GiveWell, for example, has explicitly distanced themselves from numerical calculations (albeit recently) and several EAs have called into question the usefulness of cost-effectiveness estimates, a charge that was largely lead by GiveWell.

I'll speak up on this one. I am a booster of more such estimates, detailed enough to make assumptions and reasoning explicit. Quantifying one's assumptions lets other challenge the pieces individually and make progress, where with a wishy-washy "list of considerations pro and con" there is a lot of wiggle room about their strengths. Sometimes doing this forces one to think through an argument more deeply only to discover big holes, or that the key pieces also come up in the context of other problems.

In prediction tournaments training people to use formal probabilities has been helpful for their accuracy.

Also I second the bit about comparative advantage: CEA recently hired Owen Cotton-Barratt to do cause prioritization/flow-through effects related work. GiveWell Labs is heavily focused on it. Nick Beckstead and others at the FHI also do some work on the topic.

It seems like the EA mainstream either agrees with many of your critiques already (and therefore you're just trying to convince EAs to adopt the mainstream)

I think that on some of these questions there is also real variation in opinion that should not simply be summarized as a clear "mainstream" position.