Weather prediction models provide a workable analogy. Such models consist of continually updatable inputs, that must adapt to an enormous array of incoming data [17] . Short-term predictions, especially those associated with discrete, extreme weather events such as floods and hurricanes, have proven useful in supporting emergency management strategies, unlike events such as earthquakes or acid rain, which have longer lead times [18] . Complex mediating models which themselves have explanatory power and which embody techniques of modeling can be refined and passed down to successor models [9] . The virtue of mathematics in such a context is that it forces clarity and precision upon the conjecture, thus enabling meaningful comparison between the consequences of basic assumptions and the empirical facts [19] .