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System Perspectives of Experts and Farmers Regarding the Role of Livelihood Assets in Risk Perception: Results from the Structured Mental Model Approach

System Perspectives of Experts and Farmers Regarding the Role of Livelihood Assets in Risk... Pesticide application is increasing and despite extensive educational programs farmers continue to take high health and environmental risks when applying pesticides. The structured mental model approach (SMMA) is a new method for risk perception analysis. It embeds farmers' risk perception into their livelihood system in the elaboration of a mental model (MM). Results from its first application are presented here. The study region is Vereda la Hoya (Colombia), an area characterized by subsistence farming, high use of pesticides, and a high incidence of health problems. Our hypothesis was that subsistence farmers were constrained by economic, environmental, and sociocultural factors, which consequently should influence their mental models. Thirteen experts and 10 farmers were interviewed and their MMs of the extended pesticide system elicited. The interviews were open‐ended with the questions structured in three parts: (i) definition and ranking of types of capital with respect to their importance for the sustainability of farmers' livelihood; (ii) understanding the system and its dynamics; and (iii) importance of the agents in the farmers' agent network. Following this structure, each part of the interview was analyzed qualitatively and statistically. Our analyses showed that the mental models of farmers and experts differed significantly from each other. By applying the SMMA, we were also able to identify reasons for the divergence of experts' and farmers' MMs. Of major importance are the following factors: (i) culture and tradition; (ii) trust in the source of information; and (iii) feedback on knowledge. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Risk Analysis Wiley

System Perspectives of Experts and Farmers Regarding the Role of Livelihood Assets in Risk Perception: Results from the Structured Mental Model Approach

Schoell, Regina; Binder, Claudia R.
Risk Analysis , Volume 29 (2) – Feb 1, 2009
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References (59)

Publisher
Wiley
Copyright
© 2008 Society for Risk Analysis
ISSN
0272-4332
eISSN
1539-6924
DOI
10.1111/j.1539-6924.2008.01153.x
pmid
19000068
Publisher site
See Article on Publisher Site

Abstract

Pesticide application is increasing and despite extensive educational programs farmers continue to take high health and environmental risks when applying pesticides. The structured mental model approach (SMMA) is a new method for risk perception analysis. It embeds farmers' risk perception into their livelihood system in the elaboration of a mental model (MM). Results from its first application are presented here. The study region is Vereda la Hoya (Colombia), an area characterized by subsistence farming, high use of pesticides, and a high incidence of health problems. Our hypothesis was that subsistence farmers were constrained by economic, environmental, and sociocultural factors, which consequently should influence their mental models. Thirteen experts and 10 farmers were interviewed and their MMs of the extended pesticide system elicited. The interviews were open‐ended with the questions structured in three parts: (i) definition and ranking of types of capital with respect to their importance for the sustainability of farmers' livelihood; (ii) understanding the system and its dynamics; and (iii) importance of the agents in the farmers' agent network. Following this structure, each part of the interview was analyzed qualitatively and statistically. Our analyses showed that the mental models of farmers and experts differed significantly from each other. By applying the SMMA, we were also able to identify reasons for the divergence of experts' and farmers' MMs. Of major importance are the following factors: (i) culture and tradition; (ii) trust in the source of information; and (iii) feedback on knowledge.

Journal

Risk Analysis – Wiley

Published: Feb 1, 2009

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