Online research in philosophy

The approach to generative grammar originating with Chomsky (1957) has been enormously successful within linguistics. Seeing such success, one wonders whether a similar approach might help us understand other human domains besides language. One such domain is morality. Could there be universal generative moral grammar? More specifically, might it be useful to moral theory to develop an explicit generative account of parts of particular moralities in the way it has proved useful to linguistics to produce generative grammars for parts of particular languages? Should moral theorists attempt to develop a theory of moral universals that is analogous to the theory of universal grammar in linguistics? Can moral theorists develop a “principles and parameters” account of possible moralities inspired by the principles and parameters approach to language in current linguistics? Could there be a “minimalist” program for moral theory inspired by the minimalist program in linguistics? In this chapter we offer a preliminary account of some analogies, focusing on clarifying issues, making distinctions, and considering how—in a general way—such analogies might yield a fruitful research program for moral theory. There are two main parts to our discussion, one focusing on an analogy between generative grammar and moral theory, the other focusing on analogies between universal grammar and theories of moral universals. In the first part, we say a little about the background and say how we are going to understand morality and moral theory. We describe certain aspects of generative grammar and how claims about generative grammars are tested, allowing for a distinction between “competence” and “performance”. We then try to say what a corresponding “generative moral grammar” would be and how it would be tested. We next discuss a number of objections to the analogy between moral theory and generative grammar and indicate possible responses. In the second part, we discuss certain universal constraints on grammars and consider whether there might be similar constraints on moralities. Then we discuss how linguists describe core aspects of languages in terms of principles and parameters and consider what aspects of moralities might be described in similar terms. After that we make some brief remarks about minimalism.

We compare our model of unsupervised learning of linguistic structures, ADIOS [1, 2, 3], to some recent work in computational linguistics and in grammar theory. Our approach resembles the Construction Grammar in its general philosophy (e.g., in its reliance on structural generalizations rather than on syntax projected by the lexicon, as in the current generative theories), and the Tree Adjoining Grammar in its computational characteristics (e.g., in its apparent affinity with Mildly Context Sensitive Languages). The representations learned by our algorithm are truly emergent from the (unannotated) corpus data, whereas those found in published works on cognitive and construction grammars and on TAGs are hand-tailored. Thus, our results complement and extend both the computational and the more linguistically oriented research into language acquisition. We conclude by suggesting how empirical and formal study of language can be best integrated.

Katz offers such a grammatical account, in which makes it possible for the first time to explain the illocutionary potential of sentences within grammar.

A certain metaphysical thesis about meaning that we'll call Informational Role Semantics (IRS) is accepted practically universally in linguistics, philosophy and the cognitive sciences: the meaning (or content, or `sense') of a linguistic expression1 is constituted, at least in part, by at least some of its inferential relations. This idea is hard to state precisely, both because notions like metaphysical constitution are moot and, more importantly, because different versions of IRS take different views on whether there are constituents of meaning other than inferential role, and on which of the inferences an expression occurs in are meaning constitutive. Some of these issues will presently concern us; but for now it will do just to gesture towards such familiar claims as that: it's part and parcel of dog meaning dog2 that the inference from x is a dog to x is an animal is valid; it's part and parcel of boil meaning boil that the inference from x boiled y to y boiled is valid; it's part and parcel of kill meaning kill that the inference from x killed y to y died is valid; and so on. (See Cruse, Ch. 1 and passim.) IRS brings in its train a constellation of ancillary doctrines. Presumably, for example, if an inference is constitutive of the meaning of a word, then learning the word involves learning that the inference holds. If dog means dog because dog ---> animal is valid, then knowing that dog ---> animal is valid is part and parcel of knowing what the word dog means; and, similarly, learning that x boiled y ---> y boiled is part and parcel of learning what boil means, and so forth. IRS constrains grammatical theories. The semantic lexicon of a language is supposed to make explicit whatever one has to know to understand the lexical expressions of the language, so IRS implies that meaning constitutive inferences are part of the semantic lexical entries for items that have them. Lexical entries are thus typically complex objects (`bundles of inferences') according to standard interpretations of IRS..

Meaning in philosophy, by K. Lehrer.--Meaning in linguistics, by A. Lehrer.--Theories of meaning, by W. Alston.--Of names, by J. S. Mill.--Of words, by J. Locke.--Of language, by G. Berkeley.--Signs and behavior situations, by C. Morris.--Meaning and verification, by M. Schlick.--Meaning and use, by R. Wells.--The meaning of a word, by J. Austin.--Meaning and speech acts, by J. R. Searle.--Meaning and linguistic analysis, by C. C. Fries.--The semantic compound of a linguistic description, by J. J. Katz.--Componential analysis and universal semantics, by J. Lyons.--Bibliographical essay (p. 213-216).

In most language technology applications that include a lexicon, this lexicon is a collection of static accounts of the properties of words, such as their meaning. However, in human conversations it is often the case that word-meaning is adjusted to fit the context. Pustejovsky’s [10] theory of the Generative Lexicon explores some regular ways in which word meanings shift in context and thus represents an important step towards the implementation of systems which can assign meanings to words dynamically depending on the context in which they occur.

The Generative Lexicon presents a novel and exciting theory of lexical semantics that addresses the problem of the "multiplicity of word meaning" - that is, how ...

Jackendoff's Foundations of Language: Brain, Meaning, Grammar, Evolution attempts to reconnect generative linguistics to the rest of cognitive science. However, by minimally acknowledging decades of work in cognitive linguistics, treating dynamical systems approaches somewhat dismissively, and clinging to certain fundamental dogma while revising others, he clearly risks satisfying no one by almost pleasing everyone.

The goal of this study is to reintegrate the theory of generative grammar into the cognitive sciences. Generative grammar was right to focus on the child's acquisition of language as its central problem, leading to the hypothesis of an innate Universal Grammar. However, generative grammar was mistaken in assuming that the syntactic component is the sole course of combinatoriality, and that everything else is “interpretive.” The proper approach is a parallel architecture, in which phonology, syntax, and semantics are autonomous generative systems linked by interface components. The parallel architecture leads to an integration within linguistics, and to a far better integration with the rest of cognitive neuroscience. It fits naturally into the larger architecture of the mind/brain and permits a properly mentalistic theory of semantics. It results in a view of linguistic performance in which the rules of grammar are directly involved in processing. Finally, it leads to a natural account of the incremental evolution of the language capacity. Key Words: evolution of language; generative grammar; parallel architecture; semantics; syntax.