Online research in philosophy

Semantic minimalism is an attempt to answer two questions: ‘what counts as semantic content?’ and ‘what work does semantic content do?’. The answer the theory gives to both these questions is minimal (hence the name): first, semantic content is exhausted by the contributions made by the syntactic constituents of a sentence together with their mode of composition. Second the role played by this kind of content is much more constrained than is often supposed. With respect to the first question, semantic minimalism holds that content is entirely determined by syntax – there is nothing to be had ‘for free’, as it were, at the semantic level. Specifically, minimalism holds that it is not possible for features of the context of utterance to permeate semantic content unless their presence is demanded by something at the syntactic level. Furthermore, the syntactic elements which can trigger pragmatic intrusion are themselves limited to unarguably contextsensitive elements, such as words like ‘here’ and ‘now’. (Thus minimalism is not the thesis that semantic content is context-invariant, but that contextual infiltration of semantics is very limited.) So take utterances of the following sentences.

The concept of genetic information is controversial because it attributes semantic properties to what seem to be ordinary biochemical entities. I argue that nucleic acids contain information in a semantic sense, but only about a limited range of effects. In contrast to other recent proposals, however, I analyze genetic information not in terms of a naturalized account of biological functions, but instead in terms of the way in which molecules determine their products during processes known as template-directed syntheses. I argue that determining an outcome in a certain way is constitutive for being an instruction. On this account, the content of genetic information is identified with the template's properties, which determine the product in the way constitutive for instructions.

There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information (SDI) as meaningful data, in favour of the Dretske-Grice approach: meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth-values do not supervene on semantic information, and misinformation (that is, false semantic information) is not a type of semantic information, but pseudo-information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo-information. As a consequence, SDI is revised to include a necessary truth-condition. The last section summarises the main results of the paper and indicates some interesting areas of application of the revised definition.

This article mounts a defence of Floridi’s theory of strongly semantic information against recent independent objections from Fetzer and Dodig-Crnkovic. It is argued that Fetzer and Dodig-Crnkovic’s objections result from an adherence to a redundant practice of analysis. This leads them to fail to accept an informational pluralism, as stipulated by what will be referred to as Shannon’s Principle, and the non-reductionist stance. It is demonstrated that Fetzer and Dodig-Crnkovic fail to acknowledge that Floridi’s theory of strongly semantic information captures one of our deepest and most compelling intuitions regarding informativeness as a basic notion. This modal intuition will be referred to as the contingency requirement on informativeness. It will be demonstrated that its clarification validates the theory of strongly semantic information as a novel, and non ad hoc solution to the Bar-Hillel-Carnap semantic paradox.

What is it that one thinks or believes when one thinks or believes something? A mental formula? A sentence in some natural language? Its truth conditions? Or perhaps an abstract proposition? The current story of content is fairly ecumenical. It says that a number of aspects, some mental, other semantic, go into our understanding of content. Yet the current story is incomplete. It leaves out a very important aspect of content, one which I call incremental information. It is information in a specific format, information as a limited or local increment, structured by a number of underlying parameters. It is in the form of such increments that information drives cognition and behavior. This is why, perhaps of all aspects of content, it is incremental information which matters most when we want to understand cognitive attitudes and performances. This in turn must have an impact on our philosophical notions of content, propositional attitudes, inference, justification and knowledge.

‘Information’ and ‘code’ originated as technical terms within linguistics and information theory but are now widely used in genetics and developmental biology. Against this background, it is examined if coded information distinguishes genes from other information carriers, i.e., whether there are genetic words or sentences by virtue of the genetic code, and, if so, whether they have any semantic content. It is concluded that there is no genetic language with semantic content, but that the genetic code still enables unique language-like modes of transmission and interpretation of causal information.

This paper explores John Maynard Smith’s conceptual work on animal signals. Maynard Smith defined animal signals as traits that (1) change another organism’s behaviour while benefiting the sender, that (2) are evolved for this function, and that (3) have their effects through the evolved response of the receiver. Like many ethologists, Maynard Smith assumed that animal signals convey semantic information. Yet his definition of animal signals remains silent on the nature of semantic information and on the conditions determining its content. I therefore compare three ways to specify the semantic content of animal signals. The first suggestion models semantic content on Maynard Smith’s theory of genetic information. On the second proposal, semantic content is equated with a condition identified by conventional content ascriptions. The third suggestion is to explain semantic content in terms of consumer-based teleosemantics. I show how these accounts equate semantic content with distinct kinds of conditions and how they differ with respect to the kinds of traits that qualify as carrying semantic information.

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.