  We show that the abstract and conclusion of Hansen's {\it Econometrica}
paper, \cite{Hansen22}, entitled a modern Gauss-Markov theorem (MGMT), obscures
a material fact, which in turn can confuse students. The MGMT places ordinary
least squares (OLS) back on a high pedestal by bringing in the Cramer-Rao
efficiency bound. We explain why linearity and unbiasedness are linked, making
most nonlinear estimators biased. Hence, MGMT extends the reach of the
century-old GMT by a near-empty set. It misleads students because it misdirects
attention back to the unbiased OLS from beneficial shrinkage and other tools,
which reduce the mean squared error (MSE) by injecting bias.
