  This paper presents proof that Google Scholar (GS) can construct documentary
sets relevant for evaluating researchers' works. Nobelists in economics were
the researchers under analysis, and two types of tests of the GS cites to their
works were performed: distributional and semantic. Distributional tests found
that the GS cites to the laureates' works conformed to the power-law model with
an asymptote or "tail" conterminous with their h-index demarcating their core
oeuvre, validating both GS and the h-index. Semantic tests revealed that their
works highest in GS cites were on topics for which they were awarded the prize.
