Assessment and management of policy conflict in the illinois river watershed in oklahoma: An application of q methodology[1]

International Journal of Public Administration

Volumn 25, Issue 11, 2002, Pages 1311-1349

  Focht, Will ^a  

^a OKLAHOMA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84937375960     PISSN: 01900692     EISSN: 15324265     Source Type: Journal    
DOI: 10.1081/PAD-120013349     Document Type: Article

References (49)

1. This research was funded by the US Environmental Protection Agency′s National Center for Environmental Research and Quality Assurance, EPA Grant Number R825791, for a project entitled, “Ecological Risks, Stakeholder Values, and River Watersheds: Testing Management Alternatives for the Illinois River.” An earlier version of this paper was presented at the annual meeting of the International Society for the Scientific Study of Subjectivity, Tulsa, Oklahoma, October 5–8, 2000. The author wishes to acknowledge the contributions of John Wood, who administered the Q sorting exercises to IRW stakeholders, and Professor Steven Brown, who kindly provided useful references to publications that helped inform this study
2. Dr. Focht is Assistant Professor of Political Science, Oklahoma State University, 519 Mathematical Sciences, Stillwater, Oklahoma, USA (E-mail: wfocht@okstate.edu)
3. Bality, A., Caneday, L., Fite, E., III, Wikle, T., and Yuan, M., 1998. “ IRW Management Plan 1999 ”. 1–94. Tahlequah, Oklahoma: Oklahoma Scenic Rivers Commission.
4. Stephenson, W., 1935. Technique of Factor Analysis. Nature, 136 (3434): 297
5. Stephenson, W., 1953. The Study of Behavior: Q Technique and Its Methodology 376Chicago: University of Chicago Press.
6. Stephenson, W., 1969. Foundations of Communication Theory. The Psychological Record, 19 (1): 65–82.
7. Stephenson, W., 1967. The Play Theory of Mass Communication 225Chicago: University of Chicago Press.
8. Stephenson, W., 1978. Concourse Theory of Communication. Communication, 3 (1): 21–40.
9. Stephenson, W., 1973. Applications of Communication Theory: III–Intelligence and Multivalued Choice. The Psychological Record, 23 (1): 17–32.
10. Young, Z., 1957. Doubt and Certainty in Science 168New York: Oxford University Press.
11. Techniques that examine correlations among traits across people are referred to as R methodologies, after Pearson′s “r” correlation coefficient. Q methodology, which examines correlations among people, was given this name by Sir Godfrey Thomson in 1935 to differentiate it from trait correlations
12. Stephenson, W., 1935. Correlating Persons Instead of Tests. Character and Personality, 4: 17–24.
13. Stephenson, W., 1961. Scientific Creed–1961: Abductory Principles. The Psychological Record, 11 (1): 9–17. From Charles Pierce, abductive inference is the discovery of the unexpected, but not unsuspected, by purposive exploration. It involves the pursuit of potential causes (plausibilities) from effects
14. Stephenson, W., 1971. “ Factors as Operant Subjectivity ”. In Multivariate Analysis Edited by: Lunneborg, C., Seattle: University of Washington Press.
15. Vickers, G., 1968. The Art of Judgment 242London: Methuen.
16. Focht, W., and Lawler, J.J., 2001. “ NIMBY and TIMBY: Analysis of Stakeholder Perspectives on Hazardous Waste Controversies in Oklahoma Environmental Policy ”. In Oklahoma: Issues, Innovations, Insights Edited by: Focht, W., Oklahoma City: Oklahoma Political Science Association. (special issue of Oklahoma Politics 10: 63–79)
17. Pelletier, D., Kraak, V., McCullum, C., Uusitalo, U., and Rich, R., 1999. The Shaping of Collective Values through Deliberative Democracy: An Empirical Study from New York's North Country. Policy Sciences, 32 (2): 103–131.
18. Webler, T., Tuler, S., and Krueger, R., 2000. What Is a Good Public Participation Process? Five Perspectives from the Public. Environmental Management, 27 (3): 435–450.
19. Ascher, W., 1987. Subjectivity and the Policy Sciences. Operant Subjectivity, 10 (1/2): 73–80.
20. Barkley, M.V., 1975. Adaptation of the Q-Sort Technique as an Evaluation Device. Illinois Teacher of Home Economics, 18 (4): 206–207.
21. Brown, S.R., 1974. The Compositions of Microcosms. Policy Sciences, 5 (1): 15–27.
22. Cooper, D.R., and Dantico, M.K., 1990. Priority Setting Techniques for the Budgetary Process: An Experimental Comparison to Determine What Works. Experimental Study of Politics, 9 (1): 94–117.
23. Gerrard, J., and Hausman, W., 1985. The Priority Sort: An Empirical Approach to Program Planning and Evaluation. American Journal of Social Psychiatry, 5 (5): 29–36.
24. Webler, T., and Tuler, S., 2001. Public Participation in Watershed Management Planning: Views on Process from People in the Field. Human Ecology Review, in press
25. Steelman, T.A., and Maguire, L.A., 1999. Understanding Participant Perspectives: Q-Methodology in National Forest Management. Journal of Policy Analysis and Management, 18 (3): 361–388.
26. Maxwell, J., and Brown, S.R., 2000. Identifying Problems and Generating Solutions under Conditions of Conflict. Operant Subjectivity, 23 (1): 31–51.
27. Gargan, J.J., and Brown, S.R., 1993. ‘What Is to Be Done?” Anticipating the Future and Mobilizing Prudence. Policy Sciences, 26 (4): 347–359.
28. van Eeten, M., 2000. “ Recasting Environmental Controversies: A Q Study of the Expansion of Amsterdam Airport ”. In Social Discourse and Environmental Policy Edited by: Addams, H., and Proops, J., 41–70. Northampton, Massachusetts: Edward Elgar Publishing, Inc.
