  For words, rank-frequency distributions have long been heralded for adherence
to a potentially-universal phenomenon known as Zipf's law. The hypothetical
form of this empirical phenomenon was refined by Ben\^{i}ot Mandelbrot to that
which is presently referred to as the Zipf-Mandelbrot law. Parallel to this,
Herbet Simon proposed a selection model potentially explaining Zipf's law.
However, a significant dispute between Simon and Mandelbrot, notable empirical
exceptions, and the lack of a strong empirical connection between Simon's model
and the Zipf-Mandelbrot law have left the questions of universality and
mechanistic generation open. We offer a resolution to these issues by
exhibiting how the dark matter of word segmentation, i.e., space, punctuation,
etc., connect the Zipf-Mandelbrot law to Simon's mechanistic process. This
explains Mandelbrot's refinement as no more than a fudge factor, accommodating
the effects of the exclusion of the rank-frequency dark matter. Thus,
integrating these non-word objects resolves a more-generalized rank-frequency
law. Since this relies upon the integration of space, etc., we find support for
the hypothesis that $all$ are generated by common processes, indicating from a
physical perspective that space is a word, too.
