Paper short abstract:

We studied resilience work of Dutch health system actors, whilst staying sensitive to the ‘dark sides’ of resilience. In our analysis we zoom in on the interplay of three crucial types of resilience work by actors; representing, layering, and accounting.

Paper long abstract:

Resilience as concept is gaining traction in discussions about crises and disasters in healthcare. There is a plethora of frameworks that propose the characteristics or building blocks of resilient health systems. Yet, we know little about how resilience is actually practised in healthcare. Hence, we studied how Dutch health system actors practised resilience, whilst staying sensitive to its ‘dark sides’. We thereby break away from resilience as descriptive and apolitical notion, as this ignores the vulnerabilities it induces. We conducted an ethnographic study with 20 interviews throughout the Dutch health system, an analysis of international literature and policy documents, and a secondary data analysis of a previous project on resilience during the pandemic.

We zoom in on the interplay of three types of resilience work. First, actors work to represent the needs of their wider communities. They strategically and dynamically position themselves as spokesperson for themes such as acute care or public health, whilst safeguarding the interests of particular groups. Representation also works as a means of communicating across different governance layers. Second, we observed constant efforts directed at layered governing, which includes redrawing institutional boundaries. Another important topic was the sharp ‘acute’ edge of a crisis versus its longue durée. Finally, actors work to account for deviations from common practice, or more generally to justify choices made under pressure. We note how accountability structures tend to be based on how we expect crisis to evolve, rather than being able to move along with what happens in practice.

Paper short abstract:

This study outlines the opportunities and risks of GIS integrated with AI and ML to improve disaster preparedness. Identifying opportunities and risks benefits disaster management professionals to understand and influence policy design for climate change action and disaster management.

Paper long abstract:

Climate change is leading to more frequent and severe disasters, highlighting the inadequacy of the current disaster response capabilities of government agencies and emergency teams across the globe. Although geographic information systems (GIS) have been useful for disaster preparedness modeling and emergency response planning, the emergence and integration of artificial intelligence (AI) and machine learning (ML) algorithms can be leveraged to improve disaster management and preparedness. This study utilized a systematic review methodology to outline the opportunities and risks of GIS integrated with AI And ML to improve disaster preparedness. First, integrating GIS with AI and ML creates new opportunities to improve predictive capabilities that can be leveraged to explore weather patterns and historical records, enabling more accurate predictions of extreme events and disasters. The predictability of AI-powered GIS enables government agencies and emergency teams to issue early warnings, plan evacuations, and mobilize resources, potentially saving lives and reducing the impact of such events. Second, risks associated with AI and ML result from issues related to data quality, bias, and over-reliance on existing data to perform predictive analysis. If data is biased or incomplete, models can generate inaccurate or unfair predictions, worsening existing disaster preparedness and response inequalities. Identifying opportunities and risks benefits disaster management professionals to understand and influence policy design for climate change action and disaster management.

Paper short abstract:

This presentation explores the recovery from the flood events in Takeo City, Saga Prefecture, within the Kyushu region of Japan in 2019 and 2021, and aims to clarify the dynamics of disaster and the practice of caring, highlighting the roles not just of humans but also of non-human entities.

Paper long abstract:

This presentation leverages Annemarie Mol's theory on the logic of choice and care, applying these frameworks to the studies of disaster recovery through a case study. It centers on a civilian disaster volunteer center, "O," launched in 2019 in Takeo City, Saga Prefecture, Kyushu region of Japan. The region faced severe flooding incidents in 2019 and 2021 amidst the COVID-19 pandemic, and the recovery re-launched after the 2021 flood.

Drawing from fieldwork and participant observation, I will underscore the criticality of fostering community autonomy and honoring personal value judgments in the face of disaster vulnerability. This approach necessitates a comprehensive understanding of the affected individuals' living conditions, necessities, and available human and technical resources, highlighting autonomy's significance. In fact, the community faced numerous challenges and adaptive trials, and this process has refined and evolved systems without presupposing optimal outcomes.

