Thanks for the great clarifications, Lauren! Strongly upvoted.
Another specific i found out yesterday, someone was able to pass something through their local gov that led to 400 million animals being spared that wasn’t even on the radar before they entered. It seems extremely unlikely that this kind of leverage and counterfactual would be the case for the best vs. next best candidate in an NGO.
Interesting example! I would be interested to know more, but I understand it may be sensible information to share publicly. I think one can help 400 M shrimp donating 26.7 k$ (= 400*10^6/(15*10^3)) to the Shrimp Welfare Project (SWP). So, if your example was representative of the impact of a career in policy inside the system, and the impact per animal helped in your example matched that of SWP (which I estimated to be 0.0426 DALYs averted), maximising donations could still be better. For a career of 40 years, one would only need to donate 668 $ (= 26.7*10^3/40) more to SWP per year relative to the career in policy inside the system.
Thanks for the great clarifications, Lauren! Strongly upvoted.
Interesting example! I would be interested to know more, but I understand it may be sensible information to share publicly. I think one can help 400 M shrimp donating 26.7 k$ (= 400*10^6/(15*10^3)) to the Shrimp Welfare Project (SWP). So, if your example was representative of the impact of a career in policy inside the system, and the impact per animal helped in your example matched that of SWP (which I estimated to be 0.0426 DALYs averted), maximising donations could still be better. For a career of 40 years, one would only need to donate 668 $ (= 26.7*10^3/40) more to SWP per year relative to the career in policy inside the system.
Will reply properly later