manage their portfolios in a more scientific manner; developing performance 

and outcomes metrics; measuring the return on investment; and using science to 

identify emerging trends in the U.S. scientific enterprise. 

Another activity has been the establishment of a website to provide information 

on best practices to Federal and non-Federal agencies. The website (http://

scienceofsciencepolicy.net) was launched in January 2010, and has become a model 

for other interagency groups (including the Forensic Science interagency group). The 

web site serves as a repository for data, documents, research papers, and communication tools for the communities of users. , The site receives over 2,000 hits a 

month. The associated Listserv is the highest visibility listserv in science policy, and 

has over 720 members. 

The interagency group meets monthly, and has active participation by over 15 

agencies. It is actively providing input to the Center of Excellence on Science Policy 

being established by the State Department in the Middle East.

3) Please provide a brief description and update on the status of the OSTP 

led project on science metrics, known as STAR METRICS, including a description of international engagement and interest in this 

effort 

The STAR METRICS project is a federal and university partnership to document 

the outcomes of science investments to the public. The benefits of STAR METRICS 

are that a common empirical infrastructure will be available to all recipients of federal funding and science agencies to quickly respond to State, Congressional and 

OMB requests. It is critical that this effort takes a bottom up approach that is domain specific, generalizable and replicable. 

Currently, the project is structured in two phases:

- Phase I: The development of uniform, auditable and standardized measures 

of the initial impact of ARRA and base budget science spending on job creation.

- Phase II: The development of broader measures of the impact of federal 

science investment, grouped in four broad categories:

• Scientific knowledge (such as publications and citations) and, later,

• Social outcomes (such as health and environment),

• Economic growth (through patents, firm start ups and other measures),

• Workforce outcomes (through student mobility and employment),

Phase I of the STAR METRICS project began in earnest in March of 2010 with 

funds formally designated for the project. The participation agreement was signed 

in May 2010, and a press release was issued by the three lead agencies: NIH, NSF 

and OSTP2. As noted in that press release: 

‘‘A new initiative promises to monitor the impact of federal science investments 

on employment, knowledge generation, and health outcomes. The initiative—

Science and Technology for America’s Reinvestment: Measuring the EffecT of 
23

3http://www.euractiv.com/en/science/eu-looks-to-us-model-for-measuring-rd-impact-news448950

Research on Innovation, Competitiveness and Science, or STAR METRICS—is 

a multi-agency venture led by the National Institutes of Health, the National 

Science Foundation (NSF), and the White House Office of Science and Technology Policy (OSTP).’’

In Phase I, through a highly automated process, with essentially no burden on 

scientists and minimal burden for administrators, STAR METRICS collects longitudinal employment data from the participating institutions to be able to assess the 

number of jobs created or retained (or lost) through federal funding support. The 

system is set up such that all jobs will be captured and not just principal investigators and co-principal investigator. In addition, in Phase I, STAR METRICS can provide estimates of jobs supported through facilities and administration (F&A) costs 

and through various procurement activities in the institutions. 

STAR METRICS will also help the Federal government document the value of its 

investments in research and development, to a degree not previously possible. Together, NSF and NIH have agreed to provide $1 million in funding a year for the 

next five years. 

More agencies are joining the STAR METRICS consortium. While meetings of the 

Consortium are convened by OSTP, the lead agency is NIH, which is hosting the 

data infrastructure. The official STAR METRICS website will be available September 30 2010. NSF is providing key leadership in engaging the scientific community, particularly through the SciSIP program. 

Phase II of the project expands the data infrastructure to incorporate the broader 

impact of science investments on scientific, social, economic and workforce outcomes. 

In keeping with the bottom up approach of the program, STAR METRICS is beginning a formal set of consultations with the scientific community to understand what 

data elements and what metrics the community would find useful to find in STAR 

METRICS. The first of these will occur October 22, 2010, with a meeting with Vice 

Presidents for Research of interested institutions. Other meetings will follow with 

research agencies and other interested groups. 

In a very short period of time since formalizing the project, over 100 researchintensive universities, mostly from the Federal Demonstration Partnership (FDP), 

have expressed interest in participating in STAR METRICS; about 20 are contributing data. Universities have expressed enthusiasm and support for the project. 

Science is fundamentally an international endeavor. And so must be its evaluation. In fact, there has been substantial international interest. Members of the 

STAR METRICS team have provided information or directly briefed Brazilian and 

Japanese science and technology agencies. The State Department is actively interested in learning about the program to advance the science of science policy in the 

Middle East. 

Our most active international counterpart, however, is the European Union. A 

major presentation was given to the European Parliament in April 3. A joint EU/US 

conference has been proposed for March 2011 in the Rockefeller Foundation’s 

Bellagio Center. The goal is to produce a roadmap that will outline a path for creating a US/European collaboration in developing a common theoretical and empirical infrastructure to describe and assess the outcomes of science investments. To 

achieve this, it will bring together key European and US science policy experts and 

makers, administrators and academic researchers. The group is carefully chosen to 

consist of the key players from the US side who have the experience in developing 

such an infrastructure in the US. The European attendees will consist of individuals 

who have both the deep understanding of the issues and the ability to effect change 

in Europe in a collaborative framework with the US. 

The outcomes will include a roadmap that represents a combined effort to build 

on and extend existing efforts in both regions: notably the US investment in the 

STAR METRICS program and the European efforts to build better assessments for 

their investments. It is hoped that the roadmap will have the same success that the 

Science of Science Policy Interagency Roadmap had in the United States and that 

in the EU the road map will be the basis for including assessment measures in future legislation implementing science programs.

Conclusion 

The NSF’s Science of Science and Innovation Policy program, the NSTC’s Interagency SOSP ITG, along with STAR METRICS, represent the first efforts to construct a scientific framework that is supported by multiple agencies and multiple 

institutions—all jointly engaged. It represents a true bottom up approach to pro-
24

viding an evidence basis for U.S. science policy. Its success is important for decisionmakers: in a nutshell, you can’t manage what you can’t measure and what you 

measure is what you get. 

NSF’s innovative Science of Science and Innovation Policy program, and STAR 

METRICS, can help all of us do a better job in explaining this essential symbiosis. 

This concludes my testimony, Mr. Chairman. I look forward to answering any 

questions you or Members may have.

BIOGRAPHY FOR JULIA I. LANE

Dr. Julia I. Lane is the Program Director of the Science of Science & Innovation 

Policy program at the National Science Foundation. Her previous jobs included Senior Vice President and Director, Economics Department at NORC/University of Chicago, Director of the Employment Dynamics Program at the Urban Institute, Senior 

Research Fellow at the U.S. Census Bureau and Assistant, Associate and Full Professor at American University. 

Julia has published over 60 articles in leading economics journals, and authored 

or edited six books. She became an American Statistical Association Fellow in 2009. 

She has been the recipient of over $20 million in grants; from foundations such as 

the National Science Foundation, the Sloan Foundation, the MacArthur Foundation, 

the Russell Sage Foundation, the Spencer Foundation, the National Institute of 

Health; from government agencies such as the Departments of Commerce, Labor, 

and Health and Human Services in the U.S., the ESRC in the U.K., and the Department of Labour and Statistics New Zealand in New Zealand, as well as from international organizations such as the World Bank. 

She has organized over 30 national and international conferences, received several 

national awards, given keynote speeches all over the world, and serves on a number 

of national and international advisory boards. She is one of the founders of the 

LEHD program at the Census Bureau, which is the first large scale linked employer-employee dataset in the United States. A native of England who grew up in 

New Zealand, Julia has worked in a variety of countries, including Australia, Germany, Malaysia, Madagascar, Mexico, Morocco, Namibia, Sweden, and Tunisia. 

Her undergraduate degree was in Economics with a minor in Japanese from 

Massey University in New Zealand; her M.A. in Statistics and Ph.D. in Economics 

are from the University of Missouri in Columbia. She is fluent in Swedish and German and speaks conversational French.

Chairman LIPINSKI. Thank you, Dr. Lane. Dr. Sarewitz. 

STATEMENT OF DANIEL SAREWITZ, CO-DIRECTOR OF THE 

CONSORTIUM FOR SCIENCE, POLICY & OUTCOMES AND 

PROFESSOR OF SCIENCE AND SOCIETY, ARIZONA STATE 

UNIVERSITY 

Dr. SAREWITZ. Thank you, Chairman Lipinski and Ranking Member Ehlers. I very much appreciate the invitation and the opportunity to testify. So, my name is Daniel Sarewitz. I am a Professor 

of Science and Society at Arizona State University where I Co-Direct the Consortium for Science Policy and Outcomes, which works 

to understand and improve the linkages between science and technology and social outcomes. We are located on ASU’s Tempe campus. We also have a location here in DC. We are a highly interdisciplinary and collaborative organization involving researchers at 

dozens of other institutions. We are also fortunate to receive generous grant funding from NSF, including from the Science of 

Science and Innovation Policy Program, so I declare my vested interest in the outcomes of this hearing. 

I would like to make three brief points in support of my over-extensive written testimony. The first is about the importance of the 

SciSIP Program itself. With shrinking discretionary budgets, vibrant economic competitors, and daunting challenges to our wellbeing, the Nation needs effective tools for making better decisions 

about how to design, assess, and set priorities for our science and 
25

innovation enterprise. For the most part, we lack these tools, as we 

have already heard. As former Presidential Science Advisor Jack 

Marburger said in 2005, ‘‘the nascent field of social Science of 

Science Policy needs to grow up, and quickly.’’

With modest resources, SciSIP is mobilizing a community of researchers to focus on the complex problem of how to bring the most 

out of our public investment in R&D. SciSIP reacted quickly to support research assessing the impacts of stimulus funding for R&D, 

and is beginning with NIH to take on the incredibly complex problem of evaluating what the nation gets for its enormous investment 

in bio-medical R&D. These are really difficult challenges and it is 

hard to see how this committee and others at the helm of the R&D 

enterprise can guide it effectively in the absence of such efforts. 

A second point is that outputs are not outcomes. And SciSIP 

needs to focus on outcomes. Outputs are immediate products of 

R&D like publications, and patents, and Ph.D’s. Outcomes are 

what people care about, not just economic growth, but of course 

economic growth, but also secure and affordable food supplies and 

energy supplies, high quality public health, a clean environment, 

expanding job opportunities and strong national defense. The 40-

year war on cancer has yielded the output of remarkable new scientific knowledge yet very modest gains in public health outcomes 

despite the tens of billions spent. Thirty years of energy R&D output have done little to advance the outcome of reducing our vulnerability to energy-based threats to security, economy, and environment. Research on science and innovation policy to date has given 

us a pretty good idea how to design and assess science policies to 

advance outputs. But we still have a lot to learn about how to implement and assess successful outcome-based science and innovation policies. 

My final point is that research on outcome-based science and innovation policies and the use of such research by decision makers 

are not separate problems. While the SciSIP Program is commendably serious about disseminating its research and its results to policy makers, the dissemination problem is also structural. That is it 

is built into the way we organize much research including SciSIP, 

and its great strength in supporting bottom-up inquiry on fundamental problems is also a weakness when there is an urgent need 

for new knowledge, the need that Dr. Marburger pointed out. Such 

cases require close ties between those who do research and decision 

makers who might use research results. We already heard from 

Julia Lane about her efforts to create those ties. Now on the one 

hand, these ties allow researchers to understand the needs of decision makers and to recognize the types of information that will be 

both usable and used. But at the same time, close ties allow decision makers to understand what research can and cannot do for 

them. Such mutual understanding breeds trust and value, and usable science. 

There are many examples of federal programs that link research 

performance and research use, including USDA’s Agricultural Extension Service, the USGS Earthquake Hazards Program, and 

NOAA’s Regional Integrated Sciences and Assessments Program. 

Similarly, DARPA is justifiably well regarded for its capacity to 

connect the technology needs of DOD to research groups in aca-
26

demia and the private sector. These and other examples are discussed in the handbook ‘‘Usable Science’’, which I just happened to 

have brought along with me, which summarizes the results of 

CSPO’s [Consortium for Science, Policy & Outcomes] five year NSF 

Decision Making Under Uncertainty project, carried out jointly 

with researchers of the University of Colorado. 

These lessons can be applied to SciSIP. Let me mention three 

possibilities. First, NSF could sponsor one or more large centers for 

SciSIP research, education, and outreach with a core requirement 

to build strong, ongoing collaborative links between researchers 

and science policy decision makers. Second, NSF could work with 

mission-oriented R&D agencies to integrate SciSIP activities into a 

range of existing outcome-oriented programs. Third, NSF could require all of its center-scale awardees, such as Science and Technology Centers and Engineering Research Centers, to be designed 

from the outset to include integrated SciSIP components. 

Through these sorts of approaches, SciSIP could enhance its capacity to produce usable knowledge for the near to medium term 

and help accelerate a convergence between science and innovation 

policy research and policy decisions across a range of R&D outcome 

priorities. Thank you for your attention. I look forward to discussing these issues more. 

[The prepared statement of Dr. Sarewitz follows:]

PREPARED STATEMENT OF DANIEL SAREWITZ

Mr. Chairman, Members of the Committee, thank you for inviting me to testify 

today. My name is Daniel Sarewitz, and I am co-founder and co-director of the Consortium for Science, Policy, and Outcomes at Arizona State University, as well as 

Professor of Science and Society at ASU. My formal training was in geosciences, but 

for more than 20 years I have worked in science and technology policy, first as a 

AAAS Congressional Science Fellow and then a staffer on this Committee, working 

for Chairman George E. Brown, Jr., and more recently as an academic, at Columbia 

University and now at ASU. So I’m very pleased to return to the place that 

launched me on a new and incredibly interesting and exciting career path and intellectual journey, and honored that you have asked for my input to the Committee’s 

deliberations on the status of the science of science and innovation policy.

Introduction: Input-Output Science and Innovation Policy 

Most people agree that government support of research and development is an essential foundation of today’s complex, knowledge-based, high technology society. Yet 

the problem of how to make the most out of the nation’s investment in R&D remains amazingly poorly understood. This problem has been actively debated in Congress since World War II. In the interim the annual public investment in R&D has 

grown from a few tens of millions of dollars to about 140 billion dollars. Yet, 

throughout this period of remarkable growth—and, I should say, remarkable bipartisan support for such growth, exemplified by this Committee—the basic principles, 

terms of debate, and policy tools for guiding investment and measuring its effects 

have changed remarkably little. 

For more than sixty years, the core of science policy has been the belief that more 

money for R&D translates into more benefits for the nation. Science policy has, 

above all else, been science budget policy. The capacity of the nation to solve problems related to science and technology has been measured by the incremental 

growth of the R&D budget. The idea that the size of the R&D budget is a measure 

of the social value of science and technology remains the bedrock of science policy. 

Three other powerful beliefs have dominated science policy decision making. The 

first is that research becomes valuable for society as part of a linear progression 

starting with basic discovery and leading to application, either in the form of technological innovation, or information to inform decision making. The second, related 

belief is that there is a clear distinction between research activities aimed at creating new knowledge, and research aimed at applying that knowledge to solving 

problems. The third belief is that scientific excellence, as defined and assessed by 
27

scientists themselves, typically through the peer review process, is the best measure 

of the potential value of science for society. 

The result of these beliefs has been a national R&D enterprise that is largely understood and discussed in terms of simple inputs—how much money is being spent 

on which type of science?—and simple outputs—how much scientific knowledge is 

being produced? That this simple input-output way of understanding science and 

technology policy led to the world’s largest and most productive R&D enterprise is, 

however, much more of a happy historical accident than an endorsement of this way 

of looking at R&D policy. 

Coming out of World War II, the U.S. simply had no serious scientific or economic 

competitors, so we had a huge head start that only began to be seriously eroded in 

the 1980s. Moreover, the U.S. R&D enterprise as a whole was—and still is—so 

much bigger than that of any other nation that simply as a function of scale it 

could—and still does—outperform everyone else. An additional crucial point is that 

by far the dominant player in translating the public R&D investment into tangible 

societal outcomes was the Department of Defense. The core of DOD’s approach was 

the cultivation of very powerful linkages between high-tech private sector firms, research universities, and the DoD itself, an arrangement that was responsible for 

creating most of the important technological systems that undergird our society and 

our economy today. 

I present this thumbnail sketch to explain how we have arrived at the situation 

in which we find ourselves today. The limits of the post-War input-output approach, 

as I have said, became increasingly clear starting in the 1980s, with the rise of serious economic and technological competitors, especially in east Asia; with the end of 

the Cold War, and the decline of DoD’s catalytic role in civilian technological innovation; and with the increasing awareness of an array of social challenges that seemed 

to demand scientific and technological solutions—from cancer and emerging infectious diseases to energy security and environmental quality. Yet if one looks at the 

endless series of reports over the past decades sounding the alarm bells about the 

nation’s science and technology enterprise, one finds the problem still discussed predominantly in terms of the same old input-output measures: how much are we 

spending, how many scientists are we producing, how many publications or patents 

are issued, and how do these input-output numbers compare to our economic competitors? 

The problem with the input-output model is that it can’t tell us very much about 

what actually matters: how the size, organization, and productivity of the R&D enterprise itself relates to the achievement of the societal outcomes that we desire and 

expect. Because pretty much everyone assumed that these outcomes flowed automatically from the R&D enterprise, as long as it was big and scientifically productive, there seemed to be no reason to worry about how the enterprise worked. These 

assumptions put a damper on research, as well as debate, about the complex relations between scientific advance, technological innovation, and the well-being of society. Why try to understand these issues if the only thing that really mattered was 

the size of the budget? 

But in an era of constrained resources and mounting challenges to our well-being, 

the limits of the input-output approach have become impossible to ignore. We cannot ignore them because we need to make difficult choices about how to allocate 

scarce resources. We also cannot ignore them because we are faced with strong 

prima fascia evidence that the input-output approach is leading to significant 

science and innovation policy failures. For example, the National Institutes of 

Health’s forty year War on Cancer has yielded remarkable new scientific knowledge, 

yet remarkably modest public health benefits for the tens of billions spent. The devastation of New Orleans by Hurricane Katrina occurred despite the existence of 

comprehensive scientific knowledge about the inevitability and precise consequences 

of such an event. Thirty years of energy R&D has left the nation no less vulnerable 

to energy-based security, economic, and environmental threats than it was when the 

Department of Energy was created. These are not input-output problems, but they 

are science and innovation policy problems. 

