Foundations of Science

, Volume 20, Issue 3, pp 213–231 | Cite as

Structures of Logic in Policy and Theory: Identifying Sub-systemic Bricks for Investigating, Building, and Understanding Conceptual Systems

Article

Abstract

A rapidly growing body of scholarship shows that we can gain new insights into theories and policies by understanding and increasing their systemic structure. This paper will present an overview of this expanding field and discuss how concepts of structure are being applied in a variety of contexts to support collaboration, decision making, learning, prediction, and results. Next, it will delve into the underlying structures of logic that may be found within those theories and policies. Here, we will go beyond Toulmin’s logics of claim and proof that have not proven useful for advancing the social sciences and focus on five structures of “causal logic.” The results suggest a useful and more comprehensive approach to developing deeper understanding of our conceptual systems such as theory and policy.

Keywords

Conceptual system Theory theory building Metatheory Policy  Metapolicy Causal logic Structures of logic 

References

  1. Appelbaum, R. P. (1988). Karl Marx (Vol. 7, Masters of Social Theory). Thousand Oaks, CA: Sage.Google Scholar
  2. Axelrod, R. (1976). Structure of decision: The cognitive maps of political elites. Princeton: Princeton Universtiy Press.Google Scholar
  3. Bateson, G. (1979). Mind in nature: A necessary unity. New York: Dutton.Google Scholar
  4. BonJour, L., & and Sosa, E. (2003). Epistemic justification: Internalism vs. externalism, foundations vs. virtues (Great Debates in Philosophy). Malden, MA: Blackwell.Google Scholar
  5. Bozeman, B., & Landsbergen, D. (1989). Truth and credibility in sincere policy analysis: Alternative approaches for the production of policy-relevant knowledge. Evaluation Review, 13(4), 355–379.CrossRefGoogle Scholar
  6. Carolan, M. S. (2006). Science, expertise, and the democratization of the decision making process. Society and Natural Resources, 19, 661–668.CrossRefGoogle Scholar
  7. Casti, J. L. (1995). Complexification: Explaining a paradoxical world through the science of surprise. New York: Harper Perennial.Google Scholar
  8. Curseu, P., Schalk, R., & Schruijer, S. (2010). The use of cognitive mapping in eliciting and evaluating group cognitions. Journal of Applied Social Psychology, 40(5), 1258–1291.CrossRefGoogle Scholar
  9. Dubin, R. (1978). Theory building (Revised ed.). New York: The Free Press.Google Scholar
  10. Gleick, J. (1987). Chaos: Making a new science. New York: Penguin Books.Google Scholar
  11. Goodier, C. I., Austin, S. A., Soetanto, R., & Dainty, A. R. J. (2010). Causal mapping and scenario building with multiple organisations. Futures, 42(3), 219–229.CrossRefGoogle Scholar
  12. Greenhalgh, T., Robert, G., Macfarlane, F., Bate, P., Kyriakidou, O., & Peacock, R. (2005). Storylines of research in diffusion of innovation: A meta-narrative approach to systematic review. Social Science and Medicine, 61, 417–430.Google Scholar
  13. Kaplan, A. (1964). The conduct of inquiry: Methodology for behavioral science (Chandler Publications in Anthropology and Sociology). San Francisco: Chandler Publishing Company.Google Scholar
  14. Kelley, K. T., & Mayo-Wilson, C. (2012). Causal conclusions that flip repeatedly and their justification. http://arxiv.org/ftp/arxiv/papers/1203/1203.3488.pdf. Accessed August 25, 2013.
  15. Kelly, KT. (2007). Simplicity, truth, and the unending game of science. In S. Bold, B. Löwe, T. Räsch, & J. v. Benthem (Eds.), Foundations of the formal sciences V: Infinite games (pp. 368, Studies in Logic: Volume 11). London: College Publications.Google Scholar
  16. Kingdon, J. W. (1997). Agendas, alternatives, and public policies (2nd ed.). Upper Saddle River, NJ: Pearson Education.Google Scholar
