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dc.contributorFaculty of Humanitiesen_US
dc.contributor.advisorHuang, Chu-ren (CBS)en_US
dc.creatorWang, Xiaowen-
dc.publisherHong Kong Polytechnic Universityen_US
dc.rightsAll rights reserveden_US
dc.titleIntratextual generic construction of research paradigms in scientific explanation : a corpus-based computational analysis of post-results sections in clinical research articlesen_US
dcterms.abstractClinical research is a sub-type of medical research that provides the best evidence for clinical practices. It can be divided into two empirical research paradigms based on the methodological nature of research: observational and experimental. The former evaluates the direct impacts of clinical interventions for treating or preventing diseases, while the latter observes the potential associations between exposure and outcome of diseases without assigning interventions to patients. While this is a fundamental paradigmatic dichotomy in the evidence-based medical study, how scientific explanation is discursively constructed in the two paradigms is an important issue that has not been investigated in previous analyses of the genre of medical research articles. This study takes a corpus-based computational approach to systematically compare the post-results sections of clinical research articles (CRAs) that belong to the experimental and observational paradigms. The post-results sections include the discussion and conclusion sections in a CRA, and the investigation into this genre part aims to explore the influence of empirical research paradigms on the intratextual generic construction of scientific explanation. A corpus of randomly selected English-medium CRAs in reproductive medicine published in academic medical journals within the recent ten years (2009-2019) was compiled, and two sub-corpora – EXP_MAIN, composed of 49 non-protocol experimental CRAs and OBS_MAIN, composed of 49 non-protocol observational CRAs – were annotated and analyzed at multi-layers for the post-results sections.en_US
dcterms.abstractAdapted from Wang et al.'s (2014) and Bhatia's (2017) frameworks for generic variation, the theoretical framework for this study complements Bhatia's (2002a, 2004, 2017) multi-dimensional genre models by drawing on Hyland's (2005) model of interactional metadiscourse. Following this framework, comparative analyses were carried out on the planes of genre, metadiscourse, and text. On the plane of genre, the distribution of moves and steps in the post-results sections exhibited paradigmatic differences. On the plane of text, the two research paradigms diverged morpho-syntactically and lexical-semantically, although they were similar in most syntactic and lexical complexity indices (Ai & Lu, 2010; Lu, 2010, 2012). On the plane of tenor, the two research paradigms markedly differed in the distribution of boosters and hedges, and the correlations between boosters and hedges. Finally, paradigmatic classifications were conducted with machine learning methods. Various linguistic features on the three planes were identified as useful predictor variables to classify the post-results section texts in EXP_MAIN and OBS_MAIN into experimental and observational classes; however, the integration of them produced the best performance, with an accuracy of 90.82%. In all, the study proves that the experimental paradigm, which focuses on hypothesis-proving, and the observational paradigm, which focuses on fact-discovery, differ in their intratextual generic construction, reflecting differences in the nature of the experimental and observational studies. Particularly, generic intratextuality plays an important role in the generic construction of research paradigms in scientific explanation, with different patterns on all the three planes that have been investigated. Taking a bird's view, these features interact in different ways, reflecting that the experimental paradigm takes a hypothetico-deductive mode of reasoning and the fact-discovery observational paradigm tends to be inductive-oriented in the mode of reasoning.en_US
dcterms.extentxvii, 380 pages : color illustrationsen_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.educationalLevelAll Doctorateen_US
dcterms.LCSHClinical medicine -- Researchen_US
dcterms.LCSHComputational linguisticsen_US
dcterms.LCSHDiscourse analysis -- Data processingen_US
dcterms.LCSHCommunication in medicineen_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.accessRightsrestricted accessen_US

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