I'm very proud of this scenario.  (Even if you're confident you aren't going to play it, I think you could read the wrapup doc and in particular the section on 'Bonus Objective' so you can see what it involved).

It accomplished a few things I think are generally good in these scenarios:

• There was underlying structure that players could uncover, which created emergent complexity in the output but made sense with the theme once the underlying ruleset was revealed/discovered.
• Human thought about e.g. the theme and what patterns would be reasonable to observe was valuable, the puzzle was not optimally-solved just by feeding the data into a model and calling it a day.
• Multiple levels of solution were possible, from a decent solution with little effort up to a more-involved solution that went further and dug into the underlying structure.

And also it managed to trick many players with a surprising-yet-thematic twist :P

...oops.  It turns out that efficiently solving the Knapsack Problem is hard.

On looking in, it looks like my confusion with python variables means that, while your soldiers will always find a valid solution if it's reachable by a few straightforward rules, they will sometimes fail to find the solution if it wouldn't be reachable like that.^[1]

This doesn't affect the performance of any submitted team (since the teams were evaluated using the same code that the dataset was generated with), but it does mean that the underlying ruleset was messier and less derivable than I'd hoped...sorry :(

1. ^{^}

   In detail: when your soldiers can't find a solution using simple rules, they were supposed to list each possible target for their biggest shot, and make separate branches for each of those.  However, a bug means that the code execution for the first branch removes shots from their available list for the later branches, and so all the later branches are doomed.  Therefore they will win only if the first branch works.

I have mixed feelings about this scenario.

I was proud of the underlying mechanics, which I think managed to get interesting and at-least-a-little-realistic effects to emerge from some simple underlying rules.

The theme...at least managed to make me giggle to myself a little as I was writing it.

When players submitted answers to this, though, several people got tricked into getting themselves killed.  Out of five answers, two players took extremely safe approaches.  Of the three players who were more daring, one submitted an excellent answer while two managed to trick themselves into submitting answers that were worse than random.

From a certain point of view, this is a valuable learning experience, which could teach people not to take drastic risks on limited data.

But I feel like other scenarios in this genre may have taught that lesson better without shooting quite so many players in the foot.

Another downside of this strategy is that a political faction not currently perceived by voters as 'in power' has an incentive to use any power they do have to actively worsen the lives of voters, who will blame their opposition.

Your boolean disagreement is relevant because it's actionable.  Suppose that:

• Alice thinks calling is +$100 EV
• Bob thinks calling is +$10 EV
• Claire thinks folding is +$10 EV
• David thinks folding is +$100 EV

In this case, Bob is much closer to Claire than to Alice in terms of their beliefs.  But Bob agrees with Alice about the correct action, which is often the thing where disagreement actually matters.

(Politics-related examples are left as exercises for the reader).

I think this is definitely an effect, but I do not think that Bughouse would have been my first example for 'a game where you need to cooperate with random other people online and can be sabotaged by their inexplicable ineptitude.'

See e.g. this Reddit meme.

Doris wasn’t self-sacrificing. Amaryllis, now there was a woman who would be able to make a suicide bomber clone. If Doris Finch tried it, her clone would, at best, start up an argument about which of them should be the one to do it, or try to spawn another clone to do the work for her.

This does not sound to me like good advice in general?  It could work with a small, driven team on a single focused project who wants to be sure everyone has hands on everything.  But in general, specialization is an extremely powerful tool that we use to accomplish things we cannot accomplish alone.  I would not benefit from insisting on understanding the whole fertilizer production supply chain before I could eat breakfast.

You seem to be conflating 'amount of money paid to the worker as salary' with 'amount of capital used to equip the worker'.

...I would say that the Soft PNR has clearly already occurred?