How does the following matrix algebra reduce dimensionally

$$\left( \frac{\boldsymbol{\Sigma}^{-1} \boldsymbol{1} }{\boldsymbol{1}^\top \boldsymbol{\Sigma}^{-1} \boldsymbol{1}}\right)^\top$$
given that $\boldsymbol{\Sigma}$ is the covariance matrix and $\boldsymbol{1}$ is a vector of ones?

I think the solution is a vector, like how its un-transposed self was a vector, but I'm more interested in **how the transpose operator changes the dimensions of each individual vector and matrix** in the parentheses, derivation-wise. which explains the question title being "how to", instead of "what is".