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|a Corpus-informed research and learning in ESP :
|b issues and applications /
|c edited by Alex Boulton, Shirley Carter-Thomas, Elizabeth Rowley-Jolivet.
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260 |
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|a Amsterdam ;
|a Philadelphia :
|b John Benjamins Pub. Co.,
|c 2012.
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300 |
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|a 1 online resource (316 pages).
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|a Studies in corpus linguistics ;
|v v. 52
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|a Includes bibliographical references and indexes.
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|a Corpus-Informed Research and Learning in ESP; Editorial page; Title page; LCC data; Table of contents; Preface; References; Issues in Corpus-Informed Research and Learning in ESP; 1. Introduction; 2. Overview of the volume; 3. ESP corpora for language research; 4. ESP corpora for genre-based approaches; 5. ESP corpora for language teaching and learning; 6. Perspectives; References; Part I ESP corpora for language research; From text to corpus; 1. Introduction; 2. Academic corpora and language learning: Combining quantitative and qualitative approaches; 3. Corpus and methodology.
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|a 3.1 Methodology: From individual RAs ... 3.2 ... to corpus examples; 4. The author's voice: Author roles and the CARS model; 4.1 Learning from a single article; 4.2 'Multicontextual learning': The contribution of corpus data; 4.2.1 Quantitative data; 4.2.2 Verbs and moves: Three author roles; 4.3 First person singular and plural in the English and French single-authored articles; 5. Pedagogical applications; 6. Conclusion; References; Appendix A. French model introduction; Appendix B. English model introduction; Appendix C. Studying author roles using a concordance.
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|a Phraseological patterns in a large corpus of biomedical articles1. Introduction; 1.1 Biomedical articles and phraseology; 1.2 Objectives; 1.3 Article structure and phraseological patterns; 2. Methodology; 2.1 Corpus compilation; 2.2 Analysis of the LBC; 2.3 Distributional analysis of salient nouns and verbs; 3. Phraseological patterns in the LBC; 3.1 Preferred wordings; 3.2 Phraseological patterns in sub-corpus I; 3.3 Phraseological patterns in sub-corpus M; 3.3.1 Describing patient enrollment; 3.3.2 Presenting exclusion and inclusion criteria; 3.3.3 Describing randomization methods.
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|a 3.3.4 Introducing definitions3.3.5 Identifying end points; 3.3.6 Describing treatment or drug administration; 3.3.7 Describing ethical precautions; 3.3.8 Describing statistical methods; 3.4 Phraseological patterns in sub-corpus R; 3.4.1 Referring the reader to tables and figures; 3.4.2 Reporting observations; 3.4.3. Signaling changes from baseline situation; 3.4.4 Making comparisons; 3.4.5 Describing events in the follow-up period; 3.5 Phraseological patterns in sub-corpus D; 3.5.1 Checking consistency with previous studies; 3.5.2 Signaling improvements in patients' health.
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|a 3.5.3 Mentioning the need for further research3.5.4 Describing limitations; 3.5.5 Hedging conclusions; 4. Conclusion; References; Appendix A. Keyword relative frequencies in subcorpora I, M, R & D; Appendix B. Section-specific salient words (SSSWs) in sub-corpora I, M, R & D; A corpus-based study of adjectival vs nominal modification in medical English; 1. Introduction; 2. Relational adjectives or denominal adjectives?; 2.1 Morphological features; 2.2 Syntactic features; 2.2.1 Non-attributiveness; 2.2.2 Non-gradability; 2.3 Semantic features.
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|a 3. Terminological uses of denominal adjectives in medicine.
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|a These specially-commissioned studies cover corpus-informed approaches to researching, teaching and learning English for Specific Purposes (ESP). The corpora used range from very large published corpora to small tailor-made collections of written and spoken text, as well as parallel and contrastive corpora, in both the hard and softer sciences. Designed to tackle the problems faced by a variety of first- and second-language ESP users (specialised translators, undergraduates, junior and experienced researchers, and language trainers), the breadth of approaches enables treatment of issues central.
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|t Corpus-Informed Research and Learning in ESP : Issues and applications.
|d Amsterdam/Philadelphia : John Benjamins Publishing Company, ©2012
|z 9789027203571
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830 |
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