If you want a bit more detail, look at my edit. The functions to calculate the hot and scaled for content is now there.

You're making assumptions about how they work based on your intuition - luckily we don't need to do much guesswork about how the sorts are actually implemented because we can just look at the code to check:

CREATE FUNCTION r.scaled_rank (score numeric, published timestamp with time zone, interactions_month numeric)
    RETURNS double precision
    LANGUAGE sql
    IMMUTABLE PARALLEL SAFE
    -- Add 2 to avoid divide by zero errors
    -- Default for score = 1, active users = 1, and now, is (0.1728 / log(2 + 1)) = 0.3621
    -- There may need to be a scale factor multiplied to interactions_month, to make
    -- the log curve less pronounced. This can be tuned in the future.
    RETURN (
        r.hot_rank (score, published) / log(2 + interactions_month)
);

And since it relies on the hot_rank function:

CREATE FUNCTION r.hot_rank (score numeric, published timestamp with time zone)
    RETURNS double precision
    LANGUAGE sql
    IMMUTABLE PARALLEL SAFE RETURN
    -- after a week, it will default to 0.
    CASE WHEN (
now() - published) > '0 days'
        AND (
now() - published) < '7 days' THEN
        -- Use greatest(2,score), so that the hot_rank will be positive and not ignored.
        log (
            greatest (2, score + 2)) / power (((EXTRACT(EPOCH FROM (now() - published)) / 3600) + 2), 1.8)
    ELSE
        -- if the post is from the future, set hot score to 0. otherwise you can game the post to
        -- always be on top even with only 1 vote by setting it to the future
        0.0
    END;

So if there's no further changes made elsewhere in the code (which may not be true!), it appears that hot has no negative weighting for votes <2 because it uses the max value out of 2 and score + 2 in its calculation. If correct, those posts you're pointing out are essentially being ranked as if their voting score was 2, which I hope helps to explain things.

edit: while looking for the function someone else beat me to it and it looks like possibly the hot_rank function I posted may or may not be the current version but hopefully you get the idea regardless!

It's a simplified version they had explained somewhere in the documentation. Details like that may be left out.