Reduction of disaster vulnerability through Indigenous knowledge
AbstractLinking indegenious knowledge of the community with modern techniques to mesure, analyse and reduce disaster vulnerability is one way of engaging and moblising community capacity. This paper discuses he use of the local/ indegenious knowledge into disater management. It suggest a way to moblise available human and technical resources in order to strengthen a good partnership between local communities and local and national institutions. The study conducted through field work in two districts “Thatta and Badin” of coastal area of Sindh Province of Pakistan. Multistage cluster sampling technique has used to select the sample size of 360 households from the area. Data was collected through well structured questioner. With the increasing socio-economic changes in this global village, local knowledge is wear away unremittingly and having no severe to sightsee. New peers are accepting new ways of life and grownup groups reminisce very less. Proper utilization of local wisdom, knowledge along with modern tools and techniques can give rid from disaster worst situation and can reduce risk. To measure local knowledge and wisdom of the community statistically new model has developed through primary data, Model for local knowledge. In the model Local Knowledge is dependent variable whereas, age, experience, living status and prediction about disasters are independent variable. The impact of these independent variables on dependent variable has measured through multiple regressions and in the end suggestions and recommendations put forward in the light of local vulnerability to have minimum loss in upcoming disasters.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 39532.
Date of creation: 18 Apr 2012
Date of revision: 16 Jun 2012
Cyclone; Flood; Disaster; Disaster Management; Local Knowledge; Vulnerability; Hazards; Taluka; Climate Change; Reconstruction; Awareness;
Find related papers by JEL classification:
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