In 1992, this Committee issued a brief ‘‘Chairman’s Report’’ entitled the ‘‘Report 

of the Task Force on the Health of Research,’’ which pointed at the need to re-think 

basic assumptions about science and innovation policy. (As a Committee staffer at 

the time, I was privileged to be one of the members of that Task Force.) While there 

certainly were, at that time, small pockets of academic scholarship on the links between science policy and societal outcomes, and while some federal S&T programs 

had of course had great success in achieving the outcomes that the public expected 

from them, the fact is that there existed in the United States at the end of the 20th 

century an extraordinarily modest capacity to develop knowledge, tools, and human 
28

resources that would allow the nation to improve its capacity to turn progress in 

S&T into progress toward desired societal outcomes. 

A turning point in achieving high level attention and action came in 2005, when 

President Bush’s science advisor, John Marburger, speaking at the Science and 

Technology Policy Colloquium of the American Association for the Advancement of 

Science, declared that ‘‘The nascent field of the social science of science policy needs 

to grow up, and quickly.’’ His point was that the nation could no longer afford to 

set policy for one of it’s most important areas of public investment on the basis of 

simplistic ideas that had arisen in a very different world, half-a-century ago. The 

National Science Foundation responded to the urgency of Dr. Marburger’s call by 

creating the Science of Science and Innovation Policy (SciSIP) program.

Committee Question 1. (A) Please provide an overview of the research activities of the Consortium for Science, Policy, and Outcomes. (B) 

How are you facilitating interdisciplinary collaborations within 

the Consortium? (C) What new and continuing areas of research in 

the science of science and innovation policy (SciSIP) could significantly improve our ability to design effective programs and better 

target federal research investments? (D) What are the most promising research opportunities and what are the biggest research 

gaps?

Background to CSPO: 

The Consortium for Science, Policy, and Outcomes (CSPO) was conceived in 1997 

during discussions between myself and Michael M. Crow, who was then Executive 

Vice Provost at Columbia University, and formally launched in 1999. The decision 

to create CSPO was made for much the same reasons that SciSIP was created: despite the overwhelming importance of science and technology in our society, policy 

makers and scholars almost completely lacked the knowledge and tools necessary 

to make informed and effective decisions. CSPO was founded as one small effort to 

begin to reverse this lack of capacity. 

When Michael Crow became President of Arizona State University he asked me 

to move to ASU as well, and gave me the opportunity to help transform CSPO from 

a small research and policy center to a broader consortium with expanded ambition 

and reach. Today this consortium operates at three organizational levels: First, 

there is a core group of fifty or so faculty, researchers, students, and staff who work 

directly in CSPO, mostly in Arizona but with several of us located here in Washington, DC. Second, there is a significantly expanded group of collaborators throughout ASU as a whole, ranging from many of the university’s top scientists and engineers, to faculty and students in ASU’s programs on public policy, law, business, 

architecture and design, communications, journalism and even the arts. Third, we 

have deep and persistent collaborations with researchers and students at other universities in the U.S. and around the world. Virtually all of our major research 

thrusts are carried out in collaboration with individuals or groups at other universities, and CSPO hosts an continual stream of visiting scholars and students, many 

from foreign universities and research institutions, for periods of up to two years. 

In briefly describing CSPO’s major research activities, I want to emphasize a 

point that should be obvious but is often lost in discussions of the Science of Science 

and Innovation Policy. Public support for science and innovation is justified for a 

wide range of reasons, many of which are non-economic. For example, we count on 

science to provide a safe, abundant, and tasty food supply for a growing population; 

ensure the protection of our natural environment and the provision of reliable and 

affordable energy; protect and improve our health; help ensure national security; 

and create new and challenging work opportunities. The reason I belabor this obvious point is that in fact we are particularly empty-handed when it comes to understanding how best to design and assess S&T policies aimed at advancing these noneconomic outcomes. This is the arena where CSPO focuses most of its efforts. 

CSPO is engaged in a wide range of research activities that seek to advance 

knowledge, real-world practice, and human resources in this broad domain of 

science and innovation policy for social outcomes. And I want to gratefully acknowledge the National Science Foundation’s generosity in providing peer-reviewed grant 

support for many of our most important and I would say high-risk, high-pay-off 

ideas, through a variety of its programs, including SciSIP. 

At the core of all of our research is a commitment to looking at S&T activities 

as part of larger social systems. Trying to understand and assess the outcomes of 

science and innovation by studying and measuring research and development activities alone is like analyzing a family’s home life by studying lumber mills and brick 

kilns. What makes a given line of research valuable for society? Of course the 
29

science itself must be of high quality, just like a fine home needs to be constructed 

of quality materials. But for investments in science and innovation to support desired social outcomes, many other elements will come into play: the ways that scientists choose projects; the culture and organization of research institutions; publicprivate interactions; economic incentives and regulatory structures; public preferences and behavioral norms—all this and more make up the process by which 

knowledge, innovation, and social benefit are connected.

1. (A) Please provide an overview of the research activities of the Consortium for Science, Policy, and Outcomes. 

With this background, let me outline some of our efforts, in four areas of direct 

relevance to the science of science and innovation policy. 

(1) CSPO’s flagship research program is our Center for Nanotechnology in Society 

(CNS), an NSF Nano-scale Science and Engineering Center which has just been renewed for a second and final five-year grant period, under the directorship of CSPO 

co-director Professor David Guston. CNS takes a systems view of technological innovation to ask: what are the factors that may influence whether an emerging domain 

of technology, in this case nanotechnology, is able to move toward areas of social 

need and desired outcomes? CNS involves multiple universities and researchers 

from multiple disciplines bringing numerous specialties to bear on what we call 

‘‘real-time technology assessment,’’ or a capacity to understand linkages between 

new knowledge, emerging innovations, and societal outcomes—as they are unfolding. 

Among the many specific research activities encompassed by CNS are relatively 

traditional tools for assessing scientific productivity such as citation and patent 

analysis, as well as proven methods for tracking public opinions and preferences. 

But we also bring social scientists together with nanoscale scientists and engineers 

to reflect on the choices available to them for advancing nanotechnology, and to develop and discuss future scenarios of nanotechnology-enabled society. We cultivate 

ongoing discussions with the public about potential benefits, problems, and dilemmas of nanotechnology. We bring graduate students working on nanotechnology into 

discussions of science policy and social outcomes. We work with science and technology museums to create programs and exhibits that go beyond technical explanations to help people understand the ways that nanotechnology and society influence each other. 

In total, what we are trying to create with CNS is a test-bed for developing a 

more holistic understanding of science, innovation, and social outcomes, where the 

choices made about science, innovation, and their application in society are brought 

out in the open and discussed even at the earliest stages of the innovation process, 

to bring into better alignment the directions of science and innovation, and the aspirations and needs of society. I also hope it is clear from this brief description that 

standard categories of ‘‘basic research,’’ ‘‘applied research,’’ ‘‘education,’’ and ‘‘outreach’’ are not pursued separately, but are part of an integrated approach at CNS. 

I want to emphasize three elements of U.S. science policy that made this research 

program possible. First was the explicit desire of this Committee and the Congress 

in general, as expressed in the 21st Century Nanotechnology Research and Development Act of 2003, to ensure that nanotechnology advanced along with a capacity to 

understand unfolding social implications. Second was the complementary recognition by the National Nanotechnology Initiative, under Mihail Roco’s early leadership, and the National Science Foundation, that understanding the social aspects 

of nanotechnology should be an important aspect of the overall nanotech research 

agenda. And third was ASU itself, a university that has made huge strides in reducing the barriers to true interdisciplinary collaboration, and that is simultaneously 

committed to connecting the work of its faculty and students to the needs of society. 

(2) A second project I want to mention is Science Policy Assessment and Research 

on Climate (SPARC), funded through NSF’s Decision Making Under Uncertainty 

program. SPARC is a collaboration with the Center for Science and Technology Policy Research at the University of Colorado, and we are finishing the project up after 

a five-year funding period. SPARC explores a question that lies at the heart of 

science and innovation policy: what makes the results of a scientific research project 

useful, and usable? While the broad context for this project was the nation’s considerable investment in research related to climate, our research looked at science policy decision making aimed at many different problems, including water management, weather and natural hazards, nanotechnology, technological standards, agriculture, and ecology. 

SPARC results reinforce a major point: science policies tend to be more successful 

when they are carried out through institutional arrangements that allow scientists 

and decision makers to understand each other’s needs and capabilities. Fostering 
30

close, ongoing, trusting relations between those who produce new knowledge and 

those who might benefit from it seems to be an essential attribute of science policies 

that lead to new knowledge quickly moving into society for public benefit. Drawing 

on the lessons of this major project, we produced a short handbook for science policy 

decision makers, called ‘‘Usable Science.’’ We released this report last April at a 

meeting here in DC that attracted about 100 participants, many from federal agencies. The handbook is available at: http://cstpr.colorado.edu/sparc/outreach/

sparc¥handbook/. (3) A third project, called Public Value Mapping, or PVM, has been supported by 

the SciSIP program, as well as the V. Kann Rasmussen Foundation and the Rockefeller Foundation. The idea behind PVM draws on my previous point that most publicly funded S&T activities aim to advance a variety of social outcomes, not just economic ones. PVM finds that these desired social outcomes—what we call ‘‘public values’’—are clearly expressed at many levels across the science and innovation policy 

endeavor—in legislation and laws; in the strategic plans and budget documents of 

R&D agencies; in the websites and press releases of individual R&D programs and 

even projects. 

Because public values are harder to characterize, measure, and assess than economic values, they are often given short shrift both in debates about science and 

innovation policies, and in research to evaluate the outcomes of such policies. Yet 

a key concept for PVM is that the public values associated with science and innovation policies may conflict with one another, and with economic values. For example, 

a new medical technology may create profit for a corporation and benefit from those 

who have access to the technology, even as it contributes to health care outcome disparities and over-diagnosis and unnecessary treatment. PVM seeks to unravel and 

clarify such complexities, in order to help view and assess the full range of social 

outcomes tied to science and innovation policies. 

In brief, our research aims first to identify public values across a particular area 

of science and innovation policy. We then analyze how various value statements actually relate to each other (for example, are they complementary or contradictory?) 

and assess whether the research activities are in fact organized in ways that may 

allow them to achieve those values. Our work is still preliminary. During three 

years of NSF-supported research, we have completed a set of detailed case studies, 

looking at S&T policy issues such as technology transfer, nanotechnology for cancer 

treatment, and environmental chemistry. One intriguing, but still quite preliminary, 

result of our work is that we think we can say something about the potential for 

a major research program to achieve desired social outcomes based in part on how 

public values are articulated across the program’s various levels and components. 

For example, our study of natural hazards research at the U.S. Geological Survey 

shows a strong coherence among public values expressed by scientists, the agency, 

legislative mandates, and various stakeholders, whereas our analysis of Federal climate change research shows considerable diversity and even conflict among values 

within and across these various levels of activity. We are now working to test the 

hypothesis that the relations among public values may in fact be predictive of a program’s performance. If this turns out to hold up after further research, it could offer 

a powerful tool for assessing the capabilities of science and innovation policies. 

(4) As one final example, I want to mention CSPO’s growing work on energy technology innovation. This is a cross-cutting theme that works its way into a number 

of our research projects, but I think it helps to communicate our overall approach. 

Consider, for example, solar energy technologies, which may have particular potential to serve energy needs in a desert state like Arizona. Yet to understand the potential for solar energy R&D to contribute to Arizona energy needs, one also needs 

to understand issues of regulatory incentive, land use, water access and availability, 

public lands management, agricultural policies, transmission corridors, military 

bases, Indian reservations, even immigration. Each of these variables may play a 

crucial role in determining the outcomes of solar energy science and innovation policies—and policies that do not attend to these variables run the risk of failing to 

achieve their desired social outcomes, regardless of levels of funding or scientific 

productivity.

1. (B) How are you facilitating interdisciplinary collaborations within the 

Consortium? 

CSPO facilitates interdisciplinary collaboration in three main ways. First, we organize our activities around problems, not around disciplines, and then we bring 

into our research teams the expertise that we need to help us understand what’s 

going on and how to make progress. 

Second, as an administrative matter, CSPO is located in ASU’s College of Liberal 

Arts and Sciences, so it does not have a disciplinary affiliation. Our core faculty 
31

members have advanced degrees in fields ranging from earth sciences and electrical 

engineering to political science and philosophy. Core faculty are jointly appointed 

between CSPO and a variety of academic units, including the Schools of Life 

Sciences; Government, Politics, and Global Studies; Human Evolution and Social 

Change; Geographical Sciences and Urban Planning; Sustainability; Communications; and Social Transformation. If these don’t sound like familiar names for traditional academic disciplines, that’s because ASU itself has moved to reorganize 

standard departments into interdisciplinary units in order to bring appropriate intellectual force to bear on complex problems. 

Third, we have worked hard to cultivate long-term collaborations with natural scientists and engineers across the university, many of whom are affiliate faculty 

members at CSPO. We work with these colleagues to design new educational and 

research projects and programs that return value both to CSPO and to our science 

and engineering partners. These activities create familiarity and trust that allow us 

to engage in higher-stakes collaborations. For example, many of the major scienceand-engineering grant proposals submitted by ASU to funding agencies now include 

an integrated set of activities aimed at understanding and enhancing societal outcomes. We have even been funded by NSF, partly with the support of the SciSIP 

program, to study the impacts of natural science-social science collaborations in labs 

at ASU and around the world.

1. (C) What new and continuing areas of research in the science of science 

and innovation policy (SciSIP) could significantly improve our 

ability to design effective programs and better target federal research investments? (D) What are the most promising research opportunities and what are the biggest research gaps? 

CSPO faculty members have been brainstorming over the past few weeks to develop a short list of ‘‘foundational/transformative’’ research challenges in response 

to a call for ideas issued by NSF’s directorate for Social, Behavioral, and Economic 

Sciences. Given CSPO’s orientation, our ideas, not surprisingly, are directly relevant 

to the SciSIP program. 

1. Science and innovation policies often aim to help transform existing technological systems to achieve particular societal outcomes: for example, to move the nation’s energy system toward a more economically, environmentally, and geopolitically secure technology base; or to move the nation’s health care system to achieve 

better health outcomes at lower cost. New scientific and technological advance are 

obviously going to be key drivers of such transitions. Yet modern societies have very 

little understanding of how to catalyze and steer these sorts of complex system 

changes, and well-intentioned efforts can often lead to unanticipated consequences 

whose benefits are very difficult to assess, as we have seen, for example, in efforts 

to advance alternative biofuels. A key SciSIP research priority should be to 

gain fundamental understanding about the drivers and dynamics of transitions in complex socio-technical systems.

2. Science and innovation policies are, in one sense, a bet on the future: that a 

certain type of knowledge or technology will prove useful or valuable. Yet the future 

of social and technological change is impossible to predict in detail. To try to deal 

with this unpredictability, a relatively small number of forward-thinking companies, 

academic units, and non-profit organizations employ a variety of techniques and 

tools that can allow them to better visualize, understand, and discuss a range of 

alternative possible futures. Such activities can inform decision making by helping 

to make clear the broad array and potential implications of scientific, technical, and 

social options and pathways available for addressing social challenges. SciSIP 

should support the study and assessment of existing tools, and the development and testing of a range of new tools, to bring future-visioning techniques to bear on science and innovation policy making processes.

3. In general, SciSIP should emphasize support for research and education programs that foster integration between natural sciences and engineering, and social sciences. Such integration can help to ensure that science 

and engineering activities are conceived and carried out with a realistic understanding of the social context in which knowledge and innovation are pursued and 

applied. In turn, social scientists will gain a deeper, and earlier, understanding of 

the potential futures that cutting edge R&D programs are making possible. The result should be a growing capacity to design and conduct science and innovation activities that are better able to contribute to desired social outcomes. 

4. SciSIP should consider supporting the development of a set of case 

studies to identify and characterize the key attributes of S&T institutions 

and programs that strongly link science and innovation activities to desired social outcomes. Case studies should range across the S&T enterprise, sam-
32

pling a variety of sectors, scales, structures, and desired outcomes. Such a program 

would need to be coordinated to ensure comparability between the methods and organization of the cases. Its institutional and programmatic focus would make it distinct from, and complementary with, the STAR METRICS approach that NSF and 

sister agencies are already taking. This case-based effort should focus on the development of a set of key organizational principles that science and innovation policy 

makers can use to guide investment strategies and priorities.

Committee Question 2: Is the Federal Government, specifically the National 

Science Foundation, playing an effective role in fostering SciSIP 

research and the development of a community of practice in 

SciSIP? What recommendations, if any, do you have for the National Science Foundation’s SciSIP program? 

Overall, I believe that NSF is doing a good job in building the SciSIP program 

and community. But this is a very difficult task. The community of researchers 

working in the SciSIP domain is rather small and very diffuse. In fact, it does not 

really identify itself as a single community, but rather as several independent communities, for example, innovation economics, science and public policy, and science 

and technology studies. So there’s simply not a lot of capacity yet in this domain, 

and what capacity there is needs to be better integrated. Moreover, most of the 

quantitative data available for analysis of science and innovation policy is input-output data—budget levels, numbers of scientists and graduate students, publication 

numbers, patents, and citations, and so on. Such data can be subjected to highly 

sophisticated data mining and analysis techniques using ever-improved software 

packages designed for this purpose, so it is very attractive to researchers. But this 

kind of input-output data can offer only an incomplete and in many ways distorted 

view of the societal value of the S&T enterprise, a view that does not allow us to 

escape the simplistic beliefs of the past. 

Now it’s clear that those running the SciSIP program understand these problems. 