29. Focht, W., and Lawler, J.J., 2000. “ Using Q Methodology to Facilitate Policy Dialogue ”. In Social Discourse and Environmental Policy Edited by: Addams, H., and Proops, J., 100–122. Northampton, Massachusetts: Edward Elgar Publishing, Inc.
30. Denzin, N.K., 1971. The Logic of Naturalistic Inquiry. Social Forces, 50 (2): 166–182.
31. Brunswick, E., 1949. Systematic and Representative Design of Psychological Experiments 157Berkeley and Los Angeles: University of California Press. A Q sample is representative if it comprehensively represents the full depth, breadth, and context of the parent concourse
32. The open-ended interview method was selected for concourse development because it minimizes researcher-introduced bias and preserves the integrity and hermeneutic nature of the concourse
33. Burt, C.L., 1940. The Factors of the Mind 509London: London University Press.
34. Brown, S.R., 1993. A Primer on Q Methodology. Operant Subjectivity, 16 (3/4): 91–138.
35. Brown, S.R., 1980. Political Subjectivity: Applications of Q-Methodology in Political Science 355Westford, Massachusetts: Murray Printing Company. (288–289)
36. Stephenson, W., 1980. Factor Analysis. Operant Subjectivity, 3 (2): 38–57.
37. van Tubergen, G.N., 1980. “ QUANAL, Q Factor Analysis Computer Software Program ”. Lexington, Kentucky: University of Kentucky. A Microsoft Windows(r)-compatible Q factor analysis program known as PQMethod, along with a user′s manual, can be down-loaded at no cost from http://www.unibw-muenchen.de/∼p41bsmk/qmethod/downpqx.htm. Commonly available statistical packages such as SAS and SPSS do not currently contain Q factor analysis algorithms
38. Stephenson, W., 1980. Factor Analysis. Operant Subjectivity, 3 (2): 38–57.
39. Principal components extraction and a theoretical rotation by varimax were used to provide a preliminary examination of stakeholder perspectives. A more careful examination is being conducted using centroid extraction and judgmental rotation to abductively explore stakeholder subjectivities and will be reported later
40. The initial extraction of seven factors has long been the default of Q methodologists. Stephenson pointed out in his 1973 article (see endnote 9) that information theory has shown that human capacity to process information is limited, leading G.A. Miller in 1967 to conclude that the most information that can be processed in complex multivalued situations is seven, plus or minus two
41. These are heuristic criteria only. Though they help guide the selection of how many factors would be retained, they are not mandatory. They are usually are traded off
42. The formulation of a conflict mitigation strategy will be discussed at the end of the paper following a discussion of results from the Q analysis of impact management preferences
43. In fact, the extreme difficulty in gaining even a temporary consensus on an OSRC impact management plan for the IRW that represents little more than a series of narrative goals without specifications of means to achieve them, even after five years of study and deliberation, confirms that negotiating effective regulatory programs to implement goals will be very difficult
44. Stern, P.C., and Fineberg, H.V., eds. 1996. Understanding Risk: Informing Decisions in a Democratic Society 249Washington, DC: National Academy Press. Committee on Risk Characterization, Commission on Behavioral and Social Sciences and Education, National Research Council
45. Again, no bipolar perspectives were found; therefore, Local Controllers and Skeptics are not hostile to science and decision rationality and Rational Managers and Precautionaries are not hostile to respect for autonomy and consent. In this case, analysis and deliberation are not in opposition and can be integrated into one coherent process
46. Though policy deliberation will need to be augmented with expert technical analysis and consultation, we suspect that in the end factual uncertainty and disagreement will be less a cause for disagreement than will value conflicts. For example, if the agriculturalists who manifested the Traditionalist and Skeptical perspectives find that scientific studies demonstrate that water quality degradation is primarily due to phosphorus-contaminated runoff from their operations and that they will be the focus of impact management regulations, we expect that they will still be inclined to oppose regulation unless their economic and social values are protected. The same can be said about outfitters if scientific studies demonstrate that floaters are a major source of water quality degradation. In other words, analysis can never be a substitute for deliberation when salient values are in conflict
47. This author is coauthoring a manuscript to appear in a book on stakeholder participation in watershed management that presents a normative theoretical argument that procedural legitimacy requires respect for autonomy (and its concomitant: informed and voluntary consent), justice, and welfare. The bases for this argument will be defended there
48. We do not mean to overstate the ability of policy deliberations to yield “good” policy. According to Pelletier et al. (see endnote 17), the practical reason that governs policy deliberations must be supplemented by expert knowledge to ensure that the policy is adequately informed and liberal rationalism to ensure that the process is fair and competent
49. Nagel, S.S., 1988. Multi-Criteria Dispute Resolution and Decision-Aiding 234Washington, DC: National Institute for Dispute Resolution.