Yes, I agree.

The OP seems to talk about cause-agnosticism (uncertainty about which cause is most pressing) or cause-divergence (focusing on many causes).

There's already a post about this.

Another disadvantage of moving to Reddit is that it would give the existing material on the EA Forum (which includes a lot of good stuff) less visibility (even though it would presumably stay online).

Overall I'd prefer the EA Forum to continue to exist.

A groundbreaking paper by Aidan Toner-Rodgers at MIT recently found that material scientists assisted by AI systems "discover 44% more materials, resulting in a 39% increase in patent filings and a 17% rise in downstream product innovation."

MIT just put up a notice that they've "conducted an internal, confidential review and concluded that the paper should be withdrawn from public discourse".

Right. I think it could be useful to be quite careful about what terms to use since, e.g. some who might actually be fine with some level of monitoring and oversight would be more sceptical of it if it's described as "soft nationalisation".

You could search the literature (e.g. on other industries) for existing terminology.

Part of our linguistic struggle here is that we're attempting to map the entire spectrum of gov. involvement and slap an overarching label on it. 

One approach could be to use terminology that's explicit about there being a spectrum. E.g. you could use terms like "tiers", "steps", "spectrum", etc. And then you could argue that the US government's approach is unlikely to be at either end of the spectrum (hands-off or total nationalisation).

Some of the listed policy levers seem in themselves insufficient for the government's policy to qualify as soft nationalization. For instance, that seems true of government contracts and some forms of government oversight. You might consider coming up with another term to describe policies that are towards the lower end of government intervention.

In general, you focus on the contrast between soft and total nationalization, but I think it could also be useful to make contrasts with lower levels of government intervention. In my view, there's a lot of ground between a hands-off approach and soft nationalization. Most industries (e.g. in the US) have a lot of regulation - and so the government doesn't take a hands-off approach - yet haven't been subjected to soft nationalization, as I'd use that term.

(Tbc this is a purely conceptual point and not an argument for or against any particular level of government intervention.)

I don't think one can infer that without having the whole distribution across different countries. It may just be that small countries have greater variance. (Though I don't know what principle the author used for excluding certain countries.)

I agree with that.

Also, notice that the top countries are pretty small. That may be because random factors/shocks may be more likely to push the average up or down for small countries. Cf:

Kahneman begins the chapter with an example of data interpretation using cases of kidney cancer. The lowest rates of kidney cancer are in counties that are rural and vote Republican. All sorts of theories jump to mind based on that data.  However, a few paragraphs later Kahneman notes that the data also shows that the counties with the highest rates of kidney cancer are rural and vote Republican. The problem is that rural counties have small sample sizes and therefore are prone to extremes. 

@Lucius Caviola and I discuss such issues in Chapter 9 of our recent book. If I understand your argument correctly I think our suggested solution (splitting donations between a highly effective charity and the originally preferred "favourite" charity) amounts to what you call a barbell strategy.

Detail, but afaict there were at least five Irish participants.