Abstract:a b s t r a c tIn early fall of 2013 in the Front Range of Colorado, several communities experienced intense rainfall over a three-day period, exceeding annual average precipitation rates. Extensive damage occurred to roads, infrastructure, parks, river corridors, homes and business throughout the region. Across the U.S. and in other nations, as population increases in flood-prone areas, flood risks and vulnerability are increasing as well. Successful response to extreme events may be due to policy learning-ch… Show more
“…Rather, the evidence points towards the indirect and unintended impact of networking behavior on learning. Here, Albright and Crow (2014) find that in the context of flood risk Fig. 1 Learning types by ability to detect cues for analytical thought ARTICLE PALGRAVE COMMUNICATIONS | DOI: 10.1057/s41599-017-0052-x management (Colorado, USA) individuals gradually reaffirm and revise their causal reasoning about policies, targets, and outcomes.…”
Section: How We Learnmentioning
confidence: 89%
“…This can entails more rapid and unpredictable changes-for example, man-made disasters (Nohrstedt and Weible, 2010;Jones and Jenkins-Smith, 2009), severe weather events (Albright and Crow, 2014), or changes in public opinion (Crow and Lawlor, 2016) that heighten the visibility of policy failures and trigger ex post learning. When confronted with rapid exogenous changes, the policy entrepreneurs observed by (Birkland, 1997) framed the novel problem in a way that highlighted similarities in their understanding of the change and possible solutions.…”
This article uses the policy-oriented learning literature to provide practical insights on how to enhance the use of evidence by policymakers. After a short introduction to the field, this article presents four steps to understanding and responding to policy learning. First, all people interpret the world through the lens of their beliefs, and learn by combining heuristics and analytical processing. Second, people learn in different ways according to their roles. A novice would not be advised to learn about a specialist isue in the same way as a scientist. Instead, a modified communication strategy would be used to ensure understanding and uptake of evidence. Third, learning is a political process: we interact with our social environment and some actors-including entrepreneurs and brokers-influence the process more than others. Therefore, to encourage learning from scientific evidence we need to move beyond communication towards entrepreneurship and brokerage roles. In other words, policy-oriented learning is as much about interaction and leadership as information.
“…Rather, the evidence points towards the indirect and unintended impact of networking behavior on learning. Here, Albright and Crow (2014) find that in the context of flood risk Fig. 1 Learning types by ability to detect cues for analytical thought ARTICLE PALGRAVE COMMUNICATIONS | DOI: 10.1057/s41599-017-0052-x management (Colorado, USA) individuals gradually reaffirm and revise their causal reasoning about policies, targets, and outcomes.…”
Section: How We Learnmentioning
confidence: 89%
“…This can entails more rapid and unpredictable changes-for example, man-made disasters (Nohrstedt and Weible, 2010;Jones and Jenkins-Smith, 2009), severe weather events (Albright and Crow, 2014), or changes in public opinion (Crow and Lawlor, 2016) that heighten the visibility of policy failures and trigger ex post learning. When confronted with rapid exogenous changes, the policy entrepreneurs observed by (Birkland, 1997) framed the novel problem in a way that highlighted similarities in their understanding of the change and possible solutions.…”
This article uses the policy-oriented learning literature to provide practical insights on how to enhance the use of evidence by policymakers. After a short introduction to the field, this article presents four steps to understanding and responding to policy learning. First, all people interpret the world through the lens of their beliefs, and learn by combining heuristics and analytical processing. Second, people learn in different ways according to their roles. A novice would not be advised to learn about a specialist isue in the same way as a scientist. Instead, a modified communication strategy would be used to ensure understanding and uptake of evidence. Third, learning is a political process: we interact with our social environment and some actors-including entrepreneurs and brokers-influence the process more than others. Therefore, to encourage learning from scientific evidence we need to move beyond communication towards entrepreneurship and brokerage roles. In other words, policy-oriented learning is as much about interaction and leadership as information.
“…Limits in staff (human capacity), community budgets (fiscal capacity), and technical capacity, constrain all communities to varying degrees. These limitations may influence a community's ability to implement participatory processes, as previous findings suggest (Albright & Crow, ). Each community in the study qualified for some level of FEMA reimbursement.…”
Section: Findings: Variation In Damagesmentioning
confidence: 90%
“…Prior studies predict that individual learning from direct and indirect experiences with hazards and professional expertise may shape beliefs about causality, risks, and seriousness of the hazard. We previously analyzed the participatory processes emerging in each community in the wake of the September 2013 floods (Albright & Crow, ), which informs the broader analysis presented here. Based on the literature outlined above related to risk perception of hazards and extreme events, along with our own previous analysis, the following hypotheses are proposed for analysis in this paper: H1: Participatory processes will vary across communities based on extent and type of flood damage and resource availability.H2: Perceptions of future flood risk, problem severity, and causal understanding of the floods will vary across individuals based on expertise (technical, environmental, social) and personal past flood experiences.…”
Policy learning in the aftermath of extreme events can happen as a result of changes in beliefs, attitudes, behaviors, and perceptions of stakeholders acting in a coordinated manner. Understanding the factors that impact these beliefs may prove critical in understanding policy learning and change, since these can mean the difference between ongoing flood vulnerability as a consequence of extreme weather events rather than long‐term resilience. Data from in‐depth interviews, stakeholder surveys, public meeting documents, and community demographics were used to analyze stakeholder processes and risk perceptions in seven Colorado communities that were flooded in 2013. Differences in extent of damages and resource capacity have led to a diversity of venues and participatory processes to manage flood recovery across the case communities. The results of the stakeholder survey suggest that perceptions of problem severity are linked to past flood experiences, type of expertise and job position. Taken together, these results suggest who participates in flood recovery processes, specifically their position and field of expertise, may influence how flood risks are perceived at the community level.
“…Learning in the aftermath of a disaster can be a means to pave the way towards a ‘better’, more resilient society (Manyena et al, 2011). Both post‐disaster recovery policies (see, for example, UNISDR, 2015) and disaster scholarship (see, for example, Gaillard and Mercer, 2012; Albright and Crow, 2015) indeed stress the importance of post‐disaster learning. During post‐disaster recovery processes, affected communities acquire new experiences and develop knowledge.…”
Learning after a disaster is crucial in creating more resilient places. However, many societies are repeatedly overwhelmed by disasters. This can be because of missed opportunities to learn in post‐disaster settings or because of actions implemented that seem to be highly relevant to recovery in the short term, but potentially constrain aspirations in the longer term. This paper assesses learning processes among state and non‐state actors and the ways in which these are bridged and scaled up to wider improvements in governance. Aiming to enrich understanding of post‐disaster learning, it explores different actors’ response actions after the earthquakes in Christchurch, New Zealand, in 2010 and 2011. On the one hand, ‘learning by doing’ is occurring, yet, on the other hand, systemic learning is hindered by mismatches between top‐down steering and bottom‐up initiatives. The study concludes that better linking and synergising of learning processes among different levels is vital for enhancing resilience in post‐disaster societies.
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