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This report delves into the calibration of complex system dynamics models, highlighting the paradox that the simplest model may not always be truly simple. It explores the motivations behind model development, emphasizing the importance of understanding explanatory needs, key controls, desired outputs, and relevant inputs. The report discusses what practitioners should learn, the effects that need demonstration, and common measurement techniques. By addressing these factors, the report provides valuable insights for practitioners aiming to enhance model calibration and functionality.
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