Another idea it puts forwards is the use of structured data for labeling decisions, for instance, maybe you trust a providers' recommendations related to racism but not transphobia, or maybe you want the CSAM and DNI data, but not to block bridges. This is all possible if we've more structured data.
Finally, FIRES makes zero opinions on how data enters the system: whether it's through a collective voting on taking specific action, or an algorithmic sourcing of data, this is up to upstream software to decide, FIRES will just keep a record of those decisions over time.
Within scope of funding may be building some of these tools, that's still to be decided.
I look forwards to working with NLNet to help bring distributed moderation data to the Fediverse.