  17. Lewis, M. W., & Grimes, A. J. (1999). Metatriangulation: Building theory from multiple paradigms. Academy of Management Review, 24(4), 627–690.CrossRefGoogle Scholar
  18. March, J. G., & Simon, H. A. (1993). Organizations (2nd ed.). Hoboken, NJ: Wiley.Google Scholar
  19. Mathieson, G. (2004). Full spectrum analysis: Practical OR in the face of the human variable. Emergence: Complexity and Organization, 6(4), 51–57.Google Scholar
  20. McLaughlin, J. A., & Jordan, G. B. (1999). Logic models: A tool for telling your program’s performance story. Evaluation and Program Planning, 22(1), 65–72.CrossRefGoogle Scholar
  21. Meehl, P. E. (2002). Cliometric metatheory II: Criteria scientists use in theory appraisal and why its is rational to do so. Psychological Reports, 91(2), 339.CrossRefGoogle Scholar
  22. Nechval, N. A., Nechval, K. N., Purgailis, M., & Rozevskis, U. (2010). Selection of the best subset of variables in regression and time series models. In S. E. Wallis (Ed.), Cybernetics and systems Theory in management (pp. 303–320). Hershey, PA: IGI Global.CrossRefGoogle Scholar
  23. Quine, W. V. O. (1969). Ontological relativity and other essays. New York: Columbia University Press.Google Scholar
  24. Raphael, T. D. (1982). Integrative complexity theory and forecasting international crises: Berlin 1946–1962. The Journal of Conflict Resolution, 26(3), 423–450.CrossRefGoogle Scholar
  25. Roe, E. (1998). Taking complexity seriously: Policy analysis, triangulation and sustainable development. New York: Kluwer.CrossRefGoogle Scholar
  26. Rogers, P. J. (2008). Using programme theory to evaluate complicated and complex aspects of interventions. Evaluation, 14(1), 29.CrossRefGoogle Scholar
  27. Rothwell, W. J., Sullivan, R., & McLean, G. N. (Eds.). (1995). Practicing organization development: A guide for consultants. San Diego, CA: Pfeiffer.Google Scholar
  28. Sabatier, P. A. (Ed.). (1999). Theories of the policy process (Vol. 1, Theoretical Lenses on Public Policy). Boulder, CO: Westview Press.Google Scholar
  29. Salmon, W. C. (1984). Scientific explanation and the causal structure of the world. New Jersey: Princeton University Press.Google Scholar
  30. Saunders, C. S., Carte, T. A., Jasperson, J., & Butler, B. S. (2003). Lessons learned from the trenches of metatriangulation research. Communications of AIS, 11, 245–269.Google Scholar
  31. Schiele, H., & Krummaker, S. (2010). Consortial benchmarking: Applying an innovative industry-academic collaborative case study approach in systemic management research. In S. E. Wallis (Ed.), Cybernetics and systems theory in management: Tools, views, and advancements (pp. 93–107). Hershey, PA: IGI Global.CrossRefGoogle Scholar
  32. Schmidt, R. E., Scanlon, J. W., & Bell, J. B. (1979). Evaluability assessment: Making public programs work better (Vol. 14, Human Services Monograph Series). Washington, D.C.: Department of Health, Education, and Welfare-Project Share.Google Scholar
  33. Seligman, J., Liu, F., & van Benthem, J. (2011). Models of reasoning in ancient China. Studies in Logic, 4(3), 57–81.Google Scholar
  34. Senge, P. (1990). The fifth discipline: The art and practice of the learning organization. New York: Currency Doubleday.Google Scholar
  35. Senge, P., Kleiner, K., Roberts, S., Ross, R. B., & Smith, B. J. (1994). The fifth discipline fieldbook: Strategies and tools for building a learning organization. New York: Currency Doubleday.Google Scholar
  36. Sloman, S. A., & Hagmayer, Y. (2006). The causal psycho-logic of choice [Opinion]. Trends in Cognitive Science, 10(9), 407–412.CrossRefGoogle Scholar
  37. Speech. (1984). Just say no: Words to the nation. Public address by President Ronald Regan and Nancy Regan Google Scholar
  38. Stacey, R. D. (1992). Managing the unknowable: Strategic boundaries between order and chaos. San Francisco: Jossey-Bass.Google Scholar
  39. Stinchcombe, A. L. (1987). Constructing social theories. Chicago: University of Chicago Press.Google Scholar
