  Continuous injection models of spectral ageing have long been used to
determine the age of radio galaxies from their integrated spectrum; however,
many questions about their reliability remain unanswered. With various large
area surveys imminent (e.g. LOFAR, MeerKAT, MWA) and planning for the next
generation of radio interferometer well underway (e.g. ngVLA, SKA),
investigations of radio galaxy physics are set to shift away from studies of
individual sources to the population as a whole. Determining if and how
integrated models of spectral ageing can be applied in the era of big data is
therefore crucial. In this paper, I compare classical integrated models of
spectral ageing to recent well resolved studies that use modern analysis
techniques on small spatial scales to determine their robustness and validity
as a source selection method. I find that integrated models are unable to
recover key parameters and, even when known a priori, provide a poor, frequency
dependent description of a source's spectrum. I show a disparity of up to a
factor of 6 in age between the integrated and resolved methods but suggest,
even with these inconsistencies, such models still provide a potential method
of candidate selection in the search for remnant radio galaxies and in
providing a cleaner selection of high redshift radio galaxies in $z - {\alpha}$
selected samples.
