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Science and Problem Solving in a Political World: Insights from Katrina

Joshua Farley, Brian Miles

Abstract


While as scientists ecological economists pursue objectivity and empiricism, as problem solvers we strive to move our policy solutions to pressing problems onto the political agenda. To what extent is a rigorous scientific understanding of sustainability issues necessary and sufficient for creating more sustainable policies? If it is not, what are the obligations of scientists who understand the threats to sustainability to act on their understanding? We use a case study of Katrina to show that impartial science alone is inadequate to achieve our ends. Ecological economics and market fundamentalism have fundamentally different definitions of the problems leading to and resulting from Katrina, which in turn lead to diametrically opposed policy solutions. The solutions of the market fundamentalists are those currently receiving the most consideration, which exacerbates the problems as defined by ecological economists. As scientists and problem solvers, ecological economists must empirically study the public policy process to learn how to promote our policy solutions. We therefore assess two schools of thought concerning public policy—the market model and polis model. The market model of the public policy process assumes that policy makers rationally analyze the options available to achieve a specific goal then choose the one that maximizes utility. The polis model in contrast assumes that policy makers are not consistently rational but respond instead to the strategic presentation of situations using stories and symbols more than value-neutral facts. We argue that the polis model is a more accurate empirical interpretation of the policy process, and therefore, to be good scientific problem solvers, ecological economists must rely on emotionally charged stories that explain the significance of their scientific research instead of impartial presentation of empirical evidence.

Keywords


Public policy; polis model; hurricane Katrina; scale; distribution

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