  Informally, we might reason as follows. Either (7) is true or (7) is not true. Thus, either (8) is true or (9) is true. Thus, (7) is true. Thus (8) is true and (9) is not true, and (7) is still true. Iterating the process once again, we get (8) is true, (9) is not true, and (7) is true. More formally, consider any initial hypothesis, h0, about the truth values of (7), (8) and (9). Either h0 says that (7) is true or h0 says that (7) is not true. In either case, we can use the T-biconditional to generate our revised hypothesis h1: if h0 says that (7) is true, then h1 says that ‘(7) is true’ is true, i.e. that (8) is true; and if h0 says that (7) is not true, then h1 says that ‘(7) is not true’ is true, i.e. that (9) is true. So h1 says that either (8) is true or (9) is true. So h2 says that ‘(8) is true or (9) is true’ is true. In other words, h2 says that (7) is true. So no matter what hypothesis h0 we start with, two iterations of the revision process lead to a hypothesis that (7) is true. Similarly, three or more iterations of the revision process, lead to the hypothesis that (7) is true, (8) is true and (9) is not true — regardless of our initial hypothesis. In Section 3, we will reconsider this example in a more formal context. 