The purpose of this paper is to look at some existing methods of semantic information quantification and suggest some alternatives. It begins with an outline of Bar-Hillel and Carnap’s theory of semantic information before going on to look at Floridi’s theory of strongly semantic information. The latter then serves to initiate an in-depth investigation into the idea of utilising the notion of truthlikeness to quantify semantic information. Firstly, a couple of approaches to measure truthlikeness are drawn from the literature and (...) explored, with a focus on their applicability to semantic information quantification. Secondly, a similar but new approach to measure truthlikeness/information is presented and some supplementary points are made. (shrink)

In a 2017 AJP paper, Cevolani and Schurz propose a novel solution to the Preface Paradox that appeals to the notion of expected truthlikeness. This discussion note extends and analyses their approach by applying it to the related Lottery Paradox.

The KK principle is typically rejected in externalist accounts of knowledge. However, a standard general argument for this rejection is in need of a supportive explication. In a recent paper, Samir Okasha argues that the standard externalist argument in question is fallacious. In this paper I start off with some critical discussion of Okasha’s analysis before suggesting an alternative way in which an externalist might successfully present such a case. I then further explore this issue via a look at how (...) Fred Dretske’s externalist epistemology, one of the exemplifying accounts, can explain failure of the KK principle. (shrink)