Navigation

    Voting Theory Forum

    • Register
    • Login
    • Search
    • Recent
    • Categories
    • Tags
    • Popular
    • Users
    • Groups

    Should we abstain from voting? (In nondeterministic elections)

    Philosophy
    2
    5
    212
    Loading More Posts
    • Oldest to Newest
    • Newest to Oldest
    • Most Votes
    Reply
    • Reply as topic
    Log in to reply
    This topic has been deleted. Only users with topic management privileges can see it.
    • bmjacobs
      bmjacobs last edited by

      Looking at Jason Brennan's "Polluting the polls" argument in the context of probabilistic voting
      https://bobjacobs.substack.com/p/should-we-abstain-from-voting-in

      T 1 Reply Last reply Reply Quote 0
      • T
        Toby Pereira @bmjacobs last edited by

        @bmjacobs Interesting article, but a couple of things. Where does it come from that in Borda you need 2/3 of the vote to ensure a win? Also Borda and winner-takes-all systems wouldn't have the step function if there are more than two candidates. E.g. having 40% of the vote under First Past the Post will still give you the win in many elections. If it's to guarantee the win then yes, but I don't think it's clear that that's what the graph is trying to say.

        bmjacobs 1 Reply Last reply Reply Quote 0
        • bmjacobs
          bmjacobs @Toby Pereira last edited by

          @toby-pereira Yes, this was about what "ensures a win" aka what guarantees it. This post didn't really go into the details on which threshold is necessary since it was more about comparing step functions and non-step functions, and what that entails for voters. However, since you're curious I'll try to explain why you need ⅔:
          Assume you control X% of the votes, want to make sure that option A wins, you do not know how the other 100–X% will vote, and there are K many options overall. No matter how you vote, the average rank of A within your X% of votes will be at least 1, and there will be some option B other than A that has an average rank of at most K/2 + 1 within your X% votes. The other 100–X% of voters might provide A with a rank of K and B with a rank of 1, in which case the overall average rank of A will be at least X% · 1 + (100 − X%)·K = K − X% · (K − 1) and that of B will be at most X% · (K/2 + 1) + (100 − X%) · 1 = 1 + X% · K/2. So, to guarantee that the latter is larger than the former, 1 + X% · K/2 > K − X% · (K − 1), you need to have X% > (K − 1)/(3K/2 − 1) ≈ K/(3K/2) = ⅔.

          T 1 Reply Last reply Reply Quote 1
          • T
            Toby Pereira @bmjacobs last edited by

            @bmjacobs OK, I think I get that. But I still don't think the graph is correct - it's giving a different measurement for a deterministic and non-deterministic systems. For non-deterministic methods, it seems to be working on the probability of getting elected, which I presume is what the "controlled winning probability" on the y axis means. But for the deterministic methods, it just gives a score of 100 if they are guaranteed to be elected and 0 otherwise.

            If it's a about guaranteed election then the non-deterministic methods should give 0 across the board. If it's probabilistic, then the non-deterministic methods are correct on the graph but the deterministic ones are wrong - though there isn't an exact probability you can give as it depends on voting patterns.

            bmjacobs 1 Reply Last reply Reply Quote 1
            • bmjacobs
              bmjacobs @Toby Pereira last edited by

              @toby-pereira See the "effective power" more as something over time. So for the random ballot, with a guaranteed 51% of the vote you'd be in power 51% of the time, but with a guaranteed 51% of the vote in a majoritarian system, you'd be in power 100% of the time. I'd gestured at this by saying "if you have 51% of the vote you are in power 100% of the time", but I'll make this all a bit clearer if I use this graph again in the future.

              1 Reply Last reply Reply Quote 1
              • First post
                Last post