UBC Theses and Dissertations
Dealing with uncertainty: an evaluation of three procedural theories Braul, Waldemar
Planning procedural theories articulate how planning agencies should deal with uncertainty. This thesis evaluates the appropriateness of three such theories--Rational Comprehensive (RC), Disjointed Incrementalism (DI), and Social Learning (SL)--in a context of resource region uncertainty. The thesis first proposes guidelines from Northeast British Columbia (NEBC) planning experience; the guidelines are informed by the successes, failures, and issues evident from agency responses to uncertainty and together propose that agencies should be centrally concerned with understanding the conditions--or the generic nature--of uncertainty. The thesis then uses these guidelines as standards by which- the three planning theories are evaluated. The evaluation reveals that the three theories generally ignore factors governing how agencies formulate and apply knowledge in the face of uncertainty. Future theory-building should elaborate how planning procedures can adduce the incisive understanding of uncertainty needed for policy design. 1. Export Market Uncertainty. The first condition identified in NEBC is that export market uncertainty varies by depth; that is, some events form and frequency are more readily predictable than others. Classifying depths of uncertainty enables agencies to decide whether so-called risk strategies-- which presume knowledge of probabilities--should be employed. If used' in NEBC, RC and DI styles would, befitting their namesakes, produce distinct descriptions of export market uncertainties; both, however, fail to provide the analytical knowledge needed for policy design. More meaningful information results from SL’s focus on understanding the predictability of events; this strength, however, is limited as SL does not explain how its decentralized planning structures would integrate the diverse views needed to properly classify the depths of export market uncertainties. A second condition is that uncertain events vary by location. In NEBC, some unpredictable export market forces could be stabilized by planning policies whereas others were truly ‘external’. Agencies should identify those export market forces which could be treated by policy and then estimate the costs and benefits of such assertive policy. This task can minimize costly and unpredictable boom-bust cycles. None of the three theories suggest the need for such an assessment, apparently assuming that an agency has little discretion or little to gain in dealing with export market forces. 2. Natural Systems Uncertainty. Natural systems uncertainties should also be classified by depth. As for export market uncertainty, RC and DI do not envision such a process; SL, in contrast, recognizes the need to classify depths, but it is unclear how a wide-based review required in NEBC could be achieved by a SL ‘decentralized’ planning hierarchy. Non-scientific factors determine how scientists select and apply scientific theories in the resolution of natural systems uncertainty. That economic, social, and cultural factors can distort predictability is a condition recognized in the philosophy of science, but unfortunately it attracts little attention in the three subject theories. 3. Uncertainty over Planning Agency Intentions. Many agencies participate in NEBC regional planning, raising the spectre of costly policy contradictions and duplications. Agencies, however, face financial and intelligence limitations, and therefore need to explicitly consider the need for and costs and benefits of consultation. All three theories hail the need to consult but naively assume that analysts will somehow define an appropriate level of consultation. 4. Public Value Uncertainty. In NEBC, social and economic factors dictate that agencies will obtain a necessarily limited view of public values. Planning agencies need to carefully assess the potentially high costs and benefits of public participation (or non-participation). All theories stress the need to survey public values, but SL’s mutual learning would best clarify policy alternatives attuned to local values. Mutual learning, however, is not a panacea, as it overlooks political reluctance to use it and ignores how non-participating societal groups should be engaged in the process.
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