I'd argue negative correlation on conditionals distributions can be reasonable here.
In that particular WA-MS example, if Trump suddenly took more liberal positions and somehow won WA (e.g., announces he's pro abortion), he would in fact be more at risk of losing Mississippi. The idea that these two states are in play already is fringe and would require some major idealogical (or other third variable) shifts.
But then the correlations with the other 48 states are broken. In that insane scenario, Mississippi now votes for Biden (because I guess he’s suddenly come out as pro-life as well), but Alaska still goes for Trump.
The negative correlations don’t make sense. Maybe it’s a small problem and the model is solid overall, but... I don’t think you can justify that one effect.
I think you have to look at the joint distribution with Alaska included to draw any conclusions. Just looking at separate marginals will be uninformative.
In that particular WA-MS example, if Trump suddenly took more liberal positions and somehow won WA (e.g., announces he's pro abortion), he would in fact be more at risk of losing Mississippi. The idea that these two states are in play already is fringe and would require some major idealogical (or other third variable) shifts.