  In the study of random structures we often face a trade-off between realism
and tractability, the latter typically enabled by assuming some form of
independence. In this work we initiate an effort to bridge this gap by
developing tools that allow us to work with independence without assuming it.
Let $\mathcal{G}_{n}$ be the set of all graphs on $n$ vertices and let $S$ be
an arbitrary subset of $\mathcal{G}_{n}$, e.g., the set of graphs with $m$
edges. The study of random networks can be seen as the study of properties that
are true for most elements of $S$, i.e., that are true with high probability
for a uniformly random element of $S$. With this in mind, we pursue the
following question: What are general sufficient conditions for the uniform
measure on a set of graphs $S \subseteq \mathcal{G}_{n}$ to be approximable by
a product measure?