This presentation argues for the necessity of sustained, collaborative efforts among diverse stakeholders—including families, professionals, volunteers, governmental entities, fellow disaster survivors, and the integrated network of technological and infrastructural supports—to ensure enduring care in disaster management. It proposes a framework that shifts from establishing a resilient society each time in the face of sporadic and intermittent disasters to caring for one capable of sustainable recovery. Also, the presentation draws upon Mol's logic of care to advocate for a model of shared responsibility that intertwines with material elements to enhance the resilience of those affected and improve the overall quality of life during the recovery phases.

Paper short abstract:

The paper mobilizes the panel’s core theme of disaster risk governance to detail the role of knowledge practices in Ghana’s disaster risk reduction strategy, paying particular attention to the knowledge contribution of local communities in central level planning and prediction.

Paper long abstract:

In October 2023, emergency spillage of Ghana’s historically iconic Akosombo hydroelectric dam resulted in the displacement of over 35,000 people in the country’s politically contentious Volta Region. Positioned in the region’s history of political marginalization (Nugent 1995, 2002), the paper offers an analysis of the politics of intervention in the face of intersecting vulnerabilities resulting from effects of climate change, infrastructural limitations, and unresolved political and economic crises. The paper mobilizes the panel’s core theme of disaster risk governance to detail the role of knowledge practices – ranging from remote sensing data and hydrological models to the observation of sentinel species and oral historical records – in Ghana’s disaster risk reduction strategy, paying particular attention to the knowledge contribution of local communities and the interactions of multiple orders of validity in central level planning and prediction.

Paper short abstract:

Flood maps are the authoritative source of flood risk information in the United States. How public officials read them reflects the sometimes-conflicting imperatives of bureaucracy and politics. Because what they deem to be the risk object shapes the social construction of disaster protection.

Paper long abstract:

This paper argues Flood Insurance Rate Maps are the backbone and bane of the U.S. government’s trillion-dollar National Flood Insurance Program (NFIP). While flood maps are crucial to the Federal Emergency Management Agency’s (FEMA) administration of the NFIP, updating the nation’s 22,000 flood maps is an impossible task. Ample research on the social consequences of risk mapping demonstrates that flood maps are highly contentious and often outdated, inaccurate, and unreliable. However, scholarship analyzing how flood risk mapping processes unfold in practice is scarce. To address this gap, I chart the risk mapping process in New Orleans. Drawing on rich ethnographic, interview, and documentary data, I investigate the case of New Orleans’ new flood map. As this new map went into effect in September 2016, controversy erupted. Champions of the new map suggested the below-sea-level city was safe from flooding. Critics charged it was an outline for disaster. The contention masked FEMA’s decade long process to redraw the city’s urban floodplain. At the outset, FEMA’s modernization drive promised to streamline the mapping process and improve accuracy. By the end, the local government had thrice questioned the accuracy of the new flood map. How local officials, federal bureaucrats, and elected representatives read flood maps reflects the sometimes-conflicting imperatives of bureaucracy and politics. Because what these actors deem to be the risk object intimately shapes the social construction of disaster protection.

Paper short abstract:

After the 3.11, it was the first time that computer simulation was used to help government officers decide on hazard areas and support their decision on the height of the seawall. However, as discussions progressed, the government abandoned simulation method in order to maintain their early decision

Paper long abstract:

After the 3.11 disaster, unlike the traditional "reconstruction on high land," Miyagi Prefecture in Japan's Tohoku area implemented reconstruction in the flooded area by defining hazard areas and constructing huge seawall to ensure the city's future safety. This has raised the issue of how to quantify and visualize "future tsunami risk," leading to the creation of new tools and expertise tasked with revealing the possible risk of future tsunamis. Consequently, computer simulation has emerged as an expert scientific tool from the viewpoint of policymakers, with its hazard maps becoming the scientific basis for selecting hazard areas and setting seawall height standards. However, as urban reconstruction and seawall construction progressed, the reliability of computer simulations as scientific evidence was continually questioned until it was declared abandoned in 2020. This article describes how computer simulation built a temporary "navigation platform" within Japan's three-tier government and how this "platform" collapsed by analyzing post-disaster meeting materials from Japan's three-tier government (country, prefecture, city) and interviews with experts from Tohoku University. This study provides insights into the role of expertise in predicting and managing natural risks, revealing the temporality and fragility of this role within Japan's unique political structure.