University of Waterloo >
Electronic Theses and Dissertations (UW) >
Please use this identifier to cite or link to this item:
|Title: ||Identification of epistemic topoi in a corpus of biomedical research articles|
|Authors: ||Gladkova, Olga|
|Keywords: ||biomedical research articles|
linguistic and semantic configurations
situated analysis of text and discourse
|Approved Date: ||24-Jan-2011 |
|Date Submitted: ||10-Dec-2010 |
|Abstract: ||This dissertation reports on the results of a study into the characteristics of epistemic topoi and the methods of their identification in a corpus of biomedical publications. The study was conceived in response to the need for a systematized description of the organization of argumentative text and discourse. This need is well recognized in knowledge-intensive fields: information processing, storage, and retrieval; corpus analysis and natural language processing; data mining, knowledge management and translation; professional training and education.
The study followed the design of a situated study combined with a methodological inquiry. I used inductive methods to describe the features and functions of recurrent patterns of argumentative and linguistic organization. This part of the study consisted in close reading of a corpus of fifty-five NTG papers and rhetorical and linguistic annotation of seventeen clinical studies (45,599 words) selected from the corpus. The data was generated by means of rhetorical and linguistic analysis. Visual annotation played an essential role in the identification and description of the argumentative patterns, complementing the traditional methods of corpus analysis.
Forty-eight basic and nine composite epistemic topoi forming the superstructure of the papers were identified in the corpus. The topoi were found to be loosely associated with the IMRD structure and signalled with configurations of lexicogrammatical, semantic, deictic, and coreferential features. The topoi were classified according to the modes of reasoning and textual and discursive functions. The obtained results confirmed earlier insights into the links of linguistic patterning with text and discourse semantics. A significant outcome of the linguistic analysis is a catalogue of linguistic features that were found to have regular links with the topoi in the corpus.
The role of linguistic configurations as identifiers of argumentative meanings makes them a valuable medium of text and discourse analysis. By linking the argumentative meanings to the surface features of text and discourse, the analysis of linguistic configurations presents informatics practitioners with an alternative to the current methods of natural language processing and knowledge management. The catalogue of linguistic features and a detailed description of the study design make the presented findings amenable to secondary analysis, extrapolation, and generalization.
The auxiliary objectives of this study were a survey of argumentative practices represented in the corpus and a review of the state of epistemic research. The results of the survey and review suggest that agonistic reasoning practices and over-reliance on reductionist models have negative implications for research writing and communication. Specifically, they hamper analysis of argumentative organization of natural text and discourse. As an alternative to agonistic argumentation, I propose an argumentation model based on Aristotle’s and Kneale’s conceptions of situated knowledge and learning. The model of textual and discursive organization that accommodates situated knowledge and learning is political stasis. This model can be used as a heuristic and analytic tool. In this dissertation I use it as an explanatory conception and as a system of reference points for identifying significant research trends both in argumentation studies and in clinical NTG research.|
|Department: ||English Language and Literature|
|Degree: ||Doctor of Philosophy|
|Appears in Collections:||Faculty of Arts Theses and Dissertations |
Electronic Theses and Dissertations (UW)
All items in UWSpace are protected by copyright, with all rights reserved.