Suppose we have the following mixed effects model for observation $Y_{ij}$ of pupil $i$ in school $j$:
$Y_{ij}=b_0 + u_j + e_{ij}$
Here, $b_0$ is a fixed parameter for the "grand mean", $u_j$ is the random effect of school $j$ and $e_{ij}$ is the residual term for pupil $i$ in school $j$. Once the fixed and random effects have been estimated, the BLUP for each school can be calculated, which shows shrinkage towards the grand mean. I think this entails that the BLUPs of the schools are all biased towards the grand mean; that is, as a prediction of the unknown true $Y$ mean of a given school, the BLUP is biased. However, the U in "BLUP" means "Unbiased". So, my question is: how must I understand this unbiasedness of the BLUP?
My guess is that it means that one must calculate the BLUP for all schools in a sample, and then calculate the difference between the true school means (could be simulated) and the BLUPs. The mean of these differences should approach zero, if the sample is large enough and the true school means are normally distributed, just like the error terms. But is this indeed what the unbiasedness of the BLUP means?