Might help to run some actual simulations with historic data. People can explain why they think these measures might work and others like me might explain why we feel these measures will likely backfire, but in the end simulations and causal modelling can answer many questions that pure reasoning can't. And if these give ambiguous results, incremental changes that can be rolled back can help to test the model without being too disruptive. Let's try to avoid an other HF20 incident.
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Yes, I'm not against running simulations, of course when the idea is to change behavior it's difficult to get a clear idea of what the new behavior would be under different economic incentives if we just model it on historical behavior, but it'll definitely help avoid something like using the wrong multiplier by a factor of 10 like with RC.
I guess this would help the covergent linear curve the most to help us arrive to some sensible constants in the n^2(n/c+1) curve.
It's obviously possible to not get close to the right numbers with curation and free downvotes too, but it's harder to see how historical behavior can help too much here.
I'dd personally like to see the simulated differences in outcomes between a set of those curves for different c, with a set of something like:
Where V is effective vests and S is a scaling factor somewhere in the 1.01 .. 1.05 range.