RAPID: Constraints on Policy Learning After Disaster

这项研究的目的是了解为什么经历过自然灾害的社区决定降低未来发生灾难的风险。社区从灾难的经历中吸取教训，但往往吸取教训并不能带来减少风险的政策变化。此外，社区减轻未来灾害的能力各不相同。这项研究的更广泛的影响是确定在社区经历灾难后对减灾政策学习的限制。理解为什么一个社区可能比它的邻居更容易受到灾难的影响，这一点至关重要。飓风哈维为理解灾难后政策学习的限制提供了一个案例，因为它影响了德克萨斯州东南部的一系列社区。数据将通过对受飓风哈维影响的社区的当地政府官员-市长、应急管理人员和城市规划者-在几个月的时间里进行一系列半结构化采访来收集。这个项目的学术价值在于利用直接从地方政府官员那里收集的数据，了解灾难发生后的各个时期的政策学习情况。这个项目询问灾后政策学习的制约因素是什么？该项目的核心理论是，地方政府将在自然灾害发生后尝试进行政策学习，但这些努力不一定会导致政策变化，从而降低未来的风险。这一理论基于这样一种观点，即当地方政府评估减轻自然灾害的信息时，政策学习的过程可能会停滞或停止。这项研究在飓风哈维的背景下考察了灾后的政策学习，因为它影响了德克萨斯州东南部的一系列社区。它假设信息是政策学习的关键因素，学习可能受到以下因素的限制：(1)社区寻找信息的来源类型，(2)信息是否可信，(3)地方政府官员在考虑信息时是否倾向于短视。数据将通过对受飓风哈维影响的社区的当地政府官员、市长、应急管理人员和城市规划者进行为期几个月的一系列半结构化采访来收集。以前关于政策学习的研究依赖于对政府文件的事后分析来推断政策学习的存在和意义。然而，该项目将实时收集数据，从而捕获如何考虑和使用信息的决策过程。此外，它还允许参与政策学习过程的地方政府官员为自己和他们的社区说话。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The objective of this study is to understand why communities that have experienced a natural disaster decide to reduce the risk of a future disaster. Communities learn from the experience of disaster but often that learning does not lead to a policy change that reduces risks. Furthermore, communities vary in their capacity to mitigate future disasters. The broader impact of this study is to identify the limits on policy learning about disaster mitigation after a community has experienced a disaster. It is critical to understand why one community may be more vulnerable to a disaster than its neighbor. Hurricane Harvey presents a case for understanding the limits on policy learning after a disaster because of the range of communities it affected across Southeast Texas. Data will be collected using a series of semi-structured interviews over several months with local government officials - mayors, emergency managers and city planners - in communities affected by Hurricane Harvey. The intellectual merit of this project is the use of data collected directly from local government officials on policy learning after a disaster across time. This project asks what are the constraints on policy learning after disaster? The central theory of this project is that local governments will attempt to engage in policy learning after a natural disaster but those efforts will not necessarily lead to a policy change that reduces future risk. This theory is based on the idea that the process of policy learning can stall or halt when local governments are assessing information about mitigating natural hazards. This study examines policy learning after disaster in the context of Hurricane Harvey because of the range of communities it impacted across Southeast Texas. It hypothesizes that information is the critical factor for policy learning and that learning can be constrained by (1) the types of sources a community looks to for information, (2) whether the information is credible, (3) whether the local government officials tend to be myopic in how they consider the information. Data will be collected using a series of semi-structured interviews over several months with local government officials?mayors, emergency managers and city planners in communities affected by Hurricane Harvey. Previous studies of policy learning have relied on ex-post analyses of government documents to infer the presence and meaning of policy learning. However, this project will gather data in real time, thereby capturing the decision making process for how information is considered and used. Furthermore, it allows local government officials who are engaged in the process of policy learning to speak for themselves and their communities.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.