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Joined 1 year ago
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Cake day: June 30th, 2023

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  • Voting is a small part of political change, it needs to be done but that’s not where the work is. Getting involved in your community and pushing for changes is far more productive, activism of all types.

    I would start by getting on mailing lists for things you care about and email for local city council meeting minutes. You might be surprised by some of the meeting times of local orgs. Some events are evening, but you can still learn about what is needed if you are staying engaged with local things. I can’t tell you what will work, but I reiterate I would start by getting on mailing lists for things you care about and take opportunities when they come.

    Edit: and don’t be so hard on yourself, you can only do what you can do. Take your wins when they come and focus on those.



  • Pick an issue, or a few, you care about. Find the local or regional group that is already fighting for that issue. Join their newsletter. When they have events or meetings near you, go. Meet people and network. Someday you will find a way you can help in a way that fits your skill set, say yes.

    It really is that easy to get involved, and these organizations need volunteers way more than they need money. People make the world move forward, not money, not votes. I mean voting and giving helps too, but giving your time is often way more important with activism.













  • I think you’re missing the point of predictive modeling. It’s probability of separate outcomes is built in. This isn’t fortune telling, there is no crystal ball. Two predictive models can have different predictions and they both may have value. Just like separate meteorologists can have different forecasts, but predict accurately the same amount over time, all be it at different intervals. IIRC, the average meteorologist correctly predicts rain over 80% of the time. They are far over predicting by chance. But if you look at the forecast in more than one place you often get slightly different forecasts. They have different models and yet arrive at similar conclusions usually getting it mostly accurate. It’s the same with political forecasts, they are only as valuable as your understanding of predictive modeling. If you think they are intended to mirror reality flawlessly, you will be sorely disappointed. That doesn’t make the models “wrong”, it doesn’t make them “right” either. They are just models that usually predict a probable outcome.


  • His model has always been closer state to state, election to election than anyone else’s, which is why people use his models. He is basically using the same model and tweaking it each time, you make it sound like he’s starting over from scratch. When Trump won, none of the prediction models were predicting he would win, but his at least showed a fairly reasonable chance he could. His competitors were forecasting a much more likely Hillary win while he was showing that trump would win basically 3 out of 10 times. In terms of probability that’s not a blowout prediction. His model was working better than competitors. Additionally, he basically predicted the battleground states within a half percentage iirc, that happened to be the difference between a win/loss in some states.

    So he has exactly one chance to get it right.

    You’re saying it hitting one of those 3 of 10 is “getting it wrong”, that’s the problem with your understanding of probability. By saying that you’re showing that you don’t actually internalize the purpose of a predictive model forecast. It’s not a magic wand, it’s just a predictive tool. That tool is useful if you understand what it’s really saying, instead of extrapolating something it absolutely is not saying. If something says something will happen 3 of 10 times, it happening is not evidence of an issue with the model. A flawless model with ideal inputs can still show a 3 of 10 chance and should hit in 30% of scenarios. Certainly because we have a limited number of elections it’s hard to prove the model, but considering he has come closer than competitors, it certainly seems he knows what he is doing.




  • but it does mean that Boeing got something wrong.

    Comparing it to Boeing shows you still misunderstand probability. If his model predicts 4 separate elections where each underdog candidate had a 1 in 4 chance of winning. If only 1 of those underdog candidates wins, then the model is likely working. But when that candidate wins everyone will say “but he said it was only a 1 in 4 chance!”. It’s as dumb as people being surprised by rain when it says 25% chance of rain. As long as you only get rain 1/4 of the time with that prediction, then the model is working. Presidential elections are tricky because there are so few of them, they test their models against past data to verify they are working. But it’s just probability, it’s not saying this WILL happen, it’s saying these are the odds at this snapshot in time.