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Title
Contrastive lexical-conceptual analysis of folk religious concepts in English, Arabic, and Hebrew: NSM approach
Fields of Research (FoR) 2008:
Author(s)
Publication Date
2012
Socio-Economic Objective (SEO) 2008
Abstract
The primary aim of this dissertation is to explore a number of religious concepts in English, Arabic, and Hebrew. These concepts are English angels, the devil, God, heaven, hell, martyr, sin, and grace, as well as their Arabic and Hebrew near equivalents. These concepts are investigated from a linguistic point of view. Linguistic evidence is based mainly on usage data from corpora of everyday language. The corpora are the Corpus of Contemporary American English (410+ million words), Collins Wordbanks Online: English (500+ million words), ArabiCorpus (68 million words), and HebrewCorpus (150 million words). The description of the results is done by relying on the Natural Semantic Metalanguage theory, developed by Anna Wierzbicka, Cliff Goddard, and colleagues. To lay the groundwork, the dissertation establishes Arabic and Hebrew versions of NSM. In other words, it identifies the exponents of the 64 Natural Semantic Metalanguage semantic primes and maps out their basic combinatorial properties. Semantic explications of the target religious concepts are then developed in terms which are both comprehensible to ordinary people and translatable between the three languages in question. This enables a clear delineation of the similarities and differences among the folk religious concepts. The dissertation is primarily a contribution to linguistic semantics. It is the first detailed study of folk religious concepts from a linguistic vantage point, and it is the first detailed study of the Arabic and Hebrew versions of the Natural Semantic Metalanguage. In addition, the results of this dissertation contribute to the fields of lexicography, corpus analysis, interfaith dialogue, cross-cultural communication, and religious education.
Publication Type
Thesis Doctoral
Fields of Research (FoR) 2020
Socio-Economic Objective (SEO) 2020
HERDC Category Description
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