You’ve missed a key point, which is that rationalization refers to a process in which one of many possible hypothesis is arbitrarily selected, which the rationalizer then attempts to support using a fabricated argument. In your query, you are asking that a piece of data be explained. In the first case, one filters the evidence, rejecting any data that too strongly opposes a pre-selected hypothesis. In the second case, one generates a space of hypothesis that all fit the data, and selects the most likely one as a guess. The difference is between choosing data to fit a hypothesis, and finding a hypothesis that best fits the data. Rationalization is pointing to a blank spot on your map and saying, “There must be a lake somewhere around there, because there aren’t any other lakes nearby,” while ignoring the fact that it’s hot and there’s sand everywhere.
You’ve missed a key point, which is that rationalization refers to a process in which one of many possible hypothesis is arbitrarily selected, which the rationalizer then attempts to support using a fabricated argument. In your query, you are asking that a piece of data be explained. In the first case, one filters the evidence, rejecting any data that too strongly opposes a pre-selected hypothesis. In the second case, one generates a space of hypothesis that all fit the data, and selects the most likely one as a guess. The difference is between choosing data to fit a hypothesis, and finding a hypothesis that best fits the data. Rationalization is pointing to a blank spot on your map and saying, “There must be a lake somewhere around there, because there aren’t any other lakes nearby,” while ignoring the fact that it’s hot and there’s sand everywhere.