  40. Suedfeld, P., & Rank, A. D. (1976). Revolutionary leaders: Long-term success as a function of changes in conceptual complexity. Journal of Personality and Social Psychology, 34(2), 169–178.CrossRefGoogle Scholar
  41. Suedfeld, P., Tetlock, P. E., & Streufert, S. (1992). Conceptual/integrative complexity. In C. P. Smith (Ed.), Handbook of thematic content analysis (pp. 393–400). New York: Cambridge University Press.Google Scholar
  42. Toulmin, S. E. (2003/1958). The uses of argument. New york: Cambridge University Press.Google Scholar
  43. UN. (1945). Charter of the United Nations and statute of the international court of justice. New York: United Nations.Google Scholar
  44. van Benthem, J. (2012). The logic of empircal theories revisited. Synthese, 186(3), 775–792. doi:10.1007/s11229-011-9916-6.CrossRefGoogle Scholar
  45. Van de Ven, A. H. (2007). Engaged scholarship: A guide for organizational and social research. New York: Oxford University Press.Google Scholar
  46. Wallis, S. E. (2008). Validation of theory: Exploring and reframing Popper’s worlds. Integral Review, 4(2), 71–91.Google Scholar
  47. Wallis, S. E. (2009a). Seeking the robust core of organisational learning theory. International Journal of Collaborative Enterprise, 1(2), 180–193.CrossRefGoogle Scholar
  48. Wallis, S. E. (2009b). Seeking the robust core of social entrepreneurship theory. In J. A. Goldstein, J. K. Hazy, & J. Silberstang (Eds.), Social entrepreneurship & complexity. Litchfield Park, AZ: ISCE Publishing.Google Scholar
  49. Wallis, S. E. (2010a). The structure of theory and the structure of scientific revolutions: What constitutes an advance in theory? In S. E. Wallis (Ed.), Cybernetics and systems theory in management: Views, tools, and advancements (pp. 151–174). Hershey, PA: IGI Global.CrossRefGoogle Scholar
  50. Wallis, S. E. (2010b). Towards developing effective ethics for effective behavior. Social Responsibility Journal, 6(4), 536–550.CrossRefGoogle Scholar
  51. Wallis, S. E. (2010c). Towards the development of more robust policy models. Integral Review, 6(1), 153–160.Google Scholar
  52. Wallis, S. E. (2011). Avoiding policy failure: A workable approach. Litchfield Park, AZ: Emergent Publications.Google Scholar
  53. Wallis, S. E. (2012a). Existing and emerging methods for integrating theories within and between disciplines. In 56th Annual meeting of the international society for systems sciences (ISSS), San Jose, CA, July 15–22, 2012, pp. 23.Google Scholar
  54. Wallis, S. E. (2012b). Theories of psychology: Evolving towards greater effectiveness or wandering, lost in the jungle, without a guide? In 30th International congress of psychology: Psychology serving humanity, Cape Town, South Africa, July 22–27, 2012.Google Scholar
  55. Wallis, S. E. (2013a). How to choose between policy proposals: A simple tool based on systems thinking and complexity theory. ECO-Emergence: Complexity & Organization, 15(3), 94–120.Google Scholar
  56. Wallis, S. E. (2013b). Propositional analysis for evaluating explanations through their conceptual structures. Paper presented at the International Society for Complexity and Emergence (ISCE) “Modes of Explanation” Paris, France, May 22–24, 2013.Google Scholar
  57. Wallis, S. E. (2014). A systems approach to understanding theory: Finding the core, identifying opportunities for improvement, and integrating fragmented fields. Systems Research and Behavioral Science, 31(1), 23–31.CrossRefGoogle Scholar
  58. Wallis, S. E. (under submission). Are theories of conflict improving? Using propositional analysis to determine the structure of conflict theories over the course of a century. Availible on request.Google Scholar
  59. Wheatley, M. J. (1992). Leadership and the new science. San Francisco: Barrett-Koehler.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Foundation for the Advancement of Social TheoryPetalumaUSA
  2. 2.Capella UniversityMinneapolisUSA

Personalised recommendations