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Journal Article

Citation

Lin PSS, Chang KM. Int. J. Disaster Risk Reduct. 2020; 42: e101339.

Copyright

(Copyright © 2020, Elsevier Publishing)

DOI

10.1016/j.ijdrr.2019.101339

PMID

unavailable

Abstract

This study aimed to elucidate local knowledge that might be used to reduce disaster risks and what, if anything, changes when local knowledge is influenced by external knowledge. Qualitative data drawn from semi-structured interviews and a workshop were analyzed to study a Taiwanese indigenous tribal community. We found that disaster experiences sharpened people's abilities to detect changes in terrain, hydrology, flora, and fauna, thereby enabling them to identify disaster risks. This local knowledge could improve early warning of an impending disaster. People also used invisible local knowledge (e.g., social relations and experiences) to build their capacities to respond to disasters. We propose involuted disaster knowledge as a new type of knowledge that integrates local knowledge with scientific knowledge through an involution process. Therefore, involuted (local) disaster knowledge functions to interpret the government's perspective based on the reality known to the local people, which could help governmental disaster management succeed in meeting community-level needs. It also functions for understanding the language used by community residents, which minimizes power inequalities in the disaster governance process. We recommend recognizing local knowledge and using it in disaster management because it might help to effectively reduce the negative effects of natural disasters. Involution could help expand local knowledge's capacity for changing the environment that further benefits both local people and the government. Participatory workshops are recommended for integrating local knowledge and governmental scientific-based knowledge as well as formulating disaster risk management with community characteristics.


Language: en

Keywords

Disaster risk reduction; Evacuation shelter; Hybrid knowledge; Involution; Knowledge integration

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