  The classical Gaussian concentration inequality for Lipschitz functions is
adapted to a setting where the classical assumptions (i.e. Lipschitz and
Gaussian) are not met. The theory is more direct than much of the existing
theory designed to handle related generalizations. An application is presented
to linear combinations of heavy tailed random variables.