They brought together a good cross section of the community to help plan the program in the spring and summer of 2005; they have sought to attract grant applications from a wide array of researchers; they have organized or otherwise supported 

events to bring together SciSIP researchers to build a sense of integrated community; they have provided grant support to a diverse set of research approaches and 

problems; and they are working through the STAR METRICS program to try to 

build better quantitative data sets that can assist certain types of analytical work. 

All this is very positive. 

To some extent, however, NSF’s institutional strength is also a weakness here. 

The agency prides itself on its bottom-up approach to setting its research agendas. 

While the SciSIP program does reflect a top-down decision to create a new program 

area, in part as a response to concerns repeatedly expressed by then-Presidential 

science advisor Marburger, the shape and direction of SciSIP has significantly been 

dictated by the existing research community. Much of that community continues to 

work within the input-output model of science and innovation policy, due, as I’ve 

said, to existing data sources and tools. For similar reasons of measurement ease, 

the community also tends to focus on economic outcomes to the significant exclusion 

of the much broader range of societal outcomes that the nation seeks to derive from 

its S&T investment. Because researchers and peer reviewers are drawn from the 

same general communities, such tendencies can be difficult to escape. 

A range of tools are potentially available for building the community and its coherence, and driving the intellectual agenda away from an input-output framework, 

and toward a systems-oriented, outcomes-focused approach. Not all of these tools require new money. SciSIP should use program guidelines and requirements to transform and build the research community; indeed, this year’s program announcement 

is notable for its openness to a wide range of approaches to SciSIP research. SciSIP 

could also consider using some of its budget to support training grants, 

similar in spirit, if not in scale, to NSF’s successful IGERT (Integrated 

Graduate Research and Traineeship) program, as a way to more quickly 

build up capacity. However, if the Committee, and NSF, believe that the science 

and innovation policy research community needs to be significantly larger and more 

coherent, this will probably require more resources. To reinforce my position 

throughout this testimony (also see my comments on ‘‘dissemination,’’ below), any 

claim to a bigger budget must be matched by programmatic design elements to help 

ensure that knowledge created by SciSIP is both usable and used. This would likely require a commitment to fund integrated Science and Technology Center-type science and innovation policy research organizations that can create and support ongoing interaction between SciSIP researchers and policy 
33

makers, perhaps analogous to NOAA’s Regional Integrated Science and Assessment 

program.

Committee Question 3. Please describe the education and outreach activities of the Consortium for Science, Policy, and Outcomes. 

CSPO sponsors a wide variety of education and outreach activities, ranging from 

formal degree programs and intensive, short-term training activities, to public outreach events and products targeted at science and innovation policy makers.

1. Graduate Degree Programs 

The ASU Professional Science Masters in Science and Technology Policy was initiated in 2009. It provides professional education for students seeking advanced public, non-profit, or private sector careers in science and technology policy and related 

fields in the United States or abroad. Students learn essential skills, knowledge, 

and methods for analyzing innovation, expertise, and large-scale technological systems. Particular emphasis is placed on the political and societal contexts and impacts of science and technology policy. The program is a one-year, 30-credit cohortbased program designed to attract students of the highest caliber in their early to 

mid-careers. Key learning outcomes of the program include:

• Understanding of the theoretical foundations of the interactions among 

science, technology, and society.

• Understanding of US and, where appropriate to a student’s career interests, 

international science and technology policies and the policy processes that 

generate them.

• Analysis of knowledge systems supporting policy decisions.

• Analysis of the social and policy dimensions and implications of large-scale 

technological systems.

• Analysis of scientific and technological innovation systems.

• Skills in collaborative, team-based analysis of science and technology policy 

problems.

• Skills in effective professional communication.

Ph.D. Program in the Human and Social Dimensions (HSD) of Science and Technology. Here CSPO collaborates with ASU’s Center for Biology and Society and Center for Law, Science, and Technology to offer a highly interdisciplinary and integrative program of advanced study. We aim at training scholars and practitioners to 

understand and inform the conceptual and philosophical foundations of scientific research; to analyze and assess the increasingly powerful roles of science and technology as agents of change in society and the economy; and to challenge universities 

to become leaders in fostering the new science and technology policies necessary to 

meet the problems and opportunities of the 21st century. 

The HSD curriculum is flexible, combining a strong, integrated, first-year experience, with substantial freedom for students, in conjunction with their advisors, to 

design carefully crafted programs of study relevant to their own areas of interest 

and expertise. The curriculum trains researchers with the necessary skills and preparation to analyze three key aspects of the study of the human and social dimensions of science and technology: 1) the historical, philosophical, and conceptual foundations of science and technology; 2) the social and institutional foundations of scientific research and technological systems; and 3) the political, ethical, and policy 

foundations of science and technology. 

Research projects of current HSD students supported by CSPO include:

• Social and ethical challenges of smart grid development

• Leadership training in graduate science and engineering education

• Comparative analysis of interdisciplinary research fields in the US and China

• The emergence and stabilization of legal regimes in online communities

• The role of non-governmental organizations in energy siting decisions in the 

United States

• Public values and public engagement in energy policy in the United States

• The organization and management of international scientific assessment processes

• Connecting knowledge to decision making in water policy

• information technology in learning & inequality
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2. Non-Degree Programs and Training 

Ph.D. plus. This integrative, non-degree program offers advanced graduate students in science and engineering the chance to consider how their research relates 

to the world of science policy and the relationship between science, technology and 

societal outcomes. Science and engineering students work with a CSPO faculty 

member to write an additional chapter of their dissertation that explores the social 

implications, political context, or ethical concerns of their work. The Ph.D. plus process is informal, and is arranged by discussions between the student, her or his dissertation advisor, and the CSPO advisor. Most Ph.D. plus students take one or more 

classes offered by CSPO faculty; attend seminars and other activities sponsored by 

CSPO; and in general interact closely with the CSPO community for an academic 

year or more. 

In the annual DC Summer Disorientation, cohorts of about 15 science and engineering graduate students spend two weeks in Washington, DC interacting with the 

government officials, lobbyists, staffers, regulators, journalists, academics, museum 

curators, and others who fund, regulate, shape, critique, and study science and technology. Students participate in interactive role-playing experiences where they may 

testify at mock Congressional hearings; work under tight deadlines to write briefing 

papers for senior officials; or write op-ed pieces for a demanding editor. The goal 

is to help future scientists develop an understanding of the political and social context of their research. CSPO has recently expanded this program and now accepts 

graduate students from outside of ASU. 

The Next Generation of Science and Technology Policy Leaders. Here we are seeking to catalyze a community of early-career science policy scholars who can span the 

terrains of intellectual inquiry and real-world practice, communicate effectively to 

general audiences, and contribute to effective decision making on key issues of 

science, technology, and society. We organized a national competition to select a 

dozen early-career science policy researchers and practitioners (5 years or less since 

Ph.D). This ‘‘Next Gen’’ group prepared draft papers, and each scholar was then 

paired with an early career ‘‘communicator’’ (typically a writer working through new 

media). The scholar and the communicator collaborated to craft a compelling, nonscholarly description of the scholar’s work—something that would appeal to a general audience. Next Gen scholars also led a roundtable discussion where each presented her/his research to a group of about 40 people at a major CSPO-sponsored 

conference, to allow the scholars to hone the more technical aspects and presentation of their work, and to interact intensively with an engaged audience. Next Gen 

scholars are now working on two versions of their research papers, one for a policymaking audience, and one for an academic audience. This project was supported by 

grants from NSF’s programs on Science, Technology, and Society, and Informal 

Science Education.

3. Outreach 

CSPO views outreach as an integral part of its operations at all levels—not as 

a separate, add-on, or late-stage activity. As described above, our research and education programs often involve policy makers, members of the public, and scientists 

and engineers, and so also serve an outreach function by creating and strengthening 

links and communication between CSPO scholars and these other groups. Indeed, 

in many cases it is difficult to know where research ends and outreach begins. For 

example, much of our work on energy innovation policy is presented to policy makers and the media in briefings and policy reports at the same time as it is written 

up for academic audiences (see: http://www.cspo.org/projects/eisbu/). Similarly, 

SPARC involved numerous workshops that brought scientists and science policy 

makers together in a way that enhanced both communication and learning. 

The integration of outreach and education is apparent in CSPO’s growing collaboration with science museums and science centers. We view these collaborations as 

ways of reaching wider audiences and increasing the ability of our graduate students—social scientists as well as natural scientists and engineers—to communicate 

to broader audiences. Our Center for Nanotechnology in Society has fostered a national strategic partnership with the NSF-funded Nano-Scale Informal Science Education Network to develop programs and exhibition materials and plans that incorporate societal interests and outcomes in communicating about emerging technologies. CSPO opens science communication opportunities for scientists and engineers through its monthly Science Cafe ́ series with the Arizona Science Center and 

incorporates museum-floor experience into its integrated training of doctoral scientists and engineers. CSPO is also working with the Museum of Science, Boston 

and the National Academy of Engineering to plan a national educational campaign 

to focus on climate change and engineered systems, to prepare the next generation 
35

of engineers, citizens, and leaders to meet the challenge of adapting the nation’s 

technological infrastructure to climate change. 

Overall, we are continually engaged in a wide variety of efforts to make our ideas 

accessible to the public and policy makers, through informal and formal meetings 

and briefings in the Phoenix area and in Washington, DC; through ‘‘handbooks’’ for 

decision makers; through ongoing contact with the media; as well as by writing opeds and articles for non-technical magazines, websites, and blogs. We have just received a small supplement to our SciSIP grant on Public Value Mapping to produce 

engaging, instructional web-based videos for science policy practitioners. New outreach products and activities are promoted via CSPO’s monthly electronic newsletter, which goes to over 3000 people in academia, government, and industry. In 

all, I think it is fair to say that CSPO views outreach, education, and research as 

equally necessary foundations for pursuing its mission.

Committee Question 4. How can the dissemination of SciSIP research findings be improved so that policymakers are better informed of the 

current state of research? Are there best practices that can be implemented by the Federal government and/or the research community to improve the incorporation of science and technology policy 

research into the decision making process? 

SciSIP program officers, in collaboration with their grantees, with organizations 

like the American Association for the Advancement of Science, and with other federal agencies, has made an impressive effort to ensure that research results are 

made available to science and innovation policy makers, through the SciSIP website 

and listserve, and through a variety of workshops, including one to be held this coming December. 

SciSIP and NSF more broadly face something of a dilemma here, however. As I’m 

sure the Committee well appreciates, academic researchers are generally not rewarded for communicating their work to policy makers, or even for making the results of their work comprehensible to non-experts. I’m extraordinarily fortunate to 

work at a university where this is not the case. Moreover, given the fundamental 

nature of much of the research supported by SciSIP, the extent to which project results can translate into results immediately useful to decision makers may be highly 

variable. At the same time, it’s fair to say that science and innovation policy decision makers may not always be either receptive to, or able to act on, the results 

of research conducted under SciSIP. 

In line with many of the comments I’ve already made, and consistent with research done by CSPO and many other groups, the best way to further improve the 

value of SciSIP research for decision makers would be to increase the level of interaction between the researchers and decision makers. This point should not be interpreted as a criticism of the current SciSIP program, which as far as I can tell is 

effectively pushing the boundaries of typical NSF practice, and working at the limits 

of its human and fiscal resources, to try to maximize dissemination. 

Yet ensuring that researchers are providing knowledge that decision makers can 

actually use is not only a matter of ‘‘dissemination,’’ it is also structural. For SciSIP 

results to be both usable and used, researchers and decision makers must each come 

to understand the needs, capabilities, and languages of the other—a process that 

we have termed, in our SPARC project, ‘‘reconciling the supply and demand of research.’’ Such a reconciliation takes time and ongoing interaction. It can certainly 

be pursued along multiple paths—through joint committees, workshops, personnel 

exchanges, interviews and surveys, and so on—but the key is ongoing and meaningful interaction leading to mutual understanding. An NSF research program, even 

one advanced with the creativity and vigor that characterizes SciSIP, is unlikely to 

be able, by itself, to provide the sort of institutional infrastructure that leads to the 

production of consistently usable knowledge. The idea of integrated SciSIP centers, 

previously mentioned, could be one way to create a greater capacity to move ideas 

into use. Federal agencies and programs that sponsor mission-oriented research, 

and that have a proven record of producing usable knowledge, might also be able 

to play a role here to help achieve the necessary integration.
36

Committee Question 5: What are the fundamental skills and content knowledge needed by SciSIP researchers and practitioners? What are 

the backgrounds of students pursuing graduate degrees in science 

and technology policy, and what career paths are sought by these 

graduates? Is the National Science Foundation playing an effective 

role in fostering the development of science and technology policy 

degree programs at U.S. universities? If not, what recommendations, if any, do you have for NSF and/or the universities with such 

programs? 

As I’ve suggested, the domain of SciSIP research and practice cannot and should 

not be defined by any particular set of skills or area of knowledge. In fact, given 

the complexity and diversity of the challenges facing SciSIP policy makers, it will 

be important to keep the field as open and flexible as possible, where the necessary 

skills and knowledge are determined based on the problem at hand, and on the evolution of the field itself, rather than some arbitrary boundary. I’ve already mentioned the varied backgrounds of CSPO’s core faculty group, and our graduate students are if anything even more diverse, coming to us with degrees in business, information systems, science and technology studies, astrophysics, political science, 

law, English, public policy, library and information science, philosophy, physics, biology, environmental science, geology, anthropology, sociology, and industrial management. 

Graduate training in science and technology policy is also diverse, occurring in 

many different types of programs, with many institutional and administrative arrangements, in many U.S. universities. There is no standard-model science and 

technology policy graduate degree, and given the complexity of the field perhaps 

that is just as well, but it does create challenges in terms of attracting resources, 

creating an identity, and setting priorities. Similarly, while many career paths are 

open to those who have advanced training and degrees in science and technology 

policy, there is no formula for how to build or advance a career in this field, as there 

is in, say, law, medicine, or engineering. In CSPO’s brief experience with graduate 

education, we do see our students and post-docs progressing on traditional academic 

paths, but they are also going into the private sector, working at nongovernmental 

organizations, and taking up positions in government agencies and think tanks. I 

also want to emphasize the importance that we place on ‘‘continuing education’’ via 

our professional Masters program, which we hope will reach mid-career professionals already working in areas related to science and technology policy, and equip 

them with tools to do their jobs more effectively, or to move into more complex jobs, 

in the public, private, and nongovernmental sectors. 

As I discussed in my response to Question 2, NSF’s SciSIP program, as well as 

its Science, Technology, and Society Program, are working hard to build a sense of 

community and identity among science and technology policy researchers, and to 

provide support for research across a broad domain of problems and applications. 

However, as discussed at length by about 75 members of the community at this 

summer’s Gordon Conference on Science and Technology Policy, the traditional academic structure of universities remains a considerable obstacle to building long-term 

capacity in the field, and most science and technology policy programs exist in the 

margins and spaces of standard disciplinary schools and departments. I am fortunate enough to work at a university whose leadership has a strong commitment to 

cultivating interdisciplinary, problem-based research that can link knowledge creation to solutions for complex societal problems. Yet even at ASU the long-term future of science and technology policy research probably depends on finding a way 

to more closely knit CSPO into the fabric of the formal academic units on campus. 

One conclusion here is that NSF’s ability to foster the development of the field 

of science and technology policy is partly dependent on incentivizing universities to 

recognize SciSIP as a field worth cultivating. While the SciSIP program is certainly 

of a scale sufficient to mobilize and motivate individual researchers working on 

science and innovation policy, it is probably not big enough to get the attention of 

university administrators. I have already emphasized the potential value of applying an integrated Science and Technology Center model to building the SciSIP community and moving its research results into use. An NSF commitment to supporting 

one or more such centers would also send a strong signal to university leaders that 

the science of science and innovation policy is a national priority, deserving of 

strong focused effort and investment from our universities.
37

BIOGRAPHY FOR DANIEL SAREWITZ

Daniel Sarewitz is Professor of Science and Society, and co-director and co-founder 

of the Consortium for Science, Policy, and Outcomes (CSPO), at Arizona State University (http://www.cspo.org). His work focuses on revealing the connections between science policy decisions, scientific research and social outcomes. How does the 

distribution of the social benefits of science relate to the way that we organize scientific inquiry? What accounts for the highly uneven advance of know-how related 

to solving human problems? How do the interactions between scientific uncertainty 

and human values influence decision making? How does technological innovation influence politics? And how can improved insight into such questions contribute to 

real-world practice? He is the author of Frontiers of Illusion: Science, Technology, 

and the Politics of Progress (Temple, 1996), an exploration of the public myths that 

underlie decisions about science and technology; the co-editor of three other books; 

and the author of many articles about the interactions of science, technology, and 

society. In addition to scholarly journals his work has appeared in The Atlantic 

Monthly, The New Republic, and many newspapers; from December 2009 until September 2010 he wrote a monthly column on science policy for the journal Nature. 

His work has also received featured coverage on NPR’s Morning Edition, in the New 

York Times and the Chronicle of Higher Education. From 1989–1993 he worked on 

R&D policy issues for the U.S. House of Representatives, first as a AAAS Fellow 

in the office of Congressman George E. Brown, Jr., and then as a staffer on the 

Committee on Science, Space, and Technology. He received a Ph.D. in Geological 

Sciences from Cornell University in 1986. He now directs the Washington, DC, office 

of CSPO, and focuses his efforts on a range of activities to increase CSPO’s impact 

on federal science and technology policy processes. His new book, The TechnoHuman Condition (co-authored with Braden Allenby; MIT Press) will be published 

in March 2011.

Chairman LIPINSKI. Thank you, Dr. Sarewitz. And it is the beginning of votes, but we should be able to get to the testimony in 

here. Dr. Murray. 

STATEMENT OF FIONA MURRAY, ASSOCIATE PROFESSOR OF 

MANAGEMENT, TECHNOLOGICAL INNOVATION & ENTREPRENEUR GROUP, MIT SLOAN SCHOOL OF MANAGEMENT 

Dr. MURRAY. Okay. Thank you very much. Thank you, Chairman 

Lipinski and other Members of the Subcommittee, for the opportunity for being here. My name is Fiona Murray as you heard before I am a Professor of Innovation and Entrepreneurship at the 

MIT Sloan School and I am also Associate Director of the MIT Entrepreneurship Center. 

