That is really interesting! I would have guessed that multiple dimensions would be required, e.g. religious/atheist, conservative/liberal, parent/no-kids, who knows... after all there are a variety of community notes topics.
One possible explanation for why these dimensions don't improve the algorithm a lot is that differences in these dimensions don't cause differences in whether users rate a note as helpful or unhelpful -- at least not beyond what can be explained by the primary latent factor. These other dimensions may contribute to other factors of user behavior -- such as which tweets they like and what users they follow. But once we know a user's left-right polarity factor, these other factors don't make a huge difference on whether or not a user ranks a note as helpful (given they rated the note at all). They do make a difference, but since most of the difference is already explained by the polarity factor, they don't add much to the algorithm.
Thanks a lot!