Community Notes (CNs) of X enables users to collaboratively moderate misleading content. To resolve conflicting moderation, CNs infers a latent ideological dimension and selects notes garnering cross-partisan support. As this system is now deployed worldwide, we evaluate its operation across diverse polarization contexts. We analyze all 1.9 million moderation notes receiving 135 million ratings by March 2025, cross-referencing ideological scaling data on 13 countries. Our results show that the CNs algorithm effectively captures the main polarizing dimensions across countries, surfacing notes that garner cross-partisan support. This also means that, by design, CNs systematically under-moderate polarizing content. We analyze notes relating to four recent elections in the US (2024), the UK (2024), France (2024) and Germany (2025) and demonstrate that they are systematically under-moderated when compared to other notes, posing potential risks to civic discourse and electoral processes.