A functional analysis of the verb-noun in Welsh

Lead Research Organisation: CARDIFF UNIVERSITY
Department Name: Sch of English Communication and Philos

Abstract

AIM: To propose a description of the 'berfenw' (English: verb-noun, VN) in Welsh, using the Systemic Functional Grammar (SFG) framework. It will draw on corpus-driven approaches to produce a description that is empirically-based and reproducible.

BACKGROUND: When conducting linguistic research, we are concerned with answering some fundamental questions: 'What is language? How does language work? How are languages different?'. If we are to take the SFG view that language is a meaning-making resource, analysing syntax in context could reveal patterns that might otherwise have gone undetected. There is, however, no expectation that all languages will be patterned in the same way: if a linguistic theory is to be robust and flexible, it must include as many language varieties as possible.

Welsh is a Celtic language with 538,300 resident speakers according to the 2021 Census. It poses several challenges: firstly, Welsh has Verb-Subject-Object order, which is unusual in the context of European languages. Secondly, Welsh has a word class that does not exist in most others: the VN, and there is some disagreement in the literature as to whether the VN contains more semantically verbal or nominal content.

THE ARGUMENT FOR AN SFG ANALYSIS: Existing analyses of the VN pose two issues: firstly, they only analyse the structure of formal elements, e.g. word classes. SFG posits that words are simply realisations of lexicogrammatical choices at a higher level in the language system, e.g. the Mood and Transitivity systems, so it is important that we analyse the role of the VN in the wider clause. Secondly, generative approaches rarely employ the use of authentic data. Text is presented detached from context thus any patterns identified cannot be probabilistically mapped or tested on a larger scale. There have been calls for linguists to hold themselves to the same rigorous standards expected of other social science disciplines, citing examples of when the introspective approach has in fact led to inaccurate conclusions.

OBJECTIVES: Where no functional description exists, as is the case with Welsh, it must be gradually developed based on the analysis of a representative sample of texts. I began this process during my MA project, designing a small-scale, corpus-driven analysis of the Subject in Welsh to propose a functional description of Nominal Groups. This project will continue this work, focusing next on answering the following questions: What is the experiential contribution of the verbal system in Welsh? What is the function of the VN in Welsh? How are these patterns shaped by the context in which they are observed?

METHODS: I will use corpora to identify, extract and analyse verbs and verbal elements in the clause. Existing corpora are rarely coded for SFG functions, so my approach will need to adapt data coded for other purposes. The National Corpus of Contemporary Welsh (CorCenCC) contains over 11 million tokens across a range of registers and dialects. Tokens are POS-tagged which will allow for the extraction of a sample relevant word classes, the size of which will be determined following a closer review of the literature.

IMPACT: The Welsh Government has launched an ambitious strategy to reach one million speakers by 2050, citing investment in education and digital technologies amongst its primary enablers. Language descriptions in SFG have had far reaching impacts on these fields, therefore introducing minority languages such as Welsh into this framework is imperative to progress advancement in these key strategic areas. Furthermore, this project will respond to calls for a more quantitative and reproducible approach to language description, moving away from traditionally introspective and prescriptive approaches of the past.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
ES/P00069X/1 01/10/2017 30/09/2027
2884414 Studentship ES/P00069X/1 01/10/2023 30/09/2026 Lowri Williams