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Context Sensitivity: Indexicalism, Contextualism, Relativism

  • Dan Zeman
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4635)

Abstract

The paper is primarily concerned with laying out the space of positions that purport to account for semantic context sensitivity of natural language expressions and with making a prima facie case for relativism. I start with distinguishing between pre-semantic, semantic and post-semantic context sensitivity. In the following section I briefly present the classic picture of indexicals due to David Kaplan and assess some arguments for the introduction of certain parameters in the circumstances of evaluation (specifically, time). In section III I envisage two views that purport to expand semantic context sensitivity beyond expressions from “the basic set”: indexicalism and contextualism. In section IV, by means of an example taken from John Perry, I draw attention to a specific form of semantic context sensitivity, namely that in which what is affected by context are the circumstances of evaluation of utterances rather than their content. The example leads to the necessity of distinguishing between two roles of context: a content-determinative one and a circumstance-determinative one. In section V I introduce relativism as the view incorporating the claim that context has a circumstance-determinative role and contrast it with the two views presented before. In the final section I analyze a certain type of argument usually adduced in favor of contextualism (the so-called “context-shifting arguments”) and show that in order to work it has to rule out relativism. I conclude by claiming that the battle must be fought by giving arguments to the effect that a certain parameter should or should not be part of the circumstances of evaluation rather than the content of utterances.

Keywords

Literal Meaning Epistemic Modal Knowledge Attribution Context Sensitivity Lexical Ambiguity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Dan Zeman
    • 1
  1. 1.Central European University, Department of Philosophy, Nador u. 9, H-1051, BudapestHungary

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