  The theme of the first two sections, is to prepare the framework of how from
a "complicated" family of index models I in K_1 we build many and/or
complicated structures in a class K_2. The index models are characteristically
linear orders, trees with kappa+1 levels (possibly with linear order on the set
of successors of a member) and linearly ordered graph, for this we phrase
relevant complicatedness properties (called bigness).
  We say when M in K_2 is represented in I in K_1. We give sufficient
conditions when {M_I:I\in K^1_\lambda} is complicated where for each I in
K^1_lambda we build M_I in K^2 (usually in K^2_lambda) represented in it and
reflecting to some degree its structure (e.g. for I a linear order we can build
a model of an unstable first order class reflecting the order). If we
understand enough we can even build e.g. rigid members of K^2_lambda.
  Note that we mention "stable", "superstable", but in a self contained way,
using an equivalent definition which is useful here and explicitly given. We
also frame the use of generalizations of Ramsey and Erdos-Rado theorems to get
models in which any I from the relevant K_1 is reflected. We give in some
detail how this may apply to the class of separable reduced Abelian p-group and
how we get relevant models for ordered graphs (via forcing).
  In the third section we show stronger results concerning linear orders. If
for each linear order I of cardinality lambda>aleph_0 we can attach a model M_I
in K_lambda in which the linear order can be embedded so that for enough cuts
of I, their being omitted is reflected in M_I, then there are 2^lambda
non-isomorphic cases.
