Suchergebnisse

Policy learning is an important part of the policy process that crosscuts multiple frameworks. However, policy learning is difficult to model and predict, and even less is known about the extent to which community characteristics affect policy learning. This article examines the contextual factors that promote and constrain policy learning in local government by identifying factors that promote learning. The central theory is that community characteristics, experience with a policy problem, and the type of subnational government will be important factors. We examine this in the context of primary data collected after Hurricane Harvey from open-ended interviews with 22 local government officials across Southeast Texas. Using a mixed methodology, we leverage the results of content analysis and Poisson regression. We find that cities with higher median incomes and larger populations are more likely to experience policy learning. Experience is not an important predictor of policy learning, suggesting possible maturation effects in the learning process. Given the long-term challenges posed by natural hazards and disasters, this puts smaller and less affluent communities at higher risk. If equitable risk and recovery is the goal of disaster policy, efforts must be made to either increase capacity or provide more resources to local governments with less capacity.

AbstractIt is well‐established that experience with a disaster can heighten risk perception, initiate policy learning, and ultimately enhance preparedness and mitigation. This experience can make stakeholders more amenable to mitigating risk, but disasters are sporadic, dangerous, and costly. At the same time, the importance of differences in epistemic communities that manage public agencies and departments has received little attention in the context of policy learning, preparedness, and mitigation. This study investigates whether it is possible for simulated disasters, such as tabletop exercises, to influence risk perception and encourage learning in a way that is consistent with the effects of experiencing an actual disaster. To test this idea, we analyze survey data collected from an Environmental Protection Agency workshop of drinking water officials and public health stakeholders from southeast Michigan and northwest Ohio, including Detroit, Flint, and Toledo. A pre and posttest survey captured participants' beliefs before and after a tabletop exercise designed to simulate a large‐scale drinking water disaster. Results suggest that epistemic communities matter in these exercises but professional experience is less important than what previous studies have shown about experience with a policy problem and policy learning.

AbstractWhereas policy change is often characterized as a gradual and incremental process, effective crisis response necessitates that organizations adapt to evolving problems in near real time. Nowhere is this dynamic more evident than in the case of COVID‐19, which forced subnational governments to constantly adjust and recalibrate public health and disease mitigation measures in the face of changing patterns of viral transmission and the emergence of new information. This study assesses (a) the extent to which subnational policies changed over the course of the pandemic; (b) whether these changes are emblematic of policy learning; and (c) the drivers of these changes, namely changing political and public health conditions. Using a novel dataset analyzing each policy's content, including its timing of enactment, substantive focus, stringency, and similar variables, results indicate the pandemic response varied significantly across states. The states examined were responsive to both changing public health and political conditions. This study identifies patterns of preemptive policy learning, which denotes learning in anticipation of an emerging hazard. In doing so, the study provides important insights into the dynamics of policy learning and change during disaster.