Policy Sciences

, 44:249 | Cite as

Scholarly science policy models and real policy, RSD for SciSIP in US Mission Agencies

  • Nathaniel Logar


Do theories that describe how science and technology policy works accurately characterize programs that aim to contribute to societal benefit? How can the research performed by federal mission agencies contribute to improved decision making? The US Department of Agriculture, the Naval Research Laboratory, and the National Institute of Standards and Technology each have goals of performing research that meets the needs of specific user groups. This analysis examines how institutional factors such as problem definitions, decision-making structures, quality-control mechanisms, distribution of participants, and social accountability guide the production of useful information. This empirical exploration of knowledge production theories fosters an evaluation of existing models of knowledge production, including the linear model, use-inspired basic research, well-ordered science, post-normal science, and Mode 2 science. The ensuing discussion of results concludes that such ideas are either too broad in their prescriptions or not accurately descriptive enough to guide formation of federal research programs that can contribute to usable science and technology products.


Science policy Knowledge production Use-inspired research Innovation Federal institutions 


  1. Abels, G., & Bora, A. (2006). Public Participation, stakeholders and expertise: Multi-actor spaces in the governance of biotechnology. Bielefeld: Policies for Research and Innovation in the Move towards the European Research Area.Google Scholar
  2. Brown, G. (1992). Guest comment: The objectivity crisis. American Journal of Physics, 60, 779–781.CrossRefGoogle Scholar
  3. Brown, M. H. (2004). The political philosophy of science policy. Minerva, 42, 77–95.CrossRefGoogle Scholar
  4. Bush, V. (1945). Science: The endless frontier. Washington, DC: U.S. Government Printing Office.Google Scholar
  5. Cash, D. W. (2001). “In order to aid in diffusing useful and practical information”: Agricultural extension and boundary organizations. Science, Technology, & Human Values, 26(4), 431–453.CrossRefGoogle Scholar
  6. Clinton, W. J., & Gore, A. (1993). Technology for America’s economic growth. Washington, DC: U.S. Government Printing Office.Google Scholar
  7. Dahl, R. A. (1990). After the revolution: Authority in a good society. New Haven: Yale University Press.Google Scholar
  8. David, P. A. (1995). Science reorganized? Post-modern visions of research and the curse of success.Google Scholar
  9. DOD. (2004). Financial management regulation, DOD 7000.14-R, Vol. 2B, Chap. 5. Washington, DC: U.S. Department of Defense.Google Scholar
  10. Foltz, F. (1999). Five arguments for increasing public participation in making science policy. Bulletin of Science Technology & Society, 19(2), 117–127.CrossRefGoogle Scholar
  11. Funtowicz, S. O., & Ravetz, J. R. (1993). Science for the post-normal age. Futures, 25, 735–755.CrossRefGoogle Scholar
  12. Gibbons, M. (1999). Science’s new social contract with society. Nature, 402, C81–C84.CrossRefGoogle Scholar
  13. Gibbons, M., Limoges, C., Nowotny, H., Schwartzman, S., Scott, P., & Trow, M. (1994). The new production of knowledge: The dynamics of science and research in contemporary societies. London: SAGE.Google Scholar
  14. Holton, G. (1993). Science and anti-science. Cambridge: Harvard University Press.Google Scholar
  15. Jeffrey, W. (2007). Personal interview with William Jeffrey, NIST Director, on 6/07/07, Gaithersburg.Google Scholar
  16. Kitcher, P. (2001). Science, truth, and democracy. New York: Oxford University Press.Google Scholar
  17. Kitcher, P. (2003). What kinds of science should be done? In A. Lightman, D. Sarewitz, & C. Dresser (Eds.), Living with the genie: Essays on technology and the quest for human mastery (pp. 201–224). Washington, DC: Island Press.Google Scholar
  18. Konisky, D. M., & Beierle, T. C. (2001). Innovations in public participation and environmental decision making: Examples from the Great Lakes Region. Society and Natural Resources, 14, 815–826.CrossRefGoogle Scholar
  19. Logar, N. (2008). Federally funded science for user benefit: Policy mechanisms for mission-oriented research, University of Colorado.Google Scholar
  20. Logar, N. (2009). Towards a culture of application: science and decision making at the National Institute of Standards & Technology. Minerva, 47, 345–366.CrossRefGoogle Scholar
  21. Logar, N., & Conant, R. (2007). Reconciling the supply and demand for carbon cycle science in the U.S. agricultural sector. Environmental Science & Policy, 10(1), 75–84.CrossRefGoogle Scholar
  22. Logar, N., & Pollack, L. K. (2005). Transgenic fish: Is a new policy framework necessary for new technology? Environmental Science & Policy, 8(1), 17–27.CrossRefGoogle Scholar
  23. National Research Council (NRC). (2005). Assessment of department of defense basic research. Washington, DC: National Research Council.Google Scholar
  24. Nowotny, H., Scott, P., & Gibbons, M. (2001). Re-thinking science: Knowledge and the public in an age of uncertainty. Malden: Blackwell.Google Scholar
  25. Nowotny, N., Scott, P., & Gibbons, M. (2003). Introduction: Mode 2’ revisited: The new production of knowledge. Minerva, 41, 179–194.CrossRefGoogle Scholar
  26. Pielke, R. A., Jr., & Byerly, R., Jr. (1998). Beyond basic and applied. Physics Today, 51, 42–46.CrossRefGoogle Scholar
  27. Renn, O., Webber, T., Rakel, H., Dienel, P., & Johnson, B. (1993). Public participation in decision making: A three-step procedure. Policy Sciences, 26(3), 189–214.CrossRefGoogle Scholar
  28. Rubin, H. J., & Rubin, I. S. (1995). Qualitative interviewing: The art of hearing data. London: SAGE Publications.Google Scholar
  29. Sarewitz, D., & Pielke, R. A., Jr. (2007). The neglected heart of science policy: Reconciling supply of and demand for science. Environmental Science & Policy, 10, 5–16.CrossRefGoogle Scholar
  30. Shapley, D., & Roy, R. (1985). Lost at the Frontier: U.S. Science and Technology Policy Adrift. ISI Press, Philadelphia.Google Scholar
  31. Shinn, T. (2003). The ‘Triple Helix’ and ‘New production of knowledge’ as socio-cognitive fields. In B. Joerges & H. Nowotny (Eds.), Social studies of science and technology: Looking back, ahead (pp. 103–116). Boston: Kluwer.CrossRefGoogle Scholar
  32. Smith, P. D., & McDonough, M. H. (2001). Beyond public participation: Fairness in natural resource decision making. Society and Natural Reources, 14, 239–249.CrossRefGoogle Scholar
  33. Stokes, D. E. (1994). Completing the Bush model: Pasteur’s quadrant. Talk given at conference “Science: The endless frontier 1945–1995”, pp. 1–13.Google Scholar
  34. Stokes, D. E. (1997). Pasteur’s quadrant: Basic science and technological innovation. Washington, DC: Brookings Institution Press.Google Scholar
  35. Weinberg, A. W. (1971). The axiology of science. American Scientist, 58, 612–617.Google Scholar
  36. Weingart, P. (1997). From “Finalization” to “Mode 2”: Old wine in new bottles? Social Science Information, 36, 591–613.CrossRefGoogle Scholar
  37. Wilsdon, J., & Willis, R. (2004). See-through science: Why public engagement needs to move upstream. London: Demos.Google Scholar

Copyright information

© Springer Science+Business Media, LLC. 2011

Authors and Affiliations

  1. 1.Consortium for Science, Policy, and OutcomesArizona State UniversityTempeUSA

Personalised recommendations