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Abstract:
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"Environmental problems usually involve emerging and uncertain information that must be successfully assimilated ('learned') by decision-making communities to have a consequent impact on policy. Despite the importance of successful learning, it tends to be very difficult to alter the beliefs of stakeholders involved in technically complex and ideologically divisive policy arenas. One theory of the policy process, called the Advocacy Coalition Framework (ACF), offers a potential explanation that focuses on the interactions between beliefs, bias, and the emergence of social networks. In particular, the ACF hypothesizes that cognitive biases tend to polarize policy-relevant belief systems. The result is that policy network structures tend to coalesce and self-reinforce around shared ideologies, exacerbating political conflict and making the efficient use of scientific information difficult. Collaborative institutions are hypothesized to attenuate this effect, by providing a forum for meaningful deliberation across competing ideologies and interests. Empirical data used in testing these hypotheses are collected, via online survey, from policy elites in five regional land use and transportation planning processes in California (N = 752). Hypotheses are tested using a variety of network analytic techniques to identify signatures of network growth processes as a result of biased learning. The results lend some support for the ACF view of policy learning, but also suggest that the role of bias is highly context dependent. Future work in the area should pay close attention to the differential role that various types of beliefs play in learning and the formation of policy networks."
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