The closer your causal model comes to accurately reflecting the “counterfactual world” that it is supposed to refer or correspond to...
I’m not sure I understand this statement. Forget Oswald for a moment, and let’s imagine we’re working at an insurance company. A person comes to us, and says, “sell me some cancer insurance”. This person is currently does not have cancer, but there’s a chance that he could develop cancer in the future (let’s pretend there’s only one type of cancer in the world, just for simplicity). We collect some medical data from the person, feed it into our statistical model (which has been trained on a large number of past cases), and it tells us, “there’s a 52% chance this person will develop cancer in the next 20 years”. Now we can quote him a reasonable price.
How is this situation different from the “killing Kennedy” scenario ? We are still talking about a counterfactual, since Kennedy is alive and our applicant is cancer-free.
I’m not sure I understand this statement. Forget Oswald for a moment, and let’s imagine we’re working at an insurance company. A person comes to us, and says, “sell me some cancer insurance”. This person is currently does not have cancer, but there’s a chance that he could develop cancer in the future (let’s pretend there’s only one type of cancer in the world, just for simplicity). We collect some medical data from the person, feed it into our statistical model (which has been trained on a large number of past cases), and it tells us, “there’s a 52% chance this person will develop cancer in the next 20 years”. Now we can quote him a reasonable price.
How is this situation different from the “killing Kennedy” scenario ? We are still talking about a counterfactual, since Kennedy is alive and our applicant is cancer-free.
See my reply above, specifically the last paragraph.