Hi @Backfeed_cc, thank you very much for your reply!
Yes, that is an important distinction between BF and QP. QP was designed to enable a global reputation currency. The simplicity of having a global universal currency makes it worth to have a system QP, even if BF was superior to QP in most other respects.
Quantified Prestige networks can be local or global; specific or universal. The question is when a network should use QP, or when it should use BF, or whether it would make sense to develop some kind of synthetic system that takes the best parts of both systems to create an even better one. Anyway, I think that both QP and BF will need to go through long stages of empirical testing to find out what systems are really best suited for certain networks.
I really like that term. It perfectly encapsulates the (micro)political use of BF. QP has much more of an economic focus than a political one.
I think that aligns very nicely with my idea of a fractal society, which was the basis for giving Fractal Future its name (it was called Social Future Metanet at first). People should be as free as possible to self-organize into groups of like-minded peers. Of course, the issue exists that like-minded peers are relatively scarce. Finding them seems to be a hard problem. Dating platforms seem to try solving that problem, but of course there’s the disadvantage that they are too narrowly focused on dating, and not on bringing generally like-minded people together.
Decentralized governance seems to be a seriously hard problem. I’m glad that you are working on that.
Wow, that sounds like a very clever way of putting it! 
I really love that way of expressing that idea. I think you’re on to something big. This may tie in to my IEET article Solving Problems with Collective Intelligence.
This means that as the number of members and actions in a network increases, the relative reputation weight of each member and each action decreases. But since total value might be roughly proportional to both members and their actions, this doesn’t seem to be a real problem. You only need to ensure that the distribution of reputation remains roughly appropriate.
The feedback on feedback mechanism seems to work for that purpose. The QP approach for making reputation distribution appropriate is by limiting reputation-giving power to a fixed amount, so that people need to think well about how to distribute their reputation-giving power. Both approaches seem to have their strengths and weaknesses. Perhaps it might be worth considering combining both. The resulting system might be quite complex, but at least it may evade certain failure modes of each single approach.
Ok, so there are several (potential) differences between QP and BF here:
- Reputation does not (directly) create an income in BF – but it does in QP.
- Reputation corresponds with influence in BF. In QP, this would require tying in reputation scores with decision mechanisms. I’ve considered reputation-dependent polls as one such mechanism. But I haven’t spend a lot of thought on network governance in general, yet.
- Reputation increases the weight of your evaluation of others in BF, but not in QP. At first, I also considered doing the same in QP, but then settled for a more egalitarian and “linear” approach for QP, mostly because it makes the mathematics of the system much easier. That might not be the best motivation, but I guess settling for simplicity is preferable to complexity, unless you really need that complexity.
That looks like a valid approach. I don’t see obvious overall advantages or disadvantages of this over the reputation income approach. The only big issue might be token inflation, which I’ve tried solving by reputation-dependent demurrage. But as this thread shows, this opens another whole can of worms.
Yes, there are good reasons for this approach. With QP I’ve settled for a more open way of determining value. People can esteem the contributions of others for any reason in QP, even if they can’t actually pinpoint how, or what specific action has been especially valuable. QP allows capturing subtle and diffuse value, which might get ignored when value has to be attached to specific actions. On the other hand, QP opens itself up to a larger variety of biases by following that approach.
Thank you very much for your invitation! I’ll get back to you! 