  We introduce and analyse a simple probabilistic model of article production
and citation behavior that explicitly assumes that there is no decline in
citability of a given article over time. It makes predictions about the number
and age of items appearing in the reference list of an article. The latter
topics have been studied before, but only in the context of data, and to our
knowledge no models have been presented. We then perform large-scale analyses
of reference list length for a variety of academic disciplines. The results
show that our simple model cannot be rejected, and indeed fits the aggregated
data on reference lists rather well. Over the last few decades, the
relationship between total publications and mean reference list length is
linear to a high level of accuracy. Although our model is clearly an
oversimplification, it will likely prove useful for further modeling of the
scholarly literature. Finally, we connect our work to the large literature on
"aging" or "obsolescence" of scholarly publications, and argue that the
importance of that area of research is no longer clear, while much of the
existing literature is confused and confusing.
