  We introduce a new family of refined Sobolev-Malliavin spaces that capture
the integrability in time of the Malliavin derivative. We consider duality in
these spaces and derive a Burkholder type inequality in a dual norm. The theory
we develop allows us to prove weak convergence with essentially optimal rate
for numerical approximations in space and time of semilinear parabolic
stochastic evolution equations driven by Gaussian additive noise. In
particular, we combine a standard Galerkin finite element method with backward
Euler timestepping. The method of proof does not rely on the use of the
Kolmogorov equation or the It\={o} formula and is therefore non-Markovian in
nature. Test functions satisfying polynomial growth and mild smoothness
assumptions are allowed, meaning in particular that we prove convergence of
arbitrary moments with essentially optimal rate.