Now to start my remarks I thought I would just describe the perspective I bring. Briefly, I am the grateful recipient of two SciSIP 

Grants. I worked on what I would think of as a SciSIP oriented research agenda for more than a decade, although I really only discovered the SciSIP research community in about 2006. As a faculty 

member of a business school I also engage on these issues with 

managers, scientists themselves who are also interested, sometimes 

at the lower levels, in how to organize effectively to ensure the productivity and impact of their research. 

I should also just say something about my own training. I have 

a background, a Bachelor’s, Master’s, and Ph.D. in Chemistry. That 

is a very unusual training for somebody who does SciSIP. I think 

it enables me to bring a unique understanding of the bench science 

to this research, although as I do note in my written remarks I am 

not sure that this is an ideal past to learn the rigorous social 

science methods that one really needs. I have had to rely on again 

self-education and some very patient co-workers to get me over 

what I think is a quite high bar to make a serious contribution to 
38

this endeavor, and in particular to do it in a way that contributes 

to the policy and the scholarly debate. 

I want to just take my time to see if I can make three points. 

I will make two if time—if only time permits. Something about the 

vision of SciSIP that—from what I think that means about the 

kinds of gaps there are in the research. And then also how I think 

the scientific community might more effectively be organized to 

really have an impact in terms of research links to the community 

and in particular education. 

So I think that SciSIP is not completely about doing science and 

technology analysis. I think there’s already an excellent scholarship 

describing policy initiatives, the government attitude toward 

science, and the politics of science and innovation policy. But I 

think that what SciSIP brings, which is unique, is this sort of scientific lens to the problem. And what I mean by that is that it is 

a serious and I think important attempt to undertake causal analysis and evidence-based analysis asking whether and how particular policy interventions actually have an impact, whether it is 

in the short run or the long run. And so I think that good scientific 

research defines impact richly: it is about the level of the rate and 

the direction of scientific progress and innovation, but it is also 

about long run impact on economic growth. 

But I also want to emphasize this causal piece of what kinds of 

policies we think make a difference. I think that at its best, SciSIP 

defines policy broadly but precisely in particular research instances. And so it can mean everything from high level national 

policies, the laws, but also agency implementation processes, agency selection processes, but below that, community behaviors, things 

like the Bermuda Laws and so on. And even at some microlevel, 

lab level choices around how we choose to organize the scientific research at the ground level. 

I think a key approach to SciSIP has been grounded in two recent developments. One is the data development which has already 

been discussed. But I would also say it has been enabled, actually, 

by a massive scientific data infrastructure investment, so some of 

my own work has really been enabled by investments in things like 

GEN Bank and that ability to interrogate genetic data to then do 

science policy analysis. 

But also I think a second piece of social science methods is in 

program evaluation. Actually, you are familiar with this from the 

work that you do on evaluating education policy. But I think that 

the ability to use experiments and causal analysis and so on from 

that policy evaluation tool kit is extremely important to pushing 

SciSIP forward. 

So I think that SciSIP has really been critical and attracted serious cause, but in my view there are still some gaps. To pick up the 

‘‘straw and bricks’’ analogy, it strikes me that while we need bricks, 

if we want to cross the bridge from data to understanding we actually have to build a bridge with those bricks. And what does that 

mean? I think that does mean more analysis as well as just measurement. I think at the moment a lot of the scientific work, including my own, is intrinsically focused on biologists and on funding at 

the National Institutes of Health. That is critical, but not the only 
39

1 Accessed from http://www.nsf.gov/funding/pgm¥summ.jsp?pims¥id=501084&org=sbe 9/16/

2010. 

arena, and I think that there is—we do need to understand how 

other disciplines and other agencies are working. 

I think that there has been a focus on national-level rules and 

specific agencies and less on these community-level choices about 

how to organize structure, collaborations, and more informal efforts. I think we also need to focus on distributional issues. So not 

just how many more papers are produced, but what kind of a 

breakthrough or everyday science, what kinds of research, are they 

American or foreign, and so on. I don’t think we have focused 

enough on that. 

And let me in the last few seconds just say something about the 

SciSIP community. I think that the community actually needs to 

do more of its own bottom-up organizing. The NSF has done a tremendous job in kind of structuring it in a top-down way, but that 

is a huge amount of work for one agency to do. And I think as a 

community we need to do a more bottom-up in order to both engage 

in more knowledge exchange among ourselves and to focus on education. And I think the educational imperative at the Ph.D. level 

does need to be organized across a number of campuses. And then, 

as I think at the policy level of our links, the policy makers again 

have to be organized in a more community-based way. So I would 

suggest that that needs to be done through a consortium of universities but with this tripartite mission of research, education, and 

then links to policy. And I will leave my remarks there. Thank you 

very much. 

[The prepared statement of Dr. Murray follows:]

PREPARED STATEMENT OF FIONA MURRAY

According to the National Science Foundation (NSF), the Science of Science & Innovation Policy (SciSIP) program ‘‘supports research designed to advance the scientific basis of science and innovation policy 1. The program is an important and 

bold attempt to build a strong intellectual foundation for science and technology policy making regarding the laws and rules that shape the institutional environment 

in which scientific research and innovation takes place. It does so by adopting recently developed, leading-edge methodological approaches based on both large scale 

empirical data analyses and complementary qualitative analyses. The explicit goals 

of the program are to fund research that ‘‘develops, improves and expands models, 

analytical tools, data and metrics that can be applied in the science policy decision 

making process’’. From my perspective as a SciSIP scholar, I conceptualize the 

SciSIP agenda as the systematic, evidence-based and causal analysis of the impact 

of policy interventions on the rate, direction and impact of scientific knowledge production and innovation. If successful in research and in coupling to policy decisions 

then this agenda will enable Federal and state policymakers, as well as others engaged in shaping the production and translation of scientific knowledge (including 

scientists themselves, universities, Foundations and scientific communities), to design more effective policies and practices that ensure that investments in science 

and innovation have rapid and extensive scientific, social, and economic impact. 

In this testimony I lay out my personal views of the SciSIP program from the perspective of an NSF–SciSIP scholar (and grant recipient), and as a Faculty member 

in a leading School of Management who engages routinely with scientists concerned 

with the impact of their research, policy students as well as MBA students and executives hoping to work effectively at the academic-commercial interface. 

In what follows I examine some recent breakthroughs that have enabled SciSIP 

research, outline some of the key research emerging from SciSIP to date and critical 

gaps. I then turn my attention to what I observe as the need for greater community 

building and finally, the potential for a significant educational initiative. 
40

The notion that there can be a ‘‘science’’ of science and innovation policy is relatively recent (Marburger 2005). There is a long and distinguished traditional of 

science policy research nonetheless, the current focus on measuring the causal influence of science and innovation policy levers at different levels (national policy, agency interventions as well as community and lab-level actions) can be linked to advances in economics and related fields in the early 1990s. During this period, leading economic historians including Paul David, Joel Mokyr and Nathan Rosenberg 

developed critical conceptual breakthroughs in understanding the economics of 

science and innovation as grounded both in institutions (policy levers) but also in 

the micro-level behaviors and incentives of scientists and engineers themselves. 

Building on economics as well as the sociology of science, they came to view Science 

as a distinctive institution in several ways: as a knowledge production system, as 

an input into technological innovation, and as a reward system. 

The empirical promise of this conceptual agenda was taken forward by a group 

of economists and sociologists who aimed to evaluate the impact of public policies 

on research behavior, research outputs, and associated economic outcomes 

(Marburger, 2005; Jaffe, 2006). In following this agenda, scholars confront a number 

of key challenges. In particular is it possible to separate the influence of a particular 

policy or institution from the underlying nature of the scientific knowledge that is 

being developed? To put it more simply, in the policy ‘‘whodunit’’ it is often hard 

to say whether it is the policy that had the effect of speeding up scientific progress 

in a particular area or a chance in our understanding of a scientific problem. Without a parallel universe for policy experiments, when one observes the production or 

diffusion of a piece of knowledge within a given policy environment, one cannot directly observe the counterfactual production and diffusion of that knowledge had it 

been produced and diffused under alternative policy conditions. To resolve these 

challenges, SciSIP scholars have combined methodological advances in program 

evaluation- particularly a ‘‘natural experiments’’ approach—with novel data techniques. The experiments-based approach (with which the committee is likely familiar from its work on education) relies upon methods pioneered in public finance and 

program evaluation (Meyer, 1995; Bertrand, Duflo, and Mullainathan, 2004; Angrist 

and Pischke, 2008). To complement these methods, SciSIP scholars have made extensive use of novel datasets including data on publications, patents and most recently citations. This approach uses these ‘‘documents’’ as the core objects of analysis, assuming that they represent ‘‘pieces of scientific knowledge,’’ and citation 

analysis to investigate the impact of institutions on the cumulativeness of discovery 

and innovation (Garfield, 1955, De Solla Price, 1970; Jaffe, et al, 1993; Griliches, 

1990, 1998). When placed within a framework to evaluate science and innovation 

policy, these elements constitute a robust approach to analyzing and tracking the 

causal impact of public policies on science and innovation inputs and outputs. 

The power of the emerging SciSIP agenda is to incorporate these novel approaches 

and therefore move beyond description and observation of science at work or particular policies towards the more systematic analysis of particular institutional 

interventions. Thus pioneering SciSIP research typically combines three elements:

i) Providing clear theoretical foundations for understanding the ways in 

which institutional change (at any level) might influence the behavior of 

scientists and therefore the rate and direction of their knowledge production.

ii) Building careful empirical designs that enable causal analysis, and undertaking these empirical studies using systematic data gathering methods at 

different levels (including quantitative data but also including qualitative 

studies).

iii) Grounding the analysis in a deep understanding of the phenomenon—the 

details of the particular policy changes or organizational choices as well as 

the ways in which these shape scientists daily life.

As a contributor to the broader SciSIP agenda and approach, my research in the 

past few years has focused on the conflicts and compromises shaping the boundary 

between academic science and the commercial world—especially the impact of intellectual property (IP) rights and IP licensing strategies over basic scientific research 

in areas as diverse at human genetics, stem cells and cancer biology. More recently 

I have expanded my research to examine the community and organizational-level 

interventions that scientists can make including understanding how research quality is governed (through retractions) and how projects are selected and evaluated). 

In my own work, I have found that my training as a scientist provides aids in the 

third element of the SciSIP approach but my work is strongly based on the theories 
41

and methods of economics and sociology of science and therefore links the three aspects outlined above. 

A research project of mine recently completed with a series of co-authors illustrates the SciSIP approach to the analysis of science policy. It was designed to adjudicate one policy element of the institutional complex—the impact of intellectual 

property rights on research tools (and the licenses that shape access to such tools) 

on scientific productivity and diversity. Rather than theorizing broadly, it focuses 

specifically on one controversial episode in the genetics community initiated by the 

discovery, patenting and then exclusive licensing of mouse genetics technology (the 

Oncomouse approach and the related Cre-lox approach) and the subsequent licensing agreement made among DuPont, the Jackson Laboratories and the National Institutes of Health to enable greater access to these key research tools. 

In The Oncomouse that Roared (Murray 2010), I take a qualitative approach to 

the question of whether and how the Oncomouse patent influenced the scientific 

community. Rather than compare the mouse genetics community to another scientific field (which may have any number of inherent differences), I compare the periods before and after the Oncomouse patent was granted and licensed. For 3–4 

years, with no intellectual property rights yet granted the mice were subject only 

to the informal norms that characterize a competitive, but collegial, scientific community. After the grant of the patent, DuPont (exclusive licensee) strongly enforced 

its property rights on scientists. Through detailed interviews and documentary analysis comparing the pre- and post- patent period, I follow the SciSIP approach and 

closely analyzed the impact of the Oncomouse patent on mouse geneticists. I find 

that some scientists reluctantly acquiesced, dealing with complex contracts. Others 

defied DuPont, sharing mice informally in the face of opposition from their universities. Behind the scenes other more complex changes were also taking place as scientists sought to reshape the role patents in their scientific life. This is reflective 

of broader changes in the scientific community in the face of higher levels of commercial interest and engagement and the resistance to the encroachment of highpowered commercial interests. Such a grounded perspective highlights the importance of understanding how scientists respond to policy interventions and has a 

number of policy implications. However it also raises a more SciSIP-oriented question about the causal impact of the compromise (when the NIH persuaded DuPont 

to sign a Memorandum of Understanding making Oncomice open for experimentation) on the level and type of research using these genetically modified mice i.e. 

do such policy interventions shape the rate and direction of science. 

I examine the causal impact of these shifts to greater openness in ‘‘Of Mice and 

Academics’’ (Murray et al. 2010). The ‘‘dependent variable’’ in this paper is the level 

and type of scientific research publications that use genetically engineered mice in 

each year from 1990 until 2006—based on a dataset of over 20,000 publications that 

are coded by their level of basicness, the rating of the journal in which they are published, the rank of the school affiliations of the authors etc. The ‘‘independent variable’’ is the timing of the policy shift in the openness of particular types of 

transgenic mice (Onco mice and Cre-lox mice). To aid in the interpretation of the 

data we also include a control group of papers that build on mice never influenced 

by intellectual property rules. A central idea of this research design is that while 

research discoveries (such as engineered mice) are developed at a given point in 

time, their use by subsequent researchers takes place over time. This insight motivates a differences-in-differences approach to the analysis of follow-on scientific research: If the policy environment governing the incentives and/or ability to build on 

published discoveries changes over time (and affects only some discoveries but not 

others), it is possible to identify the impact of the policy change by examining how 

the pattern of follow-on research (captured in published articles) changes after the 

policy intervention. In other words, policy changes that impact one group of articles 

and not another can constitute a natural experiment. This paper exemplifies the 

SciSIP approach by linking (microeconomic) theory about the way researchers respond to openness, with data/empirics that allow for causal analysis, and a sufficiently detailed understanding of the policies and practices of scientists to enable 

appropriate research design. We find that the NIH MoU did indeed increase not 

only the level of research using these mice but also spurred a greater diversity of 

researchers to move into the field, follow novel paths and take new approaches. 

Taken together these two papers address questions of how institutional and organizational changes shape the rate and direction of scientific knowledge. They follow 

the three key elements of the SciSIP approach by carefully and precisely focusing 

on the phenomenon at hand, using that detailed understanding to link theories of 

scientists’ behavior to careful data, and building empirical strategies in a way that 

enables causal analysis, normative conclusions and theoretical contributions.
42

2They do this by comparing the research profiles of similar biologists some of whom receive 

more open ended long-term funding from Howard Hughes while others receive more traditional 

R01-style grants from the NIH.

ASSESSING THE GAPS IN SciSIP KNOWLEDGE 

As outlined above, the SciSIP agenda presents far reaching research opportunities 

for scholars whose goal is to contribute to the social sciences, to our understanding 

of science and innovation in the economy and to have policy impact. A number of 

significant gaps in the current state of knowledge remain and can be usefully considered around the organizing framework laid out below. This describes SciSIP research according to the level of analysis at which the policy interventions are taking 

place: national rules and regulations, agency-level interventions, community norms 

and practices and organizational actions. I then propose three cross-cutting questions that apply to each level (see below). To illustrate this perspective and the gaps 

it reveals, I first describe research on high level rules and regulations then move 

to more micro-level analysis of organizational interventions.

• National rules and regulations: This includes research on the effectiveness 

of national rules and regulations on the rate and direction of scientific 

progress. A major area of focus includes research on the influence of the 

Bayh-Dole Act on university researchers (Owen-Smith and Powell 2003). In 

my own recent research, we have examined the impact of US regulations with 

regards to the funding of research in the area of human embryonic stem cells 

(Furman, Murray and Stern 2010). Gaps at this level of analysis remain with 

regards to the role of international rules and regulations on science in the 

United States, and the ability of U.S. researchers to remain highly competitive 

and at the knowledge frontier in the light of growing global spending on scientific research. In addition it would be valuable to understand how the particular funding levels, structure and incentives of university systems in different countries impact downstream outcomes, such as scientific production, 

firm founding, and health & welfare, and how they contour the impact of government policies such as those related to intellectual property rights.

• Agency or University-level rules and norms: Funding agencies, especially 

the Federal government, have a variety of opportunities to shape the rate and 

direction of scientific progress. Both areas have up to now been poorly understood. Recent work funded by SciSIP has made significant progress along 

these two dimensions but gaps remain. In particular the influence of non-Federal funding sources particularly corporate funding and the growing foundation funding is poorly documented and understood.

Æ Shaping the Direction of Research: Funding agencies, as they select 

among research projects and shape the expectations and controls they 

place on researchers have a variety of opportunities to influence knowledge production. This has often been thought of as a black-box with the 

scientific community utilizing the peer review system as the best mechanism to self-regulate and shape direction. Pioneering analysis by my MIT 

colleagues shows that exceptional scientists are much more likely to 

produce innovative breakthrough science when using long-term grants 

that allow them exceptional freedom in the lab (Azoulay et al, 2010) 2. 

This study raises the question of how researchers are encouraged to move 

into new and emerging research areas, and how to encourage ideas at the 

high-quality high-risk tail of the distribution. 

We must encourage more research to understand the impact of funding 

choices and funding incentives on the type of research outcomes. This 

agenda could also benefit from the analysis of scientists outside the U.S. 

in settings where different types of incentive systems exist. In line with recent interest in Challenges (prizes) as an alternative incentive mechanism, 

we should also extend this analysis to include other funding mechanisms 

or reward systems.

