Stance has emerged in the literature on academic writing in a major way, and as an important and pervasive mechanism by which academic writers ‘inhabit’ their writing and give it distinctiveness (Baynham, 2011; 2014). In this study, I investigate what linguistic markers of stance accounting PhD authors are more frequently used in Bayero University Kano, Nigeria and what factors might constrain or influence their use. I draw primarily on a corpus-based textual analysis but complement this with a consideration of institutional and disciplinary factors which might explain why the writers investigated write as they do. I employ nine participants: six accounting PhD authors and three accounting PhD supervisors. I compile a corpus of six accounting PhD theses from Bayero University, Kano, Nigeria (BUK corpus), and an accounting sub-corpus: four accounting UK PhD theses (UK corpus) for comparative analysis with the BUK corpus. The result of comparative corpus-based textual analysis between BUK theses shows that there are certain similarities and differences in terms of using stance markers. For example, in terms of similarities all the six authors use higher frequencies of booster than the other categories of stance markers in their result sections; whereas in their conclusion section they all use higher frequencies of hedges than the other categories of stance markers. They also use few restricted typologies of each category of stance markers. On the other hand, there are certain differences in using stance markers, for example, only two out of the six authors use explicit self-mention features. Overall comparative results show that three authors use higher frequencies of hedge than the other categories of stance markers; whereas two authors use higher frequencies of booster than the other categories of stance markers; and one author use same frequency for both booster and hedge. The result of comparative corpus-based textual analysis between the BUK and UK corpora still shows there are certain similarities and differences that both corpora have higher frequencies of hedges than the other categories of stance markers. On the other hand, UK corpus has higher frequencies of attitude markers, neutral stance markers, explicit self-mention features; whereas BUK corpus has higher frequencies of hedge and booster. The contextual data however suggests that several factors might have constrained some of the accounting PhD authors (BUK) to use explicit self-mention features. Some of the factors are: the traditional practices of the University and Department discouraging the students to make themselves explicitly present through the use of personal pronouns; unequal power relationship between lecturers and students; a lack of explicit assumptions of academic writing, as well as absence of explicit statements or rules provided regarding the use of linguistic markers of stance in feedback provided during the supervision process. This study proposes an additional analytic category of stance into Hyland’s model, influenced by Mushin’s factual epistemological stance. The new category is neutral epistemic stance. Unlike previous studies which deal only in parts of theses, this study deals with theses as complete texts in order to add our understanding and knowledge on what linguistic markers of stance are more frequently used in the discipline of accounting across whole macrostructures of the theses particularly at BUK. On the basis of these findings, this study recommends a more broadly a genre-sensitive approach to the teaching of academic writing, including explicit teaching of linguistic markers of stance rather than traditional grammar only. It also recommends raising of awareness of the students on the institutional/social practices in relation to the construction of the PhD thesis, such as the norms and conventions of the discourse community.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:727251 |
| Date | January 2017 |
| Creators | Uba, Sani Yantandu |
| Contributors | Baynham, Mike |
| Publisher | University of Leeds |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://etheses.whiterose.ac.uk/18754/ |
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