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Translating community narratives into semi-quantitative models to understand the dynamics of socio-environmental crises

Abstract: 
Acute socio-environmental crises often expose systemic problems that are linked by failures in man- agement, environmental, or social systems. If recovery efforts are to address these systemic problems, these issues and the concerns of those impacted by the crisis need to be clearly articulated, rationally represented, and communicated to those responsible for the recovery. Although participatory ap- proaches to crisis recovery often use environmental modeling, explicit ways in which stakeholders’ narratives and experiences can be translated into computer-based models for scenario analysis are not readily available to modelers or decision-makers. We present an approach to translating community narratives about crisis events using a free Fuzzy Cognitive Mapping software called Mental Modeler (www.mentalmodeler.org). We applied this process to the recent water crisis in Flint, Michigan, and demonstrate how participatory modeling can give communities a way to structure their thoughts, develop recovery actions, and communicate with those in charge of crisis recovery efforts.
Author: 
Alison Singer, Steven Gray, Artina Sadler, Laura Schmitt Olabisi, Kyle Metta, Renee Wallace, Maria Claudia Lopez, Josh Introne, Maddie Gorman, Jane Henderson
Institution: 
Michigan State University, United States
Year: 
2017
Input By: 
Christina Eilar
Affiliation: 
MIT
Country: 
United States
Datatype(s): 
Case Studies
Models