Æ Shaping the Disclosure and Sharing of Knowledge and Materials: 

Funding agencies have an opportunity to shape the rate and effectiveness 

with which knowledge that is generated as a result of grant-making is 

shared among scientists and is diffused into the economy along productive routes. Among the most important and controversial rules shaping 

such impact of scientific research are the rules around intellectual property rights. This has been the topic of vigorous debate particularly with 

regards to the increasing levels of patenting within the scientific community. This is the research arena in which SciSIP researchers have made 
43

3 Ben Jones, a leading scholars in the SciSIP field and author of several key papers in this 

area is currently a senior economist at the Council on Economic Advisors.

one of the greatest contributions, with their research informing policy 

discussions at the National Academies of Science, within the National Institutes of Health (NIH) and elsewhere. In particular, research has explored the impact of patenting on the rate at which that research is diffused within the scientific community and on the rate at which commercial or socially-beneficial products are developed (Murray and Stern 2007; 

Huang and Murray 2009; Walsh et al. 2003, 2005). Extensive research 

documents the impact of IP, licensing and material sharing practices on 

scientists, but gaps in our knowledge exist with regards to the impact of 

these policies on both scientific knowledge production and economic impact (few studies examine both with Williams (2010) a notable exception). 

We also have a less systematic understanding of how to design the ‘‘intellectual commons’’ in an efficient and effective manner so as to promote 

and rapid follow-on research and commercialization. There is also a significant opportunity to extend these studies beyond the study of life scientists to explore differences across research communities in a range of 

disciplines such as chemistry, computer science, materials science etc.

• Community level activities: The policies and practices that emerge from 

the scientific community also play a critical role in scientific progress and impact. Thanks to more systematic analysis of resource-sharing arrangements 

both informally (see Hauessler et al. 2009; Waltsh et al., 2005) and through 

formal mechanisms such as Biological Resource Centers, there is definitive 

evidence that investments in community-based infrastructure such as materials repositories and data repositories have a significant positive impact on 

the rate of scientific progress by enabling access, certification and sharing 

(Furman and Stern 2010). More recent analysis of the self-governance of scientific communities through the system of retractions has also pointed out the 

role of the community as a crucial analytic lens (Furman and Murray 2009). 

In another stream of research grounded in organizational theory and sociology, scholars have examined whether and how different community structures emerge in order to undertake the complex task of horizontal collaboration (e.g. Powell et al. 2004, O’Mahony and Bechky 2008) and collective work 

(Ferraro and O’Mahony forthcoming).

At this level of analysis, critical questions remain unanswered: how are scientific communities formed? How do they coalesce around new research areas 

and what role might policy-makers play in such community formation? For example do mechanisms such as those used in DARPA enable community building and how does this shape the long run effectiveness of scientific communities?

• Organizational Interventions: Scientific research is an activity increasingly undertaken by collections of scientists organized into teams, networks, 

collaborations and networks. Recent scholarship highlighted the potential for 

significant productivity benefits of specific organizational choices (Cummings 

and Keisler 2005, 2007, Wutchy et al. 2007, Jones et al. 2008) 3. Recent work 

on open source computer science communities highlights the complex and sophisticated nature of the organizational and governance choices that these 

groups of scientists can make (Dahlander and O’Mahony forthcoming) and 

their implications for the nature of the knowledge production (MacCormack 

et al. 2006, 2008). However, there remained only limited research that examines the organizational choices of scientists for specific research projects—they 

choice of collaborations, organization of tasks in the lab, governance of the laboratory. In part this gap arises because of the historic perspective of the scientist as ‘‘loan genius.’’ Moreover, the strong sense of autonomy among the scientific community has limited the research on choices that scientists themselves make. 

Opportunities for further research also cut across these levels of analysis with 

three of key importance:

i) On what field has the SciSIP research been focused? In other words, 

is the analysis focused on a particular scientific discipline or sub-field e.g. 

biology, high-energy physics, nanotechnology? In my opinion, too large a 

share of current SciSIP research (including my own) highlights the biologists to the exclusion of other arenas. For example we have little knowledge of the influence of policies on material scientists who, like biologists, 
44

4 A distributional approach would enable SciSIP scholars to assess the impact of policies on 

numerous dimensions: researcher and institution status, nature of the researchers’ institution 

(university, private firm, government lab, etc.); researcher cohort; collaboration type (e.g., within 

vs. across institution, state, country, and/or field); basic vs. applied research; journal status; article breadth (multiple subjects vs. single subject); journal reputation (‘‘impact factor’’); and network characteristics. 5Some of my own work has examined the theme of gender in scientific research. In ‘‘An Empirical Study of Gender Differences in Patenting among Academic Life Scientists’’ (Ding, Murray 

& Stuart 2006) we show that for over 4,000 life science faculty, after accounting for the effects 

of productivity, networks, field, and employer attributes, the net effect of gender remains: 

women patent at 40% the rate of comparable men. Other research in this spirit includes Ding 

et al. (2009). 6See Murray and O’Mahony (2007) for a detailed examination of the need for incentives for 

disclosure, reuse and accumulation in different knowledge communities and how these incentives are provided. 

rely on complex materials, data, images etc. Our knowledge of chemistry, 

computer science & engineering remains fragmented.

ii) On what outcomes has the SciSIP research been focused? Is the 

analysis focused on academic publications, patents or marketed products? 

As noted above, these outcomes are now well documented in the SciSIP literature. More emphasis however should be placed on linking up different 

measures i.e. publications and patents and finding metrics that capture 

commercializable or commercialized products (see Williams 2010) or measures that capture the broader knowledge landscape such as recent analysis 

of the patenting of the entire human genome (Jensen and Murray 2005). 

In this regard, data on licensing would be more valuable than patenting 

data alone and yet such information (for ideas developed using Federal 

funding) is not available. I would strongly recommend that this be changed 

to facilitate greater and more systematic analysis using measures closer to 

the outcomes and impacts of economic interest.

iii) On what part of the outcome distribution are SciSIP analyses focused? It is important that SciSIP researcher evaluate which researchers 

and which institutions were most affected by particular policy interventions 

rather than simply highlighting the average impact of particular policies. 

How do policy interventions impact the distribution of knowledge outcomes? 

While there may be no impact on the mean perhaps interventions influence 

the distribution of outcomes—with more high and low quality research. How 

might policy-levers all levels influence different researchers? What is their 

marginal impact on different groups of scientists: those at elite highly funded schools versus elsewhere, or those with international co-authorship ties 4. Studies that emphasize these distributional outcomes should be encouraged 

by SciSIP because it is from the richness and diversity of the scientific community that novel breakthrough outcomes arise. Studies could also fruitfully 

include analysis of the differential impact of policies on male versus female 

scientists 5. 

SciSIP COMMUNITY 

The SciSIP, led by the National Science Foundation with critical input from Program Officer Julia Lane has made tremendous progress in spurring a group of scholars to pioneer studies in the science of science and innovation policy. For some of 

these scholars, this represented an increase in their commitment to a field in which 

they already had an interest. For others, SciSIP was a new departure and an opportunity to move into a new and burgeoning field of great policy relevance and with 

significant intellectual challenges. The time is now ripe to move from funding of individual researchers to extending and emphasizing the SciSIP community. A stronger scholarly community—once established—will provide a number of critical benefits. It will be in a position to design and implement its own common pool re- sources and data sharing infrastructure to ensure that research methods, data and 

analytic tools are widely and effectively shared among scholars. At the moment 

there only a limited data-sharing infrastructure: the STARS program represents a 

key effort to gather new data, however many studies rely on complex historical 

datasets that incorporate rich and varied data sources but which are not shared 

across the community. While issues of confidentiality do arise, it is imperative that 

we follow the lead of the scientific communities we study and build a more effective 

infrastructure, norms and rules for data exchange and reuse 6. Community building will also enable a richer interchange across scholars whose 

disciplinary training and identify lies in different areas. At the present time, my 

perspective on SciSIP is that there exist various sub-communities largely within dis-
45

ciplinary silos who communicate but with little exchange across these traditional 

boundaries. For example, those who take an economics oriented approach gather as 

a community under the rubric of the Innovation Policy Working Group of the Bureau of Economic Research Productivity Program (including the Summer Institute 

Innovation Policy and the Economy activities). Not surprisingly however, this is not 

a forum in which sociologists, historians of science and technology or science and 

technology studies (STS) scholars share their research. In sociology there are few 

if any systematic gatherings of scholars with science policy interests and SciSIP researchers from STS and organizational behavior share similar concerns. One strong 

recommendation I have is for the NSF SciSIP program to fund the establishment 

of a ‘‘knowledge hub’’ that can orchestrate annual or biannual research meetings for 

interested SciSIP scholars. As I outline below in my comments on structuring 

SciSIP education, an effective cross disciplinary hub (that could be modeled on the 

Consortium on Cooperation and Competitiveness (CCC)) with governance from faculty from a number of key universities and rotating responsibility for cross-university research meetings and some (limited) cross-university doctoral training. Such 

a forum should also enjoy strong input from the NSF but overall would be most effective if it was organized with ‘‘bottom-up’’ support from faculty rather than managed directly by the NSF or other agency. 

Building stronger linkages between the SciSIP research community and the community of science policymakers is another key pillar of the broader SciSIP community that remains to be constructed. At the present time, there is limited awareness 

of the key findings of SciSIP research among policymakers, and SciSIP scholars 

have only been engaged in a limited way in recent debates over key changes in 

science policy. For example, in the recent discussions over the role of innovation 

grand Challenges there was very little scholarly input from the SciSIP community; 

many prize and challenge designers and implementers were involved but there was 

little or no discussion of the tradeoffs associated with the use of challenges and the 

characteristics of the most effective problems that might be solved using challenges 

(and whose which are less likely to be tractable with this incentive system). Building stronger links to the policy community is a long-term task that starts with the 

education of a new generation of policy makers to become critical consumers and 

co-producers of SciSIP research. However in the short run, links could be established with different government research funding agencies through a series of targeted workshops that bring policymakers, agency employees and SciSIP researchers 

to focus either on the issues, problems and successes of a particular agency or to 

focus on cross-cutting issues of mutual interest. This is likely to require sustained 

engagement through a series of regular meetings and dialogues in order to build up 

trust, mutual respect and an appreciation of the problems and opportunities that 

our nation’s research agencies, researchers and policymakers confront and the tools 

and insights that might guide them going forward.

SciSIP EDUCATION 

Education is a critical element of the SciSIP agenda and should be a central pillar 

of SciSIP going forward. To date the program has focused largely on research and 

establishing a community of scholars among established academics. There is a 

pressing need to determine the best mechanisms through which to build up the educational aspects of SciSIP and to fund this education. The challenge of SciSIP education can be considered along two dimensions—education of producers of SciSIP research and education of consumers/practitioners of SciSIP research.

PRODUCERS 

The educational requirements of SciSIP researchers are intensive; the approach 

requires strong disciplinary foundations in the social science. These must then be 

complemented by three other elements: theory, phenomenon, data/empirics:

• Theory: A perspective of the theoretical foundations that ground our understanding of the behavior of scientists, the scientific community, and scientific 

progress (these can include a microeconomic approach based on understanding incentives, the role of control rights etc. as well as a sociological 

focus on norms and practices or a psychological view)

• Data/Empirics: Strong data and empirical skills specific to science and science 

policy. SciSIP is grounded in a belief that while every scientific research 

project is different, systematic data gathering, the use of both large-scale 

analysis (with publication, patent, citation, collaboration data) and granular 

field-data, and careful empirical design will enable scholars to draw causal inferences regarding the impact of specific policy levers (at the national, regional, agency, university and lab level) on scientific productivity and impact. 
46

Therefore education must give researchers the ability to identify, gather and 

analyze such data

• Phenomenon: A deep appreciation for the nature of scientific work and for the 

ways in which particular interventions in scientific progress have shaped productivity, impact or direction. This is challenging for scholars without a scientific training but is essential if scholars are to find the most effective research settings for their studies and if they are to make their work relevant 

to scientists and to science policy practitioners.

The education of the ‘‘producers’’ of SciSIP research is a critical challenge that 

should be a high priority for the SciSIP community. Specifically, we must strengthen the education of PhD students who will become the leading scholars in the field 

developing the research agenda, pushing forward and filling research gaps and pioneering new methods for the scientific and rigorous analysis of science and innovation policy. The skills needed to push this agenda forward are two-fold—first a 

strong disciplinary grounding in the ‘‘home’ discipline—economics, sociology, social 

psychology etc. and second, an in-depth understanding of the theories, data/

empirics, and the phenomenon (as outlined above). 

Establishing PhD ‘‘SciSIP field concentrations’’ within traditional disciplinary PhDs: In my opinion, it is not fruitful to try and establish a new discipline within universities termed the ‘‘science of science and innovation policy’’. Instead I believe that it would be extremely valuable establish a ‘‘SciSIP field focus’’ 

within a variety of PhD programs within traditional disciplines including economics, 

sociology, public policy etc. At the present time, Public Policy schools are offering 

PhD degrees with a S&T policy focus. However, the promise of building a ‘‘science’’ 

of S&T policy is to extend the intellectual community well beyond the usual confines 

of policy analysis and ground the empirical and theoretical study of scientific productivity and impact in economics and sociology, as well as psychology and other 

adjacent disciplines. Therefore, as a complement to S&T Policy PhD education in 

Public Policy Schools it is critical to establish the field of ‘‘SciSIP’’ within the traditional education of PhD social scientists within their traditional departments. [It is 

worth noting that this is not an effective educational path for those from a scientific 

background to move into SciSIP. To do so requires a switch into a social science program to learn the foundations of the particular social science discipline followed by 

a SciSIP field focus]. 

Let me illustrate the proposal of a ‘‘SciSIP field focus’’ with the case of economics: 

Building a ‘‘SciSIP field focus’’ within economics would involve establishing a suite 

of courses and educational materials at a small number of leading departments (who 

could share materials, exercises, data etc.). This could then be complemented by 

educational ‘bootcamps’ which would bring these PhD students together (from across 

schools) in a common forum to build their skills, build community and hear from 

leading SciSIP scholars. Such an approach would mirror the development of entrepreneurship as a field of study within economics—an area that was pioneered by 

the ‘‘Entrepreneurship Bootcamp’’ funded by the Kauffman Foundation and taught 

at the National Bureau of Economics. The National Bureau of Economic Research 

has played an important role in coalescing much of the activity around education 

in the economic foundations of entrepreneurship through the Entrepreneurship 

Working Group now part of the Productivity Program. This has enabled vibrant 

cross-school collaboration not only on research but also teaching. At the PhD level 

this has helped to build up and educate a community of young scholars within economics departments and management schools who now have additional training allowing them to pursue this field within their discipline. 

Hub and Spoke Approach: To build a strong and effective SciSIP-oriented PhD 

educational program will require using Federal education funding to actively seed 

a ‘‘SciSIP’’ field focus within at least 4 to 5 schools per disciplinary area (with at 

least two disciplines represented)—the Spokes. This should be supplemented by 

funding to develop an effective SciSIP ‘Hub’ for PhD education. The SciSIP Hub 

would coordinate activities that encourage coordination across these educational efforts, community building activities for the students involved, and the community 

‘‘Bootcamp’’. One model to develop and effective SciSIP ‘Hub’ for PhD education is 

the Consortium on Cooperation and Competitiveness (CCC) which ‘‘links together 

scholars interested in long-run performance of U.S.-based companies and institutions’’ but with a recent focus on PhD-level education, training and community 

building among PhD students from a number of programs (based mainly within 

leading Business Schools) with the involvement of academic faculty. As they described, ‘‘No single U.S. university or graduate school contains a ‘‘critical mass’’ of 

scholars from diverse disciplinary backgrounds concerned with issues that are primary to CCC. Accordingly, the network structure of the Consortium is a significant 
47

7http://businessinnovation.berkeley.edu/ccc.html

8The CCC was funded by an initial endowment of $500,000 in May 1988 by the Walter and 

Elise Haas Fund. It has also been supported by grants from the Alfred P. Sloan Foundation 

in New York, the Smith Richardson Foundation, the Pew Foundations, the Ford Foundations, 

and the Herrick Foundation. From 1990–1995, the Sloan Foundations was the primary funding 

source for the Consortium. At the current time, the funding for doctoral activities is largely provided by individual schools supporting their students and hosting the event and by the 

Kauffman Foundation.

source of strength.’’ 7 A similar argument can be made with regards to the SciSIP 

agenda, suggesting that a similar consortium could be invaluable in advancing the 

PhD education and the scholarly community.8

CONSUMERS 

The consumers of SciSIP research include Science and Technology policy makers 

as well as scientists and engineers at different stages in their education. Each of 

these groups could benefit from a deeper understanding of the results of SciSIP research. In particular, it should be a high priority of the SciSIP community to ensure 

that the SciSIP agenda is well understood within S&T Policy education; S&T Policy 

graduates are key stakeholders in the SciSIP research community will be leading 

consumers of our research, and partners in future research design and implementation. 

Science & Technology Policy Masters Education: As students with Masterslevel education in science and technology policy move out into the policy community, 

into research-based public policy organizations, and into the funding agencies that 

are the subject of much SciSIP analysis, they should be educated to be critical consumers of SciSIP research and to be co-producers of that research in partnership 

with academics. Much SciSIP research is relatively new and involves novel methods 

that are highly technical in nature and are not always taught to public policy researchers. Therefore, SciSIP has not yet been incorporated as a central pillar into 

the S&T Policy curriculum. For example, I supervise a number of MIT Technology 

and Public Policy students each year and find that they do not have an extensive 

and thorough grounding in the SciSIP approach, methods and results. Nonetheless, 

the students are quick to learn and start to use this approach in the course of their 

thesis work. However, it would be more effective to do this in a more programmatic 

fashion. 

NSF therefore has an important opportunity to work with a number of leading 

S&T policy programs around the country to develop a curriculum for education in 

the imperative, methods and results of the SciSIP agenda. This will require a distinctive training from that provided to PhD social scientists for a number of reasons. 

