Abstract
The chapter applies and further supports the conclusion reached in chapter five by presenting a quantitative theory of strongly semantic information (TSSI) based on truth-values rather than probability distributions. It argues that the classic quantitative theory of weakly semantic information (TWSI), based on probability distributions, assumes that truth-values supervene on factual semantic information, yet this principle is too weak and generates a well-known problem, called here the Bar-Hillel–Carnap Paradox (BCP). On the contrary, TSSI, according to which factual semantic information encapsulates truth, can avoid the BCP and is more in line with the standard conception of what generally counts as semantic information.
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