Abstract

This is a corpus-based study on the uses and functions of modal verbs “will” and “shall” in the Nigerian legal discourse. It aims at examining their pragmatic functions as hedges in the legal discourse. It specifically aims to investigate how hedges are used in the legal texts to indicate precision and uncertainty. To achieve these objectives a specialised corpus was constructed which we named as “Nigerian Law Corpus” (NLC). The compilation of NLC is based on the Nigerian court proceedings and law reports. Hence, the compiled NLC corpus contains 546,313-word tokens. Meanwhile, reference corpus of law with 2.2 million word tokens based on the British National Corpus (BNC) is retrieved for comparison with NLC. To this end, two concordance tools were utilised to analyse the data of this study viz. “AntConc version 3.5” a semi-automated computer-aided tool and a web-based tool “Lextutor version 7”. Based on the frequency distribution the results revealed that model verb “will” featured in 493 instances in the NLC and 7,711 instances in the BNC Law, while, “shall” occurred at 401 instances in NLC and 1,348 instances in BNC Law. The results also indicated that “shall” was an overused element in NLC than in BNC Law with standardised concordance hits per million (NLC=734, BNC Law =589) while, “will” is the least used element of NLC (902 instances per million) compared to BNC Law (3,369 instances per million). The study also enumerated different semantic and pragmatic functions of “will” and “shall” in legal discourse, citing examples from both tag corpus (NLC) and reference corpus (BNC Law). Some of the functions as hedges (conveying a truth value of a proposition) are epistemic meanings: politeness, obligation, precision, duty, intention, and permission. In nutshell, the results indicated that “will” and “shall” are used by legal practitioners more especially lawyers in a courtroom to achieve precision in their argument in a case to persuade the court by showing the true value of commitment of the proposition.

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