 The obvious inverse situation with the theory of classical semantic information is that logical contradictions, having a truth-likelihood of 0, will deliver a maximal information measure of 1. Referred to in the literature as the Bar-Hillel-Carnap Semantic Paradox, the most developed quantitative approach to addressing it is the theory of strongly semantic information (Floridi 2004). The conceptual motivation behind strongly semantic information is that for a statement to yield information, it must help us to narrow down the set of possible worlds. That is, it must assist us in the search for the actual world, so to speak (Sequoiah-Grayson 2007). Such a contingency requirement on informativeness is violated by both logical truths and logical contradictions, both of which measure 0 on the theory of strongly semantic information. See Floridi (2013) for further details. See also Brady (2016) for recent work on the relationship between quantitative accounts of information and analyticity. For a new approach to connecting quantitative and qualitative measures of information, see Harrison-Trainor et al. (2018)