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A Statement of Principles

We need good science in the US. Good science helps us understand the universe and use this knowledge to push the boundaries of what is possible to achieve. Since the government spends many billions of dollars to support science, we need that funding system to work well.  

What would a good science funding system look like?

  • Good science funding would be open-minded and willing to consider new evidence and theories, even if a new direction goes against the current consensus. Indeed, many discoveries that are now considered breakthroughs were widely unpopular at the time. 
  • Good science funding would focus centrally on improving the production of scientific knowledge. Other goals (such as regional economic development) would be recognized as distinct and of lesser importance.
  • Good science funding would work very hard to avoid social desirability bias. What is effective may be quite distinct from what we would like to be effective.
  • Good science funding would incentivize scientists to care deeply about being right. The replicability crisis can be viewed as a paucity of such incentives in many domains. Similarly, good science funding would incentivize scientists to share findings and data freely and quickly. This allows other scientists to challenge and/or build on each other’s results, greatly accelerating progress. 
  • Good science funding would recognize a spectrum, from science that is highly goal-oriented (such as clinical trials), to science that is open to serendipity and exploration without any practical goal. 
    • Fundamental research, driven simply by an urge to understand the natural world, can be misconstrued as useless. But scientific breakthroughs can often be traced back to one or more exploratory findings whose importance could never have been foreseen at the time.
  • Good science funding would provide stable funding for infrastructure like tools, technologies, and software, as well as compensation and career advancement for staff scientists and statisticians. 
  • Good science funders would be responsive to new developments and would consistently rethink their structure and practices, rather than being tied to decades-old ideas and assumptions. 
  • Good science funding would impose minimal administrative burdens, so as to give scientists sufficient time to focus on their work.

While there are many current programs at NIH and NSF that support good science, our funding system could do more.

  • Federally-sponsored surveys have found that 42-45% of time that scientists spend on federally-funded research is taken up by administration, which includes progress reports, compliance, revenue and budgeting, and much more. Worse, that figure does not include writing proposals, serving on study sections or institutional compliance committees, or the administrative tasks performed by people other than principal investigators. 
    • While any requirement may seem sensible standing alone, the cumulative impact is so excessive that virtually everyone agrees that we should cut back so as to enable scientists to spend more time on what they do best: science. 
  • Scientific publications rarely share enough data or information about methods that anyone could reuse the work and build upon it. Federal funders could incentivize such practices. 
  • We need more career paths and funding opportunities for people who produce tools, technology, or software, or who work as staff scientists or statistical consultants. 
  • Funding could be more streamlined and responsive to new discoveries, new theories/ideas, and new developments (such as a worldwide pandemic).
  • Many scientists report that the best way to get NIH funding is to promise guaranteed success on a topic that is currently popular, sometimes by completing much of the work beforehand and then just extending it a little further. It is too difficult to get NIH funding for a new idea that isn’t a guaranteed success, never mind wide-ranging exploration of basic science questions that might pay off only after decades in ways that can’t be predicted.
  • The funding at NIH is skewed towards older people (even those eligible for retirement), while the proportion of grants going to younger people in their prime has fallen over ten-fold since 1980. Virtually everyone agrees that funding should be more evenly distributed so as to reward good ideas and encourage innovation. 
  • Even though the experimental method is central to medicine, biology, and many other disciplines, large funding agencies rarely test out different funding models and rigorously evaluate them. Instead, they standardize science funding mechanisms and hence reduce the structural diversity of the ecosystem. 

The US science funding system needs to rethink how it works. Funders should continually innovate in funding models, should avoid the homogenizing effects of implementing any single dominant methodology, and should experiment with different ways of enabling good science — science that is innovative, rigorous, and more supportive of exploration and new ideas.

Please email to be added as a signatory.

Signatories (alphabetical by last name)

Bruce Alberts
Chancellor’s Leadership Chair in Biochemistry and Biophysics for Science and Education, UCSF; former editor-in-chief of Science and president of the National Academy of Sciences

Pierre Azoulay
International Programs Professor of Management, MIT

Donald A. Berry
Professor, Department of Biostatistics, University of Texas MD Anderson Cancer Center

Philip E. Bourne
Dean of the School of Data Science, University of Virginia
Former Associate Director for Data Science, NIH (2014-2017)

Stuart Buck
Executive Director, Good Science Project
Senior Advisor, Social Science Research Council
Former Vice President of Research, Arnold Ventures (2012-2021)

Robert Cook-Deegan
Professor, Arizona State University

Daniel Correa
CEO, Federation of American Scientists
Formerly Assistant Director for Innovation Policy, White House Office of Science and Technology Policy

Tyler Cowen
Holbert L. Harris Chair of Economics and Chairman of Mercatus Center
George Mason University

Leigh A. Frame
Director, Integrative Medicine, George Washington School of Medicine & Health Sciences

Jeremy Freese
Professor of Sociology, Stanford University

Frank Harrell
Professor of Biostatistics, Vanderbilt University

Anna Harvey
President, Social Science Research Council
Professor of Politics, and Director of Public Safety Lab, New York University

Richard Henson
MRC Programme Leader and Deputy Director, MRC Cognition and Brain Sciences Unit
Professor of Cognitive Neuroscience, University of Cambridge

Tom Kalil
Chief Innovation Officer, Schmidt Futures
Former Deputy Director, Office of Science and Technology Policy

Marc Kirschner
John Franklin Enders Harvard University Professor, and Professor of Systems Biology
Harvard Medical School

Harlan Krumholz
Harold H. Hines, Jr. Professor of Medicine and Professor in the Institute for Social and Policy Studies
Director, Center for Outcomes Research and Evaluation, Yale University

Rebecca A. Maynard
University Trustee Chair Professor Emeritus, University of Pennsylvania

James D. Miller
Professor of Economics, Smith College

Jennifer Miller
Assistant Professor, Yale School of Medicine
Director, Good Pharma Scorecard Initiative

Edward Miguel
Oxfam Professor of Environmental and Resource Economics; Faculty Director of the Center for Effective Global Action; University of California, Berkeley

Richard Nakamura, Ph.D., retired
Former Director of Center for Scientific Review, NIH
Former Scientific Director, NIMH
Former Deputy Director, NIMH

Rachael Neve
Co-director, Gene Delivery Technology Core, Massachusetts General Hospital

Brian Nosek
Executive Director, Center for Open Science
Professor, Department of Psychology, University of Virginia

Russ Poldrack
Professor of Psychology and Associate Director of Stanford Data Science
Stanford University

Joseph Ross
Professor of Medicine and Public Health, Yale University

Peter Suber
Senior Advisor on Open Access, Harvard Library, Harvard University

Dr. Michael P. Taylor
Research Associate, Department of Earth Sciences, University of Bristol

Joachim Vandekerckhove
Professor, Department of Cognitive Sciences, University of California, Irvine