Let’s imagine you were given the above information, and took your representor to be the full set of probability functions that satisfied these constraints. Roger White suggested an intuitive gloss on how you might receive information about propositions so related and so constrained (White 2010). White’s puzzle goes like this. I have a proposition \(X\), about which you know nothing at all. I have written whichever is true out of \(X\) and \(\neg X\) on the Heads side of a fair coin. I have painted over the coin so you can’t see which side is heads. I then flip the coin and it lands with the \(X\) uppermost. \(H\) is the proposition that the coin lands heads up. \(Y\) is the proposition that the coin lands with the “\(X\)” side up.