Crow Deserai A, DeLeo Rob A, Albright Elizabeth A, Taylor Kristin, Birkland Tom, Zhang Manli, Koebele Elizabeth, Jeschke Nathan, Shanahan Elizabeth A, Cage Caleb
School of Public Affairs University of Colorado Denver Denver Colorado USA.
Department of Political Science Bentley University Waltham Massachusetts USA.
Rev Policy Res. 2023 Jan;40(1):10-35. doi: 10.1111/ropr.12511. Epub 2022 Oct 9.
Whereas 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 , 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.
虽然政策变化通常被描述为一个渐进的过程,但有效的危机应对要求组织几乎实时地适应不断演变的问题。这种动态在新冠疫情期间最为明显,疫情迫使地方政府面对病毒传播模式的变化和新信息的出现,不断调整和重新校准公共卫生及疾病缓解措施。本研究评估:(a)在疫情期间地方政策的变化程度;(b)这些变化是否是政策学习的体现;(c)这些变化的驱动因素,即不断变化的政治和公共卫生状况。通过使用一个新颖的数据集来分析每项政策的内容,包括其颁布时间、实质重点、严格程度及类似变量,结果表明各州的疫情应对措施差异显著。所考察的各州对不断变化的公共卫生和政治状况都做出了回应。本研究识别出了“预期性学习”模式,即针对新出现的危害进行学习。在此过程中,该研究为灾难期间政策学习和变化的动态提供了重要见解。