  Many widely used models amount to an elaborate means of making up
numbers--but once a number has been produced, it tends to be taken seriously
and its source (the model) is rarely examined carefully. Many widely used
models have little connection to the real-world phenomena they purport to
explain. Common steps in modeling to support policy decisions, such as putting
disparate things on the same scale, may conflict with reality. Not all costs
and benefits can be put on the same scale, not all uncertainties can be
expressed as probabilities, and not all model parameters measure what they
purport to measure. These ideas are illustrated with examples from seismology,
wind-turbine bird deaths, soccer penalty cards, gender bias in academia, and
climate policy.