First, these students can be expected to have less grounding in the data-oriented 

empirical methods that are common in SciSIP research. The focus should be on understanding the empirical approach and critiquing its validity and the robustness 

of findings rather than on replicating studies. Second, it is critical to share an understanding of the research design of SciSIP projects particularly those that are 

based on careful analysis of policy changes, policy experiments and other studies 

with a thoughtful counterfactual basis. This is a methodological approach that has 

been pioneered within SciSIP (as noted above) and is a critical element in the education of S&T Policy students. A greater understanding of the SciSIP approach will 

enable higher levels of collaboration between researchers and policy makers in the 

future. In particular, it has the potential to seed a higher willingness to work collaboratively with scholars to design and analyze policy experiments with the goal 

of increasing our understanding of the impact of specific policy interventions on scientific progress 

Education of Scientists & Engineers: As has long been recognized in our analysis of scientific productivity, faculty and students engaged in leading-edge research 

in science and engineering play an important and distinctive role in shaping the 

productivity and direction of their laboratories. Indeed the organization and direction of large and increasingly complex research laboratories with collaborators that 

cross disciplines, cross universities, and often cross national boundaries is a 

daunting task. Nonetheless, we provide limited education to our science and engineering colleagues to guide them in this challenging activity. Offerings for scientists 

and engineers during undergraduate and graduate education are limited. As we develop new knowledge regarding the factors shaping research group productivity and 

the role of lab leaders in this productivity, it provides another opportunity for the 

National Science Foundation together with other leading funding agencies to work 

to provide such education. Effective education for scientists and engineers would involve three elements:
48

• Teach science and engineering undergraduates about the role of science 

and technology in society and the economy and given them a broader perspective on their technical education by highlighting the role of S&T policy. Focusing on the results of SciSIP oriented research will emphasize the importance 

of systematic, rigorous and data-driven approaches to policy, institutions and 

organizations. This will also provide them with tools to guide them in their 

subsequent careers, since they will run into the problems of the science and 

technology at every stage of their careers.

• Provide PhD students with short courses regarding the ways in which their 

research can be more productive and have a more rapid impact on society and 

the economy based on SciSIP findings. Focus on the key interventions in the 

process of knowledge production (according to the SciSIP framework)—government policies, regulations etc., university policies and practices, organizational choices. Make this relevant through a focus on the career choices they 

will have to stay within academia, move into business or focus on policy. For 

those staying at the bench (in academia or industry) examine how to maximize productivity and impact using the results of SciSIP research—organizational choices they have available, the role of incentives in research teams, 

the most effective collaborative processes they can use, etc. Highlight the key 

processes involved in shaping commercial impact including entrepreneurship 

and technology transfer and the SciSIP results on how these are most effectively deployed. Finally highlight the key role of policy in shaping some of 

their choices. A program of this type has not, to my knowledge been developed systematically for PhD students. This could be done in conjunction with 

other career-oriented activities provided by the NSF and other funding agencies to recipients of PhD grants and Fellowships.

• Educate science and engineering faculty to have a deeper understanding 

of how they can achieve greater productivity and impact, based on the systematic, evidence-based results of SciSIP research by running short courses 

at the university level (perhaps for new faculty), examining the organizational 

and institutional activities that they could undertake to increase the productivity and impact of their laboratory. This could be incorporated into existing 

efforts on grantsmanship, communications etc. Possible topics could include 

two dimensions: factors shaping productivity including lab organizational 

choices, lab size choices, and collaborative models and factors shaping impact 

including patenting, technology transfer, materials sharing, networking communication etc. Such an approach would provide a platform for sharing the 

findings of SciSIP research with academic researchers while at the same time 

having an on the ground impact on the productivity of investments in research. Finding a possible funder of such an initiative would allow for key 

educational materials to be developed. The participation of key scientific societies in this activity would also expand the set of stakeholders in the SciSIP 

agenda.

REFERENCES

Azoulay, P. G. Manso, J. Graff Zivin (2010) Incentives and Creativity: Evidence from 

the Academic Life Sciences. MIT Sloan Working Paper.

Angrist J. and J.S. Pischke (2008) Mostly Harmless Econometrics, Princeton, NJ: 

Princeton University Press.

Arrow, K. and R. Nelson (1962). Rate and Direction of inventive Activity: Economic 

and Social Factors. UMI Press.

Bertrand M., Duflo E. and Mullainathan S. (2004) ‘‘How Much Should We Trust Differences-in-Differences Estimates?’’ Quarterly Journal of Economics, 119(1) 249–

275.

Cummings, J. N., & Kiesler, S. (2005). Collaborative research across disciplinary 

and organizational boundaries. Social Studies of Science, 35(5), 703–722.

Cummings, J. N., & Kiesler, S. (2007). Coordination costs and project outcomes in 

multi-university collaborations. Research Policy, 36(10), 1620–1634.

Dahlander, Linus and Siobhan O’Mahony. Forthcoming. ‘‘Progressing to the Center: 

Coordinating Knowledge Work’’ Organization Science.

De Solla Price, D. (1970), ‘‘Citation Measures of Hard Science, Soft Science, Technology, and Nonscience’’, in C. Nelson and D. Pollock, eds. Communication 

among Scientists and Engineers, (Cambridge: Heath Lexington Books).

Ding, W. F. Murray & T. Stuart (2006). ‘‘An Empirical Study of Gender Differences 

in Patenting among Academic Life Scientists.’’ Science, Vol. 313, pp. 665–667.
49

Ding, W., S. Levine, P. Stephan & A. Winkler (2009). The Impact of Information 

Technology on Scientists’ Productivity, Quality and Collaboration Patterns. 

Berkeley Institute for Research on Labor and Employment Working Papre.

Fabrizio Ferraro and O’Mahony, Siobha ́n. Forthcoming. ‘‘Managing the Boundary of 

an Open Project,’’ in Market Emergence and Transformation, W. Powell and J. 

Padgett, Eds.

Furman, J. and S. Stern. (2010) ‘‘Climbing Atop the Shoulders of Giants: The Impact of Institutions on Cumulative Knowledge Production,’’ American Economic 

Review, forthcoming.

Furman, J. F. Murray (2009). ‘‘Governing knowledge production in the scientific 

community: Quantifying the impact of retractions’’. MIT Sloan Working Paper 

(under review).

Furman, J., F. Murray, and S. Stern. (2010) ‘‘Growing Stem Cells: The Impact of 

U.S. Policy on the Organization of Scientific Research,’’ working paper.

Garfield E. (1955) ‘‘Citation Indexes for Science,’’ Science 122: 108–11.

Griliches, Z. (1990) ‘‘Patent Statistics as Economic Indicators: A Survey,’’ Journal 

of Economic Literature, 92: 630–653.

Griliches, Z. (1998) R&D and Productivity: The Econometric Evidence, Chicago, IL: 

University of Chicago Press.

Haeussler, C., L. Jiang, J. Thursby & M. Thursby, 2009. ‘‘Specific and General Information Sharing Among Academic Scientists,’’ NBER Working Papers 15315.

Huang, K., F. Murray (2009). ‘‘Does Patent Strategy Shape the Long-Run Supply 

of Public Knowledge: Evidence from Human Genetics.’’ Academy of Management 

Journal, 52(6).

Jaffe, A. (2006) ‘‘The ‘Science of Science Policy’: Reflections on the Important Questions and the Challenges They Present,’’ Keynote Address at the NSF Workshop 

on Advancing Measures of Innovation: Knowledge Flows, Business Metrics, and 

Measurement Strategies.

Jaffe, A., M. Trajtenberg, and R. Henderson (1993) ‘‘Geographic Localization of 

Knowledge Spillovers as Evidenced by Patent Citations,’’ The Quarterly Journal 

of Economics, 577–598.

Jensen, K., F. Murray (2005). ‘‘The Intellectual Property Landscape of the Human 

Genome’’. Science, Vol. 310, 14 October 2005, pp. 239–240.

Jones, B.F., Wuchty, S., Uzzi, B., 2008. Multi-university research teams: shifting impact, geography, and stratification in science. Science 322 (5905), 1259—1262

MacCormack, A., M. J. LaMantia, Y. Cai and J. Rusnak (2008). Analyzing the Evolution of Large-Scale Software Systems using Design Structure Matrices and 

Design Rule Theory: Two Exploratory Cases, Proceedings of the 7th Working 

IEEE/1FIP Conference on Software Architecture (WICSA), Feb 2008.

MacCormack, A., J. Rusnak and C. Baldwin (2006). Exploring the Structure of Complex Software Designs: An Empirical Study of Open Source and Proprietary 

Code, Management Science, Jul 2006.

Marburger, J. (2005). ‘‘Wanted: Better benchmarks,’’ Science, 308(5725): 1087.

Meyer, B. (1995). ‘‘Natural and Quasi-Natural Experiments in Economics,’’ Journal 

of Business and Economic Statistics, 13, 151–162.

Murray (2010). ‘‘The Oncomouse that Roared: Hybrid Exchange Strategies as a 

Source of Productive Tension At The Boundary Of Overlapping Institutions’’. 

American Journal of Sociology, forthcoming.

Murray, F. and S. Stern (2007) ‘‘Do Formal Intellectual Property Rights Hinder the 

Free Flow of Scientific Knowledge? An Empirical Test of the anti-Commons Hypothesis,’’ Journal of Economic Behavior and Organization.

Murray, F., P. Aghion, M. Dewatrapont, J. Kolev and S. Stern (2010). ‘‘Of Mice and 

Academics: The Role of Openness in Science’’. NBER Working Paper.

Murray, F and S. O’Mahony (2007). ‘‘Exploring the Foundations of Cumulative Innovation: Implications for Organization Science,’’ Organization Science 18 (6): 

1006–1021.

O’Mahony, Siobha ́n and Beth Bechky. 2008. ‘‘Boundary Organizations: Enabling 

Collaboration Among Unexpected Allies,’’ Administrative Science Quarterly 53: 

(422–459).

Owen-Smith, Jason, and Walter W. Powell. 2003. ‘‘The Expanding Role of University 

Patenting in the Life Sciences: Assessing the Importance of Experience and 

Connectivity.’’ Research Policy 32(9): 1695–1711.
50

Powell, Walter W., Douglas R. White, Kenneth W. Koput, and Jason Owen-Smith. 

2004. ‘‘Network Dynamics and Field Evolution: The Growth of Inter-organizational Collaboration in the Life Sciences.’’ American Journal of Sociology. 

110(4): 1132–1205.

Walsh, J., C. Cho and W.M. Cohen, ‘‘View from the Bench: Patents, Research and 

Material Transfers,’’ Science. September 23, 2005, pp. 2002–2003.

Walsh, J, A. Arora and W. M. Cohen, ‘‘Effects of Research Tool Patents and Licensing on Biomedical Innovation,’’ in W.M. Cohen and S. Merrill, eds., Patents in 

the Knowledge-Based Economy, National Academy Press, 2003.

Williams, H. (2010). ‘‘Intellectual Property Rights and Innovation: Evidence from 

the Human Genome’’, MIT Working Paper.

Wuchty, S., Jones, B.F. & Uzzi, B., 2007. The Increasing Dominance of Teams in 

Production of Knowledge. Science, 316(5827), 1036.

BIOGRAPHY FOR FIONA MURRAY

Fiona Murray is an Associate Professor of Management in the Technological Innovation and Entrepreneurship Group at the MIT Sloan School of Management and 

Faculty Director of the MIT Entrepreneurship Center. She received BA and MA degrees in Chemistry from the University of Oxford before coming to the United 

States where she received her doctoral degree from Harvard University’s School of 

Engineering and Applied Sciences. Her research interests moved away from the 

bench to the study of science-based entrepreneurship, the organization of scientific 

research and the role of science in national competitiveness. After a lectureship at 

Oxford’s Said Business School, Fiona joined the MIT Sloan School of Management 

where she studies and teaches innovation and entrepreneurship with an emphasis 

on the life sciences, chemicals and materials sectors. Fiona is well-known for her 

work on how growing economic incentives, particularly intellectual property (IP), influence the rate and direction of scientific progress. Fiona works with a range of 

firms designing global organizations working with a wide range of internal and external innovators (through traditional contracts and ‘‘Open Innovation’’ mechanisms) 

that are both commercially successful and at the forefront of science. She is also actively involved in policy debates over the appropriate use of IP and licensing in universities and more recently debates on when and when not to use patents to promoted discovery research in neglected diseases. She is also interested in the most 

effective organizational arrangements for the rapid commercialization of science including start-ups, public-private partnerships, the role of venture philanthropy, and 

university-initiated seed funding. Her research has been widely published in a diverse range of scientific and social science journals including Science, New England 

Journal of Medicine, Nature Biotechnology, Research Policy, Organization Science 

and the Journal of Economic Behavior & Organization.

Chairman LIPINSKI. Thank you, Dr. Murray. Dr. Teich. 
51

STATEMENT OF ALBERT H. TEICH, DIRECTOR OF SCIENCE & 

POLICY PROGRAMS, AMERICAN ASSOCIATION FOR THE ADVANCEMENT OF SCIENCE 

Dr. TEICH. Thank you, Chairman Lipinski, Ranking Member 

Ehlers, other Members of the Subcommittee. Thank you for the opportunity to testify at this hearing today. I am Al Teich, and I am 

the Director of Science and Policy Programs at the American Association for the Advancement of Science. 

As you know, AAAS and I myself have been deeply involved in 

science and innovation policy for many years. Although this has 

been an active field of research at least since the 1960s, and it has 

produced a large body of literature and a substantial number of researchers, there is a feeling that the results of this work are not 

widely known or used among those who actually make science and 

innovation policy. 

This was behind the frustration of Dr. Marburger in his speech, 

which led to the establishment of the NSF SciSIP Program. The 

SciSIP Program has a unique mandate to couple advances in fundamental knowledge about processes of scientific discovery and 

technological innovation with issues of relevance to policy makers. 

Among the features that differentiate the SciSIP Program from its 

predecessors is the fact that it is not just supporting individual research grants, but it is attempting to build a community of practice 

among researchers and to connect that community with potential 

users of the research, practitioners in the Federal Government. 

AAAS has played an active role in building this community of 

practice through a workshop in 2009 that brought researchers together to learn from one another. In that workshop, we saw how 

SciSIP researchers reflect distinct disciplinary traditions that can 

inhibit productive interdisciplinary dialogue. Even in this not-verylarge field, they can’t always talk to one another. They may ask different questions, use different theoretical frameworks that employ 

different methodologies even when they may address seemingly 

similar topics. 

At the same time, because of the academic reward system, 

SciSIP researchers, like many other researchers, seldom speak in 

terms that policy makers find directly useful. And as one speaker 

said at the 2009 AAAS workshop, policymakers are confronted with 

a Babel of tongues which leads them to ignore the experts and turn 

to other sources of information and advice. Next month AAAS will 

convene another workshop with NSF support. In that one we will 

try to connect researchers with customers in the government. We 

hope that that workshop will serve to allow the two communities 

to better understand each other’s needs and expectations. 

While projects like the AAAS-NSF-SciSIP workshops are an important step in building a community of practice, there is more that 

can be done. Here are a couple of ideas just as food for thought. 

Regarding research, researchers tend to communicate directly with 

their peers by journals and conference presentations in order to 

gain recognition in their fields. But few policy makers read those 

journals or attend those conferences. We need to find ways to encourage SciSIP researchers to communicate with policy makers, either directly or through the media, and to be rewarded and not penalized by less policy-oriented peers in their fields for doing so. 
52

On the teaching side, although many of the university programs 

that provide graduate training in science and innovation policy are 

interdisciplinary, the training they provide is not always responsive 

to the needs and priorities of policy makers. It might be useful to 

strengthen ties between researchers and policy makers by engaging 

policy makers in helping to develop and review curricula as well as 

engaging them in teaching as adjuncts or guest lecturers. Some 

schools already do this. Others would do well to follow their lead. 

Beyond education, there is another mechanism for promoting 

greater mutual understanding between researchers and policy 

makers. It is people transfer. One approach might be to create a 

program to give SciSIP researchers the opportunity to work in government for perhaps a year. Providing SciSIP researchers an opportunity to work in a policy making setting for a while, as we do 

for scientists and engineers in our Congressional Fellows Program, 

would allow them to gain firsthand knowledge regarding the needs, 

priorities, and modes of operation of the potential users of their 

work. Like our workshops, this hearing is an opportunity for the 

science policy community to hear from you, as policy makers, what 

research questions you believe SciSIP researchers should be addressing. I look forward to the Q&A as an opportunity to exchange 

ideas on that subject. 

[The prepared statement of Dr. Teich follows:]

PREPARED STATEMENT OF ALBERT H. TEICH

Chairman Lipinski, Ranking Member Ehlers and members of the Subcommittee, 

thank you for the opportunity to testify today on the evolving subject of the Science 

of Science and Innovation Policy. 

The American Association for the Advancement of Science (AAAS) is the world’s 

largest multidisciplinary scientific society and publisher of the journal Science. The 

association, which celebrated its 162nd birthday earlier this week, encompasses all 

fields of science, engineering, mathematics, biomedicine and their applications. For 

more than thirty-five years, AAAS has demonstrated its commitment to and involvement in science policy issues with projects and activities such as the annual AAAS 

Science and Technology Policy Forum, the Science and Technology Policy Fellows 

Program, more recently with our Leadership Seminar in S&T Policy, and—most directly relevant to this hearing—our joint project with the National Science Foundation on the Science of Science and Innovation Policy (SciSIP). We have served the 

academic science policy community by publishing the first Guide to Graduate Education in Science, Engineering and Public Policy (known as the SEPP Guide) in 1985 

and maintaining it as an online resource to the present day.

Background 

From one perspective the Science of Science and Innovation Policy is not entirely 

a new field. Since the 1950s—and probably earlier—economists, sociologists, political scientists and others interested in public policies for science and technology 

have sought ways of measuring the value of research investments. Research articles 

on topics such as measuring Return on Investment (ROT) from research and development (R&D), national innovation systems, and comparisons of state and international standings have been published for many years. Government tools such as 

the 1993 Government Performance and Results Act (GPRA) and the more recent 

Program Assessment Rating Tool (PART) as well as their programmatic forebears, 

have attempted to quantify the value of government investment in various programs, although they have found R&D programs more difficult to assess than others. 

In the 1960s, the National Science Foundation (NSF) supported the development 

of research and graduate education programs in science and technology policy in a 

number of universities. During the 1970s, it created the R&D Assessment and R&D 

Incentives programs, which funded research on some aspects of S&T policy in universities and non-profit institutions. In addition to the SciSIP program, the Foundation currently funds research in science policy and related areas through a number 
53

1 Albert H. Teich and Irwin Feller, Toward a Community of Practice: Report on the AAAS–

NSF Grantees Workshop, March 24–25, 2009 (Washington, DC: American Association for the Advancement of Science, August 2009). Available online at http://www.aaas.org/spp/scisip/

scisip¥report.pdf. 

of programs, including the Science, Technology, and Society Program in the Directorate for Social, Behavioral, and Economic Sciences, and the Division of Science Resources Statistics, which has long provided data and analysis of importance to 

science policymaking. 

