Three Rich-Lexicon Theories of Slurs: A Comparison

Abstract Many authors writing on slurs think that they are lexically rich, in the sense that their lexical meaning comprises both a descriptive dimension and an expressive/evaluative one, the latter accounting for their derogatory character. However, more fine-grained theories of slurs have recently been proposed, drawing on frameworks from lexical semantics. My main aim in this paper is to compare three such fine-grained rich-lexicon theories—the one put forward by myself in previous work with two similar ones, Croom’s (2011, 2013) and Neufeld’s (2019, 2022). While my primary aim is to underlie the commonalities and differences between the three views, I also aim at showing that the latter views have some issues that are easily avoided in the framework I propose.

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Publication Details

Journal
Topoi
Published
2024-12-27
DOI
https://doi.org/10.1007/s11245-024-10125-9
Primary Topic
Mining and Resource Management
Type
article
Field-Weighted Citation Impact
0.00

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article

Three Rich-Lexicon Theories of Slurs: A Comparison

Dan Zeman
Topoi
Mining and Resource Management
article

Three Rich-Lexicon Theories of Slurs: A Comparison

Dan Zeman
article en

Abstract

Abstract Many authors writing on slurs think that they are lexically rich, in the sense that their lexical meaning comprises both a descriptive dimension and an expressive/evaluative one, the latter accounting for their derogatory character. However, more fine-grained theories of slurs have recently been proposed, drawing on frameworks from lexical semantics. My main aim in this paper is to compare three such fine-grained rich-lexicon theories—the one put forward by myself in previous work with two similar ones, Croom’s (2011, 2013) and Neufeld’s (2019, 2022). While my primary aim is to underlie the commonalities and differences between the three views, I also aim at showing that the latter views have some issues that are easily avoided in the framework I propose.

TopoiVol. 45(1)
Universidade do Porto (PT)
Slovak Academic Information Agency, Universidade do Porto, Fundação para a Ciência e a Tecnologia
Openalex Percentile: Top 74%
Mining and Resource Management
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