Science to inform and models to engage
Scientific evidence and evidence-based reasoning are likely to face epistemological challenges when brought into societal debate if their foundational assumptions generate cognitive dissonance among key elements of the community. The risk of dissonance is even greater when scientific demonstrations and models are concerned with the decisions and behaviours of people interacting with an environment of interest. In this case, scientific information is often perceived as distorted or biased due to the inherent uncertainties attached to human ecosystems Human ecosystems are complex and adaptive, largely due to our individual cognitive capacities and communication skills. Complex systems science aims to track uncertainties attached to these systems by exploring metaphoric models of reality.
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