The current Science of Science and Innovation Policy endeavor is unique, however, 

in its focus on drawing this research together into a systematic, coherent body of 

knowledge that can be brought to bear directly on national policy decisions. The National Science Foundation’s SciSIP program is engaging the science policy community in research in theory, methods, models, and data development along four broad 

themes—workforce issues, innovation ecosystems, outcome measures, and data infrastructure. The program has an explicit mandate to couple advances in fundamental knowledge about processes of scientific discovery and technological innovation with issues of relevance to policymakers. As a field of research, the Science of 

Science and Innovation Policy has essentially been raised in relevance from a largely academic discourse to a field with a potential national impact. 

Science and technology policy research can have and has had a positive effect on 

national policy decisions. R&D data analyzed and reported by NSF, as well as by 

AAAS, for example, has provided a roadmap for decades for policymakers such as 

the Members of this Committee as a guide for crafting the federal R&D portfolio. 

As the NSF SciSIP program is still quite young and has been awarding grants 

for only a few years, we believe that it is premature to expect the results of that 

program’s research to be incorporated into national policy decisions. Furthermore, 

the results of any science and technology policy research—whether within or outside 

SciSIP—must still run the gauntlet of the policy process. 

In other words, simply because the research has been done, does not mean that 

it will be used. As helpful as the AAAS R&D budget analysis may be to its users, 

policymakers still make decisions based not only on research and analysis, but also 

on constituent needs, economic and political considerations, public opinion, and their 

own perspectives on national priorities. The same goes for studies that measure the 

effectiveness of federal programs. Politics is not a contaminant in the policymaking 

process. It is, after all, the essence of a democracy. 

One way that policymakers can increase the likelihood that SciSIP research be 

used to inform the design of effective federal programs and the management of federal research investments is to conceptualize and design research that both advances knowledge in a discipline and answers specific questions relevant to policy. 

Some examples of such research topics are given in the NSF SciSIP program solicitation:

• examinations of the ways in which the contexts, structures and processes of 

science and engineering research are affected by policy decisions,

• the evaluation of the tangible and intangible returns from investments in 

science and from investments in research and development,

It should be pointed out that science and technology policy research is just as unpredictable as basic research in physics, chemistry, or life sciences, and decision 

makers must take into consideration the fact that some studies may yield unanticipated results and that some may serve long-term rather than short-term needs. It 

is important to ensure that an effective SciSIP portfolio balances research that reflects short-term and long-term policy interests. 

Among the features that differentiate the SciSIP program from similar, past efforts, is its focus on building a community of practice among researchers in the 

many disciplines engaged in the study of science and innovation policy and its conscious effort to build bridges between this community and the practitioners in the 

federal government. Previous programs to support science and technology policy research have always focused primarily on providing grants to individual principalinvestigators. 

AAAS has played an active role in building this community of practice. We organized a workshop of the grantees from SciSIP’s first and second rounds (FY 2007 

and 2008) of awards to further construct this community. The outcome of that workshop was a report, titled, Toward a Community of Practice.1 Next month we will 

convene a second workshop to continue building a community of practice by connecting the researchers with potential users of their results in the federal policy 

community. 
54

There are challenges to building this SciSIP community of practice. A sizable 

group of researchers working on current projects as well as a large body of literature 

already exists. To an important degree, these individuals and this literature reflect 

distinct disciplinary traditions that can inhibit a productive interdisciplinary dialogue. These disciplinary clusters may ask different questions, draw upon different 

theoretical frameworks, and employ different methodologies and analytical models 

even when they may address seemingly similar topics (e.g., diffusion of innovation). 

Sometimes it seems they even speak different languages. 

At the same time, as these researchers speak to an audience of their peers—albeit 

within their disciplines—they often do not speak a language that policymakers understand or find useful. A concern expressed at the first AAAS SciSIP workshop was 

that policymakers would be confronted with a ‘‘Babel of tongues’’ which would lead 

them to ignore the experts and turn to other sources of information and advice. 

Another challenge is the fact that not all SciSIP researchers have experience 

working at the interface between academic research and federal policymaking. Some 

lack an understanding of the user community and who the policymakers are, what 

information or datasets they might require, or what other information they might 

need to know in order to effectively address national policy priorities. This is not 

to imply that these researchers are not familiar with the organization of government 

or the legislative process. Rather, it has more to do with the subtleties and nuances 

of the ‘‘game’’ and having an insider’s perspective on the complex policy questions 

that decision-makers face and the interplay of interests that often shapes the debate 

over science and innovation policy. 

The AAAS project is an effort to build these necessary relationships and to help 

SciSIP researchers and policymakers speak each other’s language and better understand each other’s needs and expectations. The goal is not to build a grand overarching theory of science and innovation policy, but to seek convergences among 

findings and a higher degree of understanding within the community about new 

perspectives and paradigms regarding science and innovation policy. It is to build 

a more interdisciplinary approach with an eye towards practical application by practitioners. 

This community of practice is intended to assist individual researchers or teams 

of researchers by enlarging the set of variables and/or relationships that they consider in their work. It provides an opportunity to expose research findings to a wider 

set of critical perspectives and allows researchers to consider how their findings may 

relate to other disciplines and research findings in other areas. 

As you know, the NSF initiative in the science of science and innovation policy 

stemmed from a sense that the body of science and innovation policy research does 

not seem to be very widely known or used among those who actually make policy 

in these areas. The AAAS SciSIP project is intended to facilitate interaction between 

relevant federal agency representatives and the growing community of SciSIP researchers, to help the agency representatives learn about emerging theories and 

models, and to connect research results with policy issues. At the same time, SciSIP 

researchers should be able to learn from the user community about their policy priorities and needs, which can help shape the direction of future projects. 

While the SciSIP program and projects like the AAAS–NSF SciSIP workshop are 

an important step in building a community of knowledge and a strong foundation 

between research practitioners and policymakers, there is more that can be done. 

Communication: As noted earlier, researchers addressing questions of science 

and innovation policy have tended to direct their work to colleagues, peers and others within their core discipline. This includes presentations at professional associations and conferences, and publishing in specialized journals (e.g., Research Policy, 

Social Studies of Science). This is quite understandable in view of the reward structure of academia and desire on the part of scholars in this field and others to gain 

recognition from their peers. Relatively few policymakers read such journals or attend academic conferences with any regularity. One could approach this problem in 

two ways: One approach would be to encourage policymakers to read these journals 

and/or attend more academic conferences. Given the constraints of time and energy 

they face, this seems unlikely to work. Alternatively, SciSIP researchers might seek, 

in addition to their regular publication outlets, opportunities to reach out to policymaking community either through themselves writing for those publications that 

policymakers do read or by cultivating opportunities to have their work reported in 

popular media. 

Education and Training: This ‘‘clustering’’ of a narrow core discipline has not 

only worked its way into the presentation of information, but in the education and 

training of students studying science and innovation policy that only encourages 

self-organization of a research area. Although the AAAS SciSIP program may help 
55

in encouraging the development of a more interdisciplinary curriculum, it isn’t the 

central goal of the project. 

As the committee has noted, there are about 25 U.S. universities that offer graduate education in science, engineering and public policy. There is no central organization for these programs and do not share a common curriculum or even a common 

nomenclature. The AAAS Guide to Graduate Education in Science, Engineering, and 

Public Policy mentioned earlier lists programs such as Science Policy; Technology 

Policy; Science and Technology Policy; Science, Technology, and Public Policy; and 

Engineering and Public Policy. In addition, many programs in Science and Technology Studies (STS) include a policy component, and some programs in public administration and public policy provide for a science and technology concentration. 

Furthermore, these graduate programs can be administered within different academic departments: Schools of Engineering, Public Administration, International Affairs, etc. Some programs allow for students to take coursework outside the traditional curriculum in other tangential fields (e.g., law), while other schools do not. 

Many of the graduates of these programs have gone on to very successful careers. 

Nevertheless, it might be useful to have people from the policy community—the potential users—involved in reviewing the curricula of these programs as well as engaging in teaching as adjuncts or guest lecturers. This is obviously easier for universities in the Washington, DC, area to do than for those in other regions and some 

institutions in this area do it regularly to good effect. But it is worth the effort and 

expense for all. 

Fellowships: Another potential mechanism for promoting cross-fertilization of 

ideas and greater understanding of the policymaking community’s needs, is to create 

a Fellowship program for SciSIP researchers to work in government for one year, 

similar to the AAAS Science and Engineering Policy Fellowship that allows scientists an opportunity to work at a federal agency or in a congressional office or 

committee. Intergovernmental Personnel Act appointments could also be used for 

this purpose. Providing science and policy researchers and/or graduate students an 

opportunity to work in a policy office of the federal government would allow them 

an opportunity to learn first-hand the language, needs, and priorities of an agency, 

department, or congressional committee.

Conclusion. 

I would like to thank the Members of the Subcommittee for holding this hearing 

and for their interest in the SciSIP program and the area of science and innovation 

policy research. I look forward to working with your staff as we prepare for the next 

AAAS workshop. Like our workshops, this hearing is an opportunity for the science 

policy community to hear from you, as policymakers, what research questions you 

believe SciSIP researchers should be addressing. I look forward to the Q&A as an 

opportunity to exchange ideas on that subject.

BIOGRAPHY FOR ALBERT H. TEICH

Al Teich is Director of Science & Policy Programs at AAAS, a position he has held 

since 1990. He is responsible for the Association’s activities in science and technology policy and serves as a key spokesperson on science policy issues. Science and 

Policy Programs, which includes activities in ethics, law, science and religion, and 

human rights, as well as science policy, has a staff of 40 and a annual budget exceeding $13 million. He also serves as director of the AAAS Archives. 

Teich received his bachelor’s degree in physics and his PhD in political science, 

both from M.I.T. Prior to joining the AAAS staff in 1980, he held positions at George 

Washington University, the State University of New York, and Syracuse University. 

Al is the author of numerous articles and editor of several books, including Technology and the Future, the most widely used college textbook on technology and society, the twelfth edition of which will be published in 2011 by Cengage Learning. 

He is a Fellow of AAAS and the recipient of the 2004 Award for Scientific 

Achievement in Science Policy from the Washington Academy of Sciences. He is a 

member of the editorial advisory boards to the journals, Science Communication; 

Science, Technology, and Human Values; Review of Policy Research; and Renewable 

Resources and has been a consultant to government agencies, national laboratories, 

industrial firms, and international organizations. He is past president of the Washington Academy of Sciences; former chair of the Board of Governors of the U.S.-

Israel Binational Science Foundation, where he remains a member of the executive 

committee; a member of the Technical Advisory Committee of the Maine Space 

Grant Consortium; the Norwegian Research and Technology Forum in the United 

States; the Advisory Board of the University of Virginia’s Department of Science, 
56

Technology and Society; the Program Committee for the 5th EuroScience Open 

Forum (to be held in Dublin, Ireland, in 2012) and the Council of Advisors for Research and Innovation Strategy of the National University of Singapore. 

Teich speaks frequently before audiences in the U.S., as well as Europe and Asia. 

He has appeared on National Public Radio, CNN, C–SPAN, as well as various other 

electronic media and has been quoted in numerous print media, including The New 

York Times, The Washington Post, National Journal, The Chronicle of Higher Education, and CQ Weekly Report.

Chairman LIPINSKI. Thank you Dr. Teich. I am going to start 

questions. If you want to leave to get over to vote I think we have 

about four minutes left, probably, in the first vote. But I think this 

vote is going to last a long time. But we will—if the witnesses can 

come back afterwards—it is probably going to be about an hour 

though. I am not sure if any of you have—we will have to leave 

at that point, but—yes, Dr. Ehlers, yes. You have a suggestion? 

Mr. EHLERS. No, just a quick comment which shows the importance of this topic and why we should come back if we can depending on the votes. But I would simply observe that the current process in the Congress is that science policy is set by the Appropriations Subcommittees. Money controls everything and when they decide to give a certain amount of money to a certain project, that 

basically ends up being the decision. That totally ignores the input 

of other scientists and SciSIP’s folks who have a much greater interest. So something you can think about in the meantime is how 

that could be addressed without throwing out the Appropriations 

Committee entirely which is probably impossible. So I just wanted 

to mention that, and I hope you will have some brilliant ideas on 

how we could practically address that particular problem. My staff 

just informed me that 300 people have not yet voted, so we could 

probably walk over instead of running over. But I hope the votes 

don’t run too long. And I would be delighted if any of you would 

take on the challenge too and follow this. 

Let me add one quick last comment. When Newt Gingrich was 

here he wanted to double the funding in NIH, which did happen 

in the Appropriations Committee. I argued that we should have 

equal funding increases for NSF, treat all the sciences equally. He 

said we will do that one next. Well, unfortunately we lost the majority and so the next—they were happy. But today I have heard 

Newt say in numerous speeches that one big mistake he regrets is 

not having increased NSF and the other hard sciences at the same 

time when he increased NIH. So let that be a moral note for all 

of you who hope someday to be the Speaker of the House of Representatives. Thank you very much. 

Chairman LIPINSKI. I am hoping that you can make sure you 

spread that work amongst your colleagues before you leave. 

Mr. EHLERS. Yeah. 

Chairman LIPINSKI. So you can help us—who really wants to 

make sure we get that done, get that done in the future. Well, you 

now have your homework assignment. You will have probably 

about an hour and we will be back. Hopefully sooner than that, but 

it is going to be at least 45 minutes I would say and I look forward 

to hearing your answers. I am most interested in how we really 

make these connections. Dr. Teich, I appreciate some of your comments. I would like to delve maybe some more into how we can, 

having been a—now as a political scientist, and talk about not—
57

policymakers don’t read the journals. Political scientists weren’t 

reading the journals because it didn’t really speak to them, much 

less the policymakers. But I would like to delve into that also some 

more, how we can improve that. But the Subcommittee will be in 

recess. 

[Recess.] 

Chairman LIPINSKI. I call this hearing back in. I will now start 

the questioning. I understand Dr. Sarewitz has to leave at four 

o’clock so we will—each of us will get the chance to ask some question before you have to leave. So I will now recognize myself of five 

minutes and will begin with Dr. Sarewitz. 

You mentioned in your testimony that most of the data available 

for SciSIP analysis are input/output data, level of funding, number 

of graduate students, patents, et cetera, publications. And if you—

data offer an incomplete view of societal value of S&T investments. 

So what would you suggest that we do to better characterize and 

measure the social outcomes of R&D? 

Dr. SAREWITZ. Okay. Thanks for asking that. It actually—see, 

how should I put this—it—my answer will reflect a diversity of perspectives here. I think we can all agree that the process—and Julia 

actually wrote about this wonderfully in Science Magazine—that 

the process that leads from R&D to a particular desired social outcome, for example more employment or better health, is extremely 

complex, with many different inputs into the process. But I think 

that measuring is one way to understand things but also very close 

case-based and textual analysis is another way to understand 

things. And my view is that the system is so complex that we are 

probably not going to come up with a big theory of how you can 

predict social outcomes from science and technology inputs. But we 

are going to be able to develop a number of principles that reflect 

our understanding of particular examples. 

So I think the kind of data that—and I wrote about this a little 

bit in my testimony—that we really need a kind of—data that we 

are lacking that would be very important is very granular case 

studies of both successes and failures in this full range of linkages 

from laboratories to social outcomes for a particular range of scientific priorities. And I think by doing that we will be able to elicit 

a set of general guiding principles that can help you guys distinguish between policy decisions that make sense and policy decisions that don’t make sense. I guess I am a little skeptical of the 

idea that we will ever be able to actually predict with precision. 

But I think we can be a lot smarter about the basic set of assumptions if we can develop some really close case studies from end to 

end, case studies that show great detail. 

Let me just quickly say, one, we are looking, for example, at Arizona State we are looking at the development of the solar power 

industry in Arizona, because obviously we have a lot of sun there. 

And so it is not—one of the important inputs of course is R&D into 

the solar power industry, but there are all sorts of local dynamics, 

from water availability, land use, obviously regulatory frameworks, 

all of those things are important and they are not generalizable. 

So while I think we can develop a very rich case study around 

solar in Arizona, I don’t think we should necessarily worry about 

a grand theory. So we should develop best practice case studies 
58

looking very closely at the full process of leading from the R&D activities themselves to the societal outcomes. 

Chairman LIPINSKI. Did anyone else want to—any of the witnesses want to comment on that? Have anything to add to that? 

If not I am—now I think about this in your answer, Dr. Sarewitz 

and I—do we have the data available right now? Would we need 

to do a better job of collecting data so that we can do this kind of 

research? The whole generalized ability of this is when you look at 

almost anything that is really a social process. I always go back to 

my days as a political scientist in trying to put together these theories that will predict outcomes and the struggle with doing that 

and trying to make political science into physics. How much can we 

do here when we are talking about doing the SciSIP research, and 

what we can really glean from the data that we have? 

Dr. SAREWITZ. So let me just say this. A diversity of perspectives 

is here and that is good. I mean, I think it is a rich field and it 

needs to bring lots of perspectives together, from the highly quantitative model to the more case-based qualitative work. We need all 

of that. I think we know a lot. I think Dr. Teich’s point about the 

problems of communicating what we know is really important, and 

that thinking about how to communicate more effectively the 

things that we already know, for your benefit, is an essential part 

of it. And so two things need to go on simultaneously. They are—

this field is really only just beginning to kind of get its legs. 

Dr. Murray talked about how she’s been doing it for a long time, 

didn’t know there was a field out there. I have been doing it for 

a long time as well, but more or less in small groups. So Dr. Lane’s, 

you know, efforts to create a community does two things. One is, 

it creates—it has created the intellectual momentum that we are 

going to need to move the field forward, but it also allows us to 

really collect what we know already, which I think is considerable, 

and present that, if we can figure out how to communicate effectively. I would be glad to talk about that a little bit, too, if you 

would like. 

