Philosophy

If I predict rain tomorrow based on satellite and radar imagery showing a cold front forming, and it does rain, I’m right.

If I predict rain because I saw a black cat walk under a ladder, and it rains, am I right (but for the wrong reasons) or am I just wrong?

Can one ever be right for the wrong reasons?

Aviator, diver, Etherean, nexialist, PhD in aviation ∩ climate science | Host of /diving /ethfinance /eth-staker /geopolitics /science /singapore /thomas

What information would you have to see in order to conclude that black cats under ladders is actually informative of weather patterns?

The only problem is externality pricing.

Building https://negationgame.com

Right, and that would require you to accurately record that the predictions were *right*.

But if you practice justificationism you'll happily throw out the predictions because they come from a methodology (a model / explanation) you don't endorse, so they can't be right.

iow, to be wrong you must grant they're right

Like everything else, repeatability under controlled conditions (that and Nestle would have purchased the rights to all black cats)