  A complex process is often a balance between non-stationary and stationary
components. We show how the non-extensive Tsallis q-entropy indicator may be
interpreted as a measure of non-stationarity in time series. This is done by
applying the non-extensive entropy formalism to the Diffusion Entropy Analysis
(DEA). We apply the analysis to the study of the teen birth phenomenon. We find
that the unmarried teen births are strongly influenced by social processes with
memory. This memory is related to the strength of the non-stationary component
of the signal and is more intense than that in the married teen time series. By
using the wavelet multiresolution analysis we attempt to give a social
interpretation of this effect.
