Abstract Resilience measurement continues to be a meeting ground between policy makers and academics. However, there are inherent limitations in measuring disaster resilience. For example, resilience indicators produced by FEMA and one produced by an independent academic group (BRIC) measure community resilience by defining and quantifying community resilience at a national level, but they each have a different conceptual model of the resilience concept. The FEMA approach focuses on measuring resilience capacity based on preparedness capabilities embodied in the National Preparedness Goals at state and county scales. BRIC examines community (spatially defined as county) components (or capitals) that influence resilience and provides a baseline of pre-existing resilience in places to enable periodic updates to measure resilience improvements. Using these two approaches as examples, this paper examines the differences and similarities in these two approaches in terms of the conceptual framing, data resolution, and representation and the resultant statistical and spatial differences in outcomes. Users of resilience measurement tools need to be keenly aware of the conceptual framing, input data, and geographic scale of any schema before implementation as these parameters can and do make a difference in the outcome even when they claim to be measuring the same concept.

中文翻译：

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实施灾难政策：探索抗灾能力的规模和衡量方案

摘要应变能力的测量仍然是决策者和学者之间的会面。但是，在衡量灾难恢复能力方面存在固有的局限性。例如，FEMA制定的弹性指标和独立学术团体（BRIC）制定的弹性指标通过在国家层面上定义和量化社区弹性来衡量社区弹性，但它们各自具有不同的弹性概念模型。FEMA方法着重于根据州和县级国家防灾目标中体现的防灾能力来衡量防灾能力。金砖四国检查影响抵御能力的社区（在空间上定义为县）组成部分（或首都），并提供场所中先前存在的抵御能力的基线，以便定期更新以衡量抵御能力的提高。本文以这两种方法为例，研究了这两种方法在概念框架，数据分辨率和表示形式以及结果的统计和空间差异方面的异同。弹性测量工具的用户需要在实施之前敏锐地意识到任何方案的概念框架，输入数据和地理范围，因为即使他们声称正在测量同一概念，这些参数也可以并确实在结果中有所作为。