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Joined 11 months ago
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Cake day: May 8th, 2024

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  • Also:

    • gift economy/trading platform (e.g. like freecycle)
    • buying/selling (e.g. like ebay)
    • local community/bioregionalism networks (e.g. what nextdoor should be)

    These seem kind of ideal for a federated network, IMO.

    I actually think Lemmy would be a pretty decent format for something stackoverflow like - just maybe needs to UI tweaks to minimise the visual space that replies take up, plus maybe answered post flair



  • I have a maths major, and think in networks, same as you. I agree that that’s a good start to thinking about the problem. It’s basically similar approach to Jay Forrester’s World model, that used system dynamics to model the global economy.

    But what you’re doing is building a model, and then proposing using it to make decisions about how to run the world. This would be sensible, except that any model is necessarily a simplification of the real world, and that simplification process is subjective. What you value and care about and think is important defines what you put in the model, and also what you optimise for, and how you interpret the outputs. So your decisions ultimately end up being subjective too.

    There are other issues too, such as the fact that any dynamic model like this exhibits complexity, which makes it analytically unsolveable; and chaos, which means numerical predictions will suffer from unpredictability due to the Butterfly effect, and the Hawkmoth effect.

    If you want to get a deeper understanding of this stuff, systems thinking is where you need to head. I would recommend this paper as an excellent introduction to the field as a whole: https://www.scienceopen.com/hosted-document?doi=10.54120%2Fjost.000051 (Open access, about 50 pages)

    For the first wave/system dynamics approach, this article is worth a read too (IMO it presents far to simple a picture though): https://donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/













  • Adding my own explanation, because I think it clicks better for me (especially when I write it down):

    1. Pick a door. You have a 66% chance of picking a wrong door, and a 33% of picking the right door.
    2. Monty excludes a door with 100% certainty
    3. IF you picked a wrong door, then there’s a 100% chance the remaining door is correct (so the contingent probability is p(switch|picked wrong) = 100%), so the total chance of the remaining door being correct is p(switch|picked wrong)* p(picked wrong) = 66%.
    4. IF you picked the right door, then Monty’s reveal gives you no new information, because both the other doors were wrong, so p(switch|picked right) = 50%, which means that p(switch|picked right) * p(picked right) = 50% * 33% = 17%.
    5. p(don't switch|picked wrong) * p(picked wrong) = 50% * 66% = 33% (because of the remaining doors including the one you picked, you have no more information)
    6. p(don't switch|picked right) * p(picked right) = 50% * 33% = 17% (because both of the unpicked doors are wrong, Monty didn’t give you more information)

    So there’s a strong benefit of switching (66% to 33%) if you picked wrong, and even odds of switching if you picked right (17% in both cases).

    Please feel free to correct me if I’m wrong here.