[H-DS09] Lirteracy for Disaster Risk Reduction

[HDS09-07] Multifaceted analysis focusing on the human resources in damage assessment work:
A Case Study of Himi City in the Noto Peninsula Earthquake of 2024

*Yasuhiro Komatsubara¹, Munenari Inoguchi² (1.Graduate School of Science and Engineering, University of Toyama, 2.Faculty of Sustainable Design, University of Toyama)

Keywords:2024 Noto Peninsula earthquake, damage assessment work, human resources, disaster ethnography, quantitative text analysis, SCAT

As the birthrate declines, the population ages, and the number of people declines, a shortage of disaster response personnel is recognized as a serious problem. In order to improve disaster response capability, it is argued that efforts from the viewpoints of technology, human resources, and systems are needed. This study attempts to analyze human resources in disaster response operations from multiple perspectives in order to contribute to the improvement of disaster response capability. In the Noto Peninsula Earthquake of 2024, Himi City, Toyama Prefecture, one of the disaster areas, suffered a lot of damage to residential houses due to the soft ground. The damage assessment work (damage assessment survey and issuance of damage certificates) in Himi City has attracted attention as an advanced case in which Himi City, Toyama Prefecture, which coordinated the support, and engineers with expertise in damage assessment work cooperated with each other. In this study, we conducted two semi-structured interviews with five people who played a central role in this advanced case study, in order to reflect on their responses at the time. By applying quantitative text analysis and qualitative data analysis method: SCAT (Steps for Coding and Theorization) (Figure 1), to the interview survey results, we conducted an exploratory analysis focusing on the human resources in the damage assessment work. Specifically, we extracted only the content related to human resources from the interview transcripts and applied quantitative text analysis to classify them into nine groups and analyzed the content of each group (Figure 2). In addition, 154 labels were created for each semantic grouping from the transcripts. From these, the contents related to the human resources were classified into 13 categories and 84 labels. By positioning the 13 categories as texts and applying SCAT, 4 theoretical descriptions were derived. Based on the results of these analyses, 3 points regarding the human resources in the case of Himi City were clarified.