Brian, you want an answer to the real-world situation? Easy. First assume you have a source of inputs that is not antagonistic, as discussed. Then measure which deterministic pivot-choice algorithms would work best on large samples of the inputs, and use the best. Median-of-three is a great pivot choosing algorithm in practice, we’ve found. If your source of inputs is narrower than “whatever people anywhere using my ubergeneral sort utility will input” then you may be able to do better. For example, I regularly build DFAs from language data. Part of this process is a sort. I could implement this plan and possibly find that, I don’t know, median of first, last, and about-twenty-percent-of-the-way-in is in general better. I anticipate the effort would not be worth the cost, so I don’t, but there you are.
You don’t have to put constraints on the input, you can just measure them (or guess well!). They’re probably already there in real-world situations.
The Informations told/implied to the Humans that they don’t lie or withold information. That is not the same as the Humans knowing that the Informations don’t lie.