  We present a series of full-shape analyses of galaxy power spectrum multipole
measurements from the 6dFGS, BOSS, and eBOSS galaxy surveys. We use an emulated
effective field theory of large-scale structure (EFTofLSS) model to conduct
these analyses. We exploit the accelerated prediction speed of the
neural-network-based emulator to explore various analysis setups for our
cosmological inference pipeline. Via a set of mock full-shape analyses of
synthetic power spectrum multipoles, designed to approximate measurements from
the surveys above, we demonstrate that the use of alternative priors on
nuisance parameters and restricted model complexity reduces many of the biases
previously observed in marginalised cosmological constraints coming from
EFTofLSS analyses. The alternative priors take the form of a Jeffreys prior; a
non-informative prior that can mitigate against biases induced by marginalising
over poorly constrained nuisance parameters. When performing a joint analysis
of all synthetic multipoles, we see an improvement in the level of agreement
between the marginalised $\ln{\left(10^{10}A_s\right)}$ constraints and the
truth; from $\sim2.0\sigma$ to $\sim0.42\sigma$. Using our pipeline to analyse
the measured multipoles, we find an improvement in the level of agreement with
cosmic microwave background (CMB) results; from $\sim2.4\sigma$ to
$\sim0.5\sigma$. Therefore, we conclude that the spectroscopic galaxy survey
datasets listed above are consistent with constraints obtained from the CMB.
