The Impacts of Narratives-based Risk Communication on Hazard Preparedness

基于叙述的风险沟通对灾害准备的影响

• 批准号: 1635885
• 负责人: Elizabeth Shanahan
• 金额: $ 55万
• 依托单位: Montana State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-15 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1635885&HistoricalAwards=false
• 关键词: Impacts; Narratives; based; Risk; Communication

Local hazard preparedness is vital to avoid disaster in the face of extreme events. Whereas conventional risk communication relies on scientific information to affect hazard preparedness, such technical information is often ineffectively assimilated into people's risk perceptions and decisions. Hazard preparedness is largely shaped by factors such as cultural values, cognitive biases, affect, knowledge, information, and experiences, all of which are communicated through stories that people construct and recount to one another. This research will test the effects of an innovative narrative-based risk communication strategy that locates science hazard information in locally produced hazard narratives. Effectively connecting scientific information to individual risk perceptions and decisions through co-produced risk narratives potentially offers an innovative way to improve hazard preparedness that could translate across hazard issues more broadly. With the project focus on flooding events, this research will draw upon expertise in social behavioral sciences, hydrology, and computer science. This interdisciplinary research effort focuses on testing whether a co-produced, narrative-based risk communication approach is more effective than conventional risk communication at improving hazard preparedness (defined as risk perception and decisions). The first objective is to develop co-produced risk narratives that are both scientifically accurate and locally relevant. Using a community-based participatory research (CBPR) approach, baseline data of flood risk narratives will be collected from river communities to ascertain narrative elements as identified in the Narrative Policy Framework (NPF). Narrative elements include subsets of narrative structure (e.g., use of characters, plot) and narrative content (who is cast in the roles of hero, villain, victim). Whereas narrative structures are stable, content varies across narratives. The characters cast in the narrative and their associated actions are formative in constructing different notions of reality and consequent decisions. Natural Language Processing computational techniques will then be used to identify key narrative content from the CBPR data to obtain the best set of combinations of narrative structure and narrative content situated in local language and images. Subsequently, researchers will quantify, explain, and depict sources of hydrologic uncertainty (data, model, and natural uncertainty) associated with flood frequency analysis in 100-year flood maps for each community. This resulting information will be embedded into the algorithmically enhanced CBPR-based risk narratives to create locally relevant and scientifically accurate flood risk narratives. These risk narratives will be returned to the CBPR groups for adjustment and validation. The second objective focuses on testing the effects of these co-produced risk narratives as narrative treatments on hazard preparedness (i.e., risk perception and intended decisions) with an experimental survey design across the larger population in these river communities. Differently constructed co-produced narratives (i.e., hero-focused, victim-focused, hero & victim focused narratives) will be used as treatments to test the extent to which they influence hazard preparedness in contrast to a non-narrative science statement and a control condition of no treatment. The findings are expected to provide insight into the power of narratives in communicating hazard risk and affecting hazard preparedness. The outcomes are expected to be useful for those local and federal entities involved in hazard preparedness strategies.

面对极端事件，当地的灾害准备对于避免灾难至关重要。传统的风险通报依靠科学信息来影响备灾工作，而这种技术信息往往不能有效地融入人们的风险认识和决定。备灾在很大程度上受到文化价值观、认知偏见、情感、知识、信息和经验等因素的影响，所有这些因素都通过人们构建和讲述的故事来传达。本研究将测试一个创新的叙事为基础的风险沟通策略，定位在当地生产的危险叙述科学危害信息的影响。通过共同制作的风险叙述，将科学信息与个人风险认知和决定有效地联系起来，有可能提供一种改进备灾的创新方法，这种方法可以更广泛地适用于各种灾害问题。该项目的重点是洪水事件，这项研究将借鉴社会行为科学，水文学和计算机科学的专业知识。 这种跨学科的研究工作的重点是测试是否共同制作的，叙事为基础的风险沟通方法是更有效的比传统的风险沟通，在提高灾害准备（定义为风险认知和决策）。第一个目标是共同编制科学上准确和当地相关的风险说明。采用基于社区的参与性研究（CBPR）方法，将从河流社区收集洪水风险叙述的基线数据，以确定叙述政策框架（NPF）中确定的叙述要素。叙事元素包括叙事结构的子集（例如，人物、情节的使用）和叙事内容（谁扮演英雄、恶棍、受害者的角色）。虽然叙事结构是稳定的，但不同叙事的内容不同。叙事中的人物及其相关行动在构建不同的现实概念和随之而来的决定中起着决定性作用。然后，自然语言处理计算技术将用于从CBPR数据中识别关键叙事内容，以获得叙事结构和叙事内容的最佳组合集，这些叙事结构和叙事内容位于当地语言和图像中。随后，研究人员将量化，解释和描述与每个社区百年洪水图中洪水频率分析相关的水文不确定性（数据，模型和自然不确定性）的来源。由此产生的信息将嵌入到算法增强的基于CBPR的风险叙述中，以创建本地相关和科学准确的洪水风险叙述。这些风险叙述将返回CBPR组进行调整和验证。第二个目标侧重于测试这些共同产生的风险叙述作为灾害准备的叙述处理的效果（即，风险认知和预期的决定），在这些河流社区的更大人口的实验性调查设计。共同制作的叙事（即，以英雄为中心、以受害者为中心、以英雄受害者为中心的叙述）将被用作治疗，以测试它们与非叙述性科学陈述和不治疗的对照条件相比对危险准备的影响程度。研究结果预计将提供洞察力的叙述在沟通危险风险和影响灾害准备的力量。预计这些结果将对参与灾害防备战略的地方和联邦实体有用。

项目成果

Characters matter: How narratives shape affective responses to risk communication

人物很重要：叙事如何塑造对风险沟通的情感反应

• DOI: 10.1371/journal.pone.0225968
• 发表时间: 2019
• 期刊: PLOS ONE
• 影响因子: 3.7
• 作者: Shanahan, Elizabeth A.;Reinhold, Ann Marie;Raile, Eric D.;Poole, Geoffrey C.;Ready, Richard C.;Izurieta, Clemente;McEvoy, Jamie;Bergmann, Nicolas T.;King, Henry;Breithaupt, Fritz
• 通讯作者: Breithaupt, Fritz

Thinking Through Levees: How Political Agency Extends Beyond the Human Mind

• DOI: 10.1080/24694452.2019.1655387
• 发表时间: 2019-10-14
• 期刊: ANNALS OF THE AMERICAN ASSOCIATION OF GEOGRAPHERS
• 影响因子: 3.9
• 作者: Bergmann, Nicolas T.;McEyoy, Jamie;Izurieta, Clemente
• 通讯作者: Izurieta, Clemente