Chairman LIPINSKI. Well, let us come back. Right now I am 

going to yield back my time. I assume my time is up and I want 

to yield now to recognize Dr. Ehlers for five minutes. 

Mr. EHLERS. Thank you very much and I don’t have any questions for you Dr. Sarewitz, other than to note that we produce 

weather today that is very close to what you have back home. We 

did put a little moisture in the air as well, so that is a little different. 

Dr. SAREWITZ. I wouldn’t be dressed like this either. 

Mr. EHLERS. That is true. But I appreciate you coming. I don’t 

have any questions for you that have not been either answered or 

explained already. But I would like to ask on the two ends of the 

panel, Dr. Lane, Dr. Teich, you both are quite familiar with the 

Congress and how it operates. Do you have any suggestions on 

what someone in the Congress could do to help educate our Members about the importance of science policy and what it should be, 

what it can do, what it cannot do, and any wisdom you could give 

us I think would be very helpful as we go forward in the Science 

Committee and try to—I hate to use the word modernize, but you 

know what I am talking about. Just try to get the workings of the 
59

House of Representatives and the Senate to reflect reality, and 

what should be done about the Science of Science Policy and in particular, what role science policy should have in guiding the Congress on the very difficult issues we have, particularly those relating to funding. So we will start with you, Dr. Lane, and go to Dr. 

Teich, and also Dr. Murray if you have any comments on that. 

Dr. LANE. Well, thank you very much for that thoughtful question. I am not as wise in the ways of Congress as you, obviously, 

so this is very much in the spirit of the suggestion rather than an 

expert approach. One of the things that I think is most important, 

that will get Congress to understand the value of science investments, is evidence. If there is clear evidence of the impact of 

science investments, on the four sets of dimensions—social, scientific, economic, and work force—that both has a qualitative aspect, that is, that there are real people affected, and there are real 

advances that are made in the quality of life, but also quantitative. 

That is, when you can unambiguously say there were—this amount 

of investment led to a whole variety of different sets of outcomes, 

and that tracer is clear. I think that is what gets people in 

Congress’s attention, because obviously they are serving the American taxpayer, and that is what the American taxpayer is interested in finding out. 

Mr. EHLERS. Okay. Dr. Teich. 

Dr. TEICH. Yeah, I think I would turn that around a bit and 

point out that it is really very much up to us in the SciSIP and 

science policy communities to communicate effectively with you in 

the Congress. You have so many messages coming at you from so 

many different directions that somehow, what we need to do is differentiate the kinds of information that we have, hopefully evidence-based. And we have to recognize that it is not the only influence, the only thing that you have to take into account in making 

decisions. 

That decision—I was struck by something Chairman Lipinski 

said about making political science into physics. I started out, I got 

an undergraduate degree in physics and my Ph.D. in political 

science, and you know physics; in some respects physics is lot easier, you know. You start, you can—my freshman physics, you know, 

assume a frictionless plane. Okay, well you can assume a 

frictionless plane and it works in some respects. Assume a 

frictionless Congress and you know you have got nothing. It doesn’t 

make any sense. So there is a—politics isn’t neat. It is not, and 

data doesn’t always trump a lot of other factors that go into decisions. We have to understand that we have to communicate within 

that framework, and then I think it is up to you in the policy community to make use of that. Best I could do on short notice. 

Mr. EHLERS. If we had a frictionless Congress, things might go 

better. Dr. Murray, do you have any wisdom to add to this? 

Dr. MURRAY. I am not sure it is wisdom. It is certainly a thought 

I have, is that—I think it is important for us to provide data that 

is meaningful. I think it is also important for us to think about 

studies that really show, again, sort of causal impact. So I think 

that there is some new work that has been funded by SciSIP and 

in other places where we can say, look, you know we did have a 

quite big shock to the system in terms of additional funding going 
60

in quite rapidly through the Recovery Act, and some of the spending in other countries that means very big shifts in research funding allocation that have happened relatively quickly. And so I think 

we have a lot of opportunities to both study those things and also 

to marshal that evidence—because I think you could always go in 

and just say, we want more for science and technology, and everybody has heard that and of course we are going to say that. And 

so I think that coming in with evidence that says—when you get 

these shifts, both in level and distribution, real things happen, real 

differences, and outcomes happen. I think if we can marshal that 

evidence in a persuasive way, then I think we can be much more 

informed and are much more likely to be listened to. 

Mr. EHLERS. Okay. Well, those are very good comments. I worry 

a little bit about the Congress requiring a lot of evidence because 

you know many experiments don’t come out that well and the Congress would say, now—next time you come around, say, well, you 

know, you sold me on this project and nothing really good came out 

of it. And that is pretty hard to overcome. 

I really appreciate the ideas you have presented and the comments you have made today. And it has given me some new insight. And I really do think that we need more concentration on 

this not only in the Congress, but among the science policy community. And what I said several times earlier on about this was—I deliberately said ‘‘Unlocking the Future’’ because I wanted someone 

in the future to write better, something better about science policy 

and something along the line of Vannevar Bush’s book which was 

probably—it could have been what we want today, but nevertheless 

he addressed a lot of issues that had to be taken into account. He 

himself was very different but very concerned about the fact that 

Congress did not pick up on a lot of his suggestions, and particularly one creating a different version of the National Science Foundation, but yet out of his work and his arguments, eventually, I 

think some ten years after he wrote the book, they did start establishing the National Science Foundation. So even though he regarded his work as a failure because the Congress didn’t pick up 

on it, eventually it did happen. 

So I encourage the science policy community to become very active, and frankly, also very aggressive in your addressing Members 

of Congress. It would not hurt at all if a few people from the 

science policy committee ran for Congress and got elected. I just 

had an experience on the Floor not 10, 15 minutes ago. Someone 

came up to me and had been present this morning at the Science 

Committee meeting and said Vern, what in the world are we going 

to do without you, because I had used my scientific knowledge in 

a number of statements. And I say well, I think, you know I don’t 

think I do that much. They will get along. But the matter of fact 

is there won’t be any scientists left on the Science Committee. And 

it is just helpful to be inside all the side discussions that are held. 

It is good to have someone there. 

So I repeat, as I have done with every speech I have given to 

every engineering or scientific group: run for Congress. We need 

more scientists in the Congress, and incidentally not just for the 

benefit of science, but most scientists are fairly clear thinkers on 
61

issues and frictionless or not, and they have a lot to contribute to 

the operation of the governing bodies of this country. 

I would actually say I probably got—had much more impact at 

the state level because I was truly a rarity there. And most state 

governments don’t have the resources to have scientists on staff. 

And I had endless amounts of work to do trying to resolve things, 

such as resolving difficulties between optometrists and ophthalmologists, or dealing with questions such as the foam installation that 

was the rage for awhile pumping into homes and now people are 

sick from formaldehyde fumes from that. These are issues no one 

in the state legislature was equipped to deal with, and I resented 

all the time I had to spend on it, but at the same time it was very 

useful to society. So spread the word, please, and thank you again 

for being here. I appreciate it very much. 

Chairman LIPINSKI. Thank you, Dr. Ehlers. 

Mr. EHLERS. Chairman, I beg your pardon but I have a bill on 

the floor that has just been called up and I have to rush down 

there to speak on it, so my apologies. 

Dr. TEICH. Mr. Ehlers, before you go I just want to say on behalf 

of AAAS, the science community and the SciSIP Community, we 

are going to miss you. Thank you for everything that you have 

done. 

Mr. EHLERS. Thank you very much. I appreciate that. 

Mr. LIPINSKI. Dr. Ehlers, we will assume I have your permission 

to continue here and wrap up. See as there was no objection from 

Dr. Ehlers I will—I was asking for your permission to continue on 

and to wrap up here. Thank you. Okay. You are still here, and 

frictionless. I will now recognize myself for five minutes. I—it is 

funny, the—talking about the assumptions and comparing physics 

to—or trying to make political science into physics. I had a colleague of mine in grad school in political science who was also, like 

myself, had a background in engineering before going to get a 

Ph.D. in political science, and he always would say that political 

science had physics envy and we were trying to be physics. Now 

it did not stop. Political scientists, and even focusing specifically on 

Congress, Congressional scholars did not—some were not afraid to 

make assumptions that wind up where they were talking about 

something that was supposed to be Congress but pretty much—

very much not Congress anymore after all the assumptions that 

were made, and make all these assumptions that said, with this, 

we were dealing with a imaginary legislature, but then we are 

going to pretend like it is Congress. Hopefully that is not the type 

of work that is going on here in SciSIP. 

I want to make sure—one thing I wanted to ask—Dr. Murray 

talked about this, and I want to ask everyone about, if they have 

any more comments on this. Because I know Dr. Murray, in your 

testimony you talked extensively about it as training, you know, 

more people to be able to do this research in having programs that 

produce the type of, you know you, go into what she is talking 

about, Ph.D. programs, but we need to, in general, produce people 

who can do this, to do this work. And I know that people who are 

doing this, researchers in this field, are located—as I mentioned in 

my opening statement—in all kinds of different places. 
62

Dr. Murray, I know you are in the business school. Are there any 

suggestions—I don’t know if there is anything else you wanted to 

add, Dr. Murray, or Dr. Teich, or if Dr. Lane would want to say 

anything about where we are right now in terms of programs that 

are producing researchers that can do SciSIP—where that is going. 

Are there programs such as this that are out there? If not, where 

are they coming from? Is this something that we need to, you really 

think we need to do more of and concentrate on, to found such a 

specific field like this, or can we get by with people coming from 

different fields. Is that the way to do it? So I just want to throw 

that question out there. As a, former political science academic I 

am interested, in you know, questions like this in terms of what 

we are doing out there in higher education. 

Dr. LANE. So I think that is a very interesting question. It is an 

important question. The main area—if you are going to train people in doing this kind of research, they are going to go into the field 

and do the kind—develop the kind of skill sets that we need. You 

want them to be able to get tenure. You want there to be able to 

be a career ladder. And the program, besides SciSIP, isn’t sufficient 

to support an interdisciplinary field in its own right. Nor is it, I 

think, possible to develop career paths for such a narrow set of 

skills. 

So I think what is important is to convince very smart people in 

economics, and sociology, and psychology and many of the other 

areas, that feel that science policy is a really important and interesting field, that they can bring their skill sets to bear on, to answer important science policy questions and that they can publish 

and get—advance within their own disciplines. So I think that is 

what is critical rather than trying to establish a separate field in 

its own right. I don’t think that is feasible given budget constraints 

and so on. So that is what we have been explicitly been trying to 

foster, to make it an intellectually challenging, exciting, and publishable type of field. 

Chairman LIPINSKI. You going to comment Dr. Murray? 

Dr. MURRAY. Yes, I think it is—I think that there are three different constituencies for education. One is the Ph.D.’s, who are 

probably the producers of research. The other—and then there are 

the science and technology policy, typically Master’s students, who 

tend to go into policy roles who I think we need to educate to be 

better consumers [of this research] and also people who really understand what we do and can help do it with us. And then finally 

there are, probably, the scientists and engineers themselves who 

could benefit from understanding some of this. We then become a 

sort of bottom-up constituency who can shape agencies and so on. 

I think on the Ph.D. side, I think Julia is exactly right. I don’t 

think you can have a new discipline of SciSIP. I think it is both 

too small, and, in fact, one of the great values of SciSIP is indeed 

the fact that people come from these other strong disciplinary foundations. I think what we do need to emphasize, though, is a serious, a sort of a field focus. 

If you think of a Ph.D. in political science or economics, mostly 

there is a field. At the moment I don’t think many places already 

have a field focus in something that we would recognize as SciSIP. 

And I think that we could go a long way towards funding things 
63

that would help establish that. You know, Ph.D. education requires, especially in something like this, you know, significant evidence, and teaching materials, and data sets, and things so that 

students can work on this, and so that we can effectively collaborate across a set of schools to really begin to develop material, 

share expertise. And then potentially bring the Ph.D. students together as a community so that they recognize one another even 

though they are always going home and we know we are educating 

them to be hired by business schools’ economics departments and 

so on. 

So I think that there is an opportunity there as long as we make 

sure we know what we’re trying to accomplish, which is not a new 

discipline. I think on the science and technology Master’s side, I am 

less familiar with that because even though I do SciSIP research 

I don’t teach in the technology and policy program at MIT. But that 

in and of itself tells you something, which is that there is, I think, 

a little bit still of a disconnect—that the traditional science and 

technology policy programs have not necessarily sort of incorporated SciSIP research into their teaching material. 

And so again I think that there is an opportunity to do something about that. Not to insist that people do it, but to provide opportunities to develop a really effective curriculum so that as people go into different—into their careers as policy makers, they understand what we are trying to do, some of the methods, they know 

good SciSIP research from less good SciSIP research and they 

themselves can say oh, you know, we are doing something in our 

agency. We could actually run that as an experiment that could be 

studied. We could try two different ways of allocating funding and 

we could really do the analysis with real data. And I think if we 

could educate people to that level, we would have a much better 

interchange in the long run, and it would be a really—it would be 

a very vibrant community. 

Chairman LIPINSKI. And Dr. Teich. 

Dr. TEICH. Yes, well, a couple of things worth noting in response. 

First of all, there are and have existed for some time about 25 programs in universities around the United States, and some outside 

the U.S. in addition to those 25. They have provided graduate education in science—in what we have called science, engineering and 

public policy, and which overlaps quite substantially with what we 

now call SciSIP. We had many years ago we published a guide, an 

old-fashioned paper type guide. We now have a website on the 

AAAS website that links to all of these programs which could help 

people find them. 

I don’t see this as a discipline either. As was said a moment ago, 

it is a—my analogy is that it is more like a field of, let us say, area 

studies in which, like Latin American studies, for example, or African studies, it is a field in which many different disciplines contribute to an understanding of what is going on in this business. 

So that is one thing that I wanted to mention. 

Another thing is that there is—there are a lot of young people 

who are very interested in this, and we need to encourage them. 

There is an organization—an international non-profit—it is incorporated as a 501(c)3 called Triple Helix, Inc., which has about 500 

students from many universities, prestigious universities around 
64

the world, which provides an opportunity for students to educate 

themselves about the relationships between science and society, in 

ethics, business, and law. They actually publish an undergraduate 

journal, which—a couple of people from AAAS’s staff serve on their 

Board of Advisors. They also have a poster session at the AAAS 

Annual Meeting. 

And then there is a group called the Science and Technology, or 

STGlobal Consortium, which is an association of graduate students 

and these programs that I mentioned, which also brings together 

people. They have a conference usually here in Washington in collaboration between the AAAS and the National Academies to provide an opportunity for younger people to explore this field, get into 

it if they’re interested, and some of them do. We at AAAS have 

hired on our staff several people who have been graduates of these 

programs—master’s degree graduates from these programs and 

some have been highly successful and are really leaders, young 

leaders in the field. 

So I am an advocate for this kind of education and I think we 

are doing it. I think it will be useful for Congress, and for Members 

of Congress if they were aware of this, to provide, I would say, 

moral support by speaking at their meetings and having staff attend and so on. So I am—I will leave it at that. 

Chairman LIPINSKI. Well, thank you, Dr. Teich, and I had a—

when we were going out for votes, I was getting in the elevator and 

someone who had been sitting in the audience, he went up and 

thanked me for having this, the hearing on SciSIP, and said, how 

do Members really become educated? How do you have the time? 

And I said, it is very, very difficult and what it really takes is a 

dedication to, you know, being educated, because the incentives, 

other than really wanting to do a good job and being interested in 

this topic, aren’t there. It is unfortunate. 

But the good thing is that we do have staff who are well educated in these things and it leaves me to thank the staff for all 

their work that you do, and all the staff on the Science Committee 

do an excellent job so that we—help us to do a better job here, 

hopefully, on the Science and Technology Committee, help the 

Members do a better job. So I thank the staff for all the work that 

they do. 

With that I want to thank the witnesses for their testimony. The 

record will remain open for two weeks for additional statements 

from the Members and for answers to any follow up questions the 

Committee may ask of the witnesses. With that the witnesses are 

excused and the hearing is now adjourned. 

[Whereupon, at 4:23 p.m. the Subcommittee was adjourned.] 
(65)

Appendix 1: 

ANSWERS TO POST-HEARING QUESTIONS
66

ANSWERS TO POST-HEARING QUESTIONS

Responses by Dr. Julia Lane, Program Director of the Science of Science and Innovation Policy Program, National Science Foundation

Questions submitted by Chairman Daniel Lipinski

Q1. You describe in your testimony an effort by NSF to improve upon the way in 

which NSF interacts with its proposal and award portfolio. Can you please 

elaborate on this effort? How might the new tools you are developing to be utilized in the development of future NSF budget proposals, new programs or other 

aspects of policy development at NSF? Also, can you please elaborate on the relevance of this effort to the broader impact criterion?

A1. The SBE and CISE directorates have established a joint subcommittee of their 

directorate advisory committees that is exploring new ways to analyze and oversee 

NSF’s portfolio of proposals and awards. The subcommittee is developing a report 

that will be available to NSF leadership and the broader community in November 

2010. A particular focus of the report will be identifying tools to help NSF program 

staff better identify and support transformative and interdisciplinary research and 

gauge the broader impacts of NSF’s investments. The report will also advise NSF 

on how to better structure existing data, improve use of existing technologies to 

complement human expertise, and characterize its programmatic data. 

These new tools and resources have many potential uses in establishing, justifying, and implementing budgetary priorities for NSF. A principal aim is to assess 

the alignment of NSF’s priorities with emerging trends and opportunities in science 

and engineering research and education and to assess NSF’s impact on areas of national priority. Other potential benefits include improving the efficiency of NSF’s 

core business processes by providing program officers with new resources for managing the merit review process. 
(67)

Appendix 2: 

ADDITIONAL MATERIAL FOR THE RECORD
68

STATEMENT OF THE CALIFORNIA HEALTHCARE INSTITUTE (CHI) SUBMITTED BY

REPRESENTATIVE BRIAN P. BILBRAY
69Æ