Argumentative meanings and their stylistic configurations in clinical research publications

References

• Aristotle. (1924). Rhetorica (W. R. Roberts, Trans.). In W. D. Ross (Ed.), The works of Aristotle (Vol. IX). Oxford: Clarendon Press. Retrieved from Scholars Portal, University of Waterloo. (Original work published in the 4th cent. BCE.).
   Google Scholar
• Association for Computational Linguistics. (2014). Proceedings of the First Workshop on Argumentation Mining (N. Green, K. Ashley, D. Litman, C. Reed, & V. Walker, Org.). Baltimore, MD. Retrieved from http://acl2014.org/acl2014/W14-21/index.html
   Google Scholar
• Berry, R. (2005). Making the most of metalanguage. Language Awareness, 14(1), 3–20. doi: 10.1080/09658410508668817
   Google Scholar
• Biber, D., Csomay, E., Jones, J. K., & Keck, C. (2004). A corpus linguistics investigation of Vocabulary-based Discourse Units in university registers. In U. Connor & T. A. Upton (Eds.), Applied corpus linguistics: A multidimensional approach (pp. 53–72). Amsterdam, NY: Rodopi.
   Google Scholar
• Brown, J. D. (2004). Research methods for applied linguistics: Scope, characteristics, and standards. In A. Davies & C. Elder (Eds. & Intr.), The handbook of applied linguistics (pp. 476–500). Oxford: Blackwell Publishing.
   Google Scholar
• Channell, J. (1990). Precise and vague quantities in academic writing. In W. Nash (Ed. & Intr.), The writing scholar: Studies in academic discourse (pp. 95–117). Newbury Park, CA: Sage.
   Google Scholar
• Connelly, D. P., & Johnson, P. E. (1980). The medical problem solving process. Human Pathology, 11(5), 412–419. doi: 10.1016/S0046-8177(80)80048-7
   PubMed Web of Science ®Google Scholar
• Crismore, A., & Farnsworth, R. (1990). Metadiscourse in popular and professional science discourse. In W. Nash (Ed.), The writing scholar: Studies in academic discourse (pp. 118–136). Newbury Park, CA: Sage.
   Google Scholar
• Crosswhite, J.. (2000). Rhetoric and computation. In C.A. Reed and T. Norman (Eds.). Symposium on Argument and Computation: position papers. Retrieved from http://www.csd.abdn.ac.uk/~tnorman/sac/ (As cited in Grasso, 2002).
   Google Scholar
• De Beaugrande, R. (1997). Linguistic theory: The discourse of fundamental works. New York: Longman Routledge.
   Google Scholar
• Fahnestock, J. (1999). Rhetorical figures in scientific argumentation. New York, NY: Oxford University Press.
   Google Scholar
• Gawryjolek, J., DiMarco, C., & Harris, R. A. (2009, July). An annotation tool for automatically detecting rhetorical figures. Paper presented at CMNA (Computational Models of Natural Argument), 13 July 2009, Pasadena, CA.
   Google Scholar
• Gladkova, O. (2010). The identification of epistemic topoi in a corpus of biomedical research articles (Unpublished dissertation). University of Waterloo. Retrieved from ResearchGate.
   Google Scholar
• Grasso, F. (2002, 4–6 September). Towards a framework for rhetorical argumentation. In J. Bos, M. E. Foster, & C. Matheson (Eds.), EDILOG 2002 – Proceedings of the 6th Workshop on the Semantics and Pragmatics of Dialogue (pp. 53–60), Edinburgh, UK.
   Google Scholar
• Green, N. L. (2010). Representation of argumentation in text with rhetorical structure theory. Argumentation, 24(2), 181–196. doi: 10.1007/s10503-009-9169-4
   Web of Science ®Google Scholar
• Green, N. L. (2012). Argumentation and risk communication about genetic testing – Challenges for healthcare consumers and implications for computer systems. Journal of Argumentation in Context, 1(1), 113–129. doi: 10.1075/jaic.1.1.09gre
   Google Scholar
• Green, N., Dwight, R., Navoraphan, K., & Stadler, B. (2011). Natural language generation of biomedical argumentation for lay audiences. Argument and Computation, 2(1), 23–50. doi: 10.1080/19462166.2010.515037
   Google Scholar
• Guo, Y., Silins, I., Stenius, U., & Korhonen, A. (2013). Active learning-based information structure analysis of full scientific articles and two applications for biomedical literature review. Bioinformatics, 29, 1440–1447. doi: 10.1093/bioinformatics/btt163
   PubMed Web of Science ®Google Scholar
• Halliday, M. A. K. (1994). An introduction to functional grammar (2nd ed.). London: Edward Arnold.
   Google Scholar
• Halliday, M. A. K., & Hasan, R. (1976). Cohesion in English. London: Longman.
   Google Scholar
• Harmsze, F.-A. P., & Kircz, J. G. (1998, 23–25 April). Form and content in the electronic age. In C. S. Nielsen & J. R. Herkert (Eds.), Socioeconomic dimensions of electronic publishing workshop proceedings: Meeting the needs of the engineering and scientific communities, Santa Barbara, CA, USA (pp. 43–49). Piscataway, NJ: Institute of Electrical and Electronics Engineers.
   Google Scholar
• Harris, R. A., & DiMarco, C. (2009, 8 April). Constructing a rhetorical figuration ontology. In J. Masthoff & F. Grasso (Chairs), AISB (Artificial Intelligence and Simulation of Behaviour), Edinburgh, Scotland (pp. 47–52). Symposium of the Society for the Study of Artificial Intelligence and the Simulation of Behaviour, Edinburgh.
   Google Scholar
• Hersh, W. R. (2009). Information retrieval: A health and biomedical perspective (3rd ed.). New York, NY: Springer Verlag.
   Google Scholar
• Huseman, R. C. (1994). Aristotle’s system of topics. In E. Schiappa (Ed.), Landmark essays on classical Greek Rhetoric (pp. 191–199). Davis, CA: Hermagoras.
   Google Scholar
• Hyland, K. (2005). Metadiscourse: Exploring interaction in writing. London: Continuum.
   Google Scholar
• Ide, N., & Romary, L. (2004). International standard for a linguistic annotation framework. Natural Language Engineering, 10(3/4), 211–225. doi: 10.1017/S135132490400350X
   Google Scholar
• Kneale, W. C. (1949). Probability and induction. Oxford: Clarendon Press.
   Google Scholar
• Kumpf, E. P. (2000). Visual metadiscourse: Designing the considerate text. Technical Communication Quarterly, 9(4), 401–424. doi: 10.1080/10572250009364707
   Google Scholar
• Lazaraton, A. (2002). Quantitative and qualitative approaches to discourse analysis. Annual Review of Applied Linguistics, 22, 32–51. doi: 10.1017/S0267190502000028
   Google Scholar
• Levene, R. (1980). Low tension glaucoma: A critical review and new material. Survey of Ophthalmology, 24(6), 621–664. doi: 10.1016/0039-6257(80)90123-X
   PubMed Web of Science ®Google Scholar
• Liakata, M., Thompson, P., de Waard, A., Nawaz, R., Maat, H. P., & Ananiadou, S. (2012). A three-way perspective on scientific discourse annotation for knowledge extraction. In Proceedings of the Workshop on Detecting Structure in Scholarly Discourse (pp. 37–46). Association for Computational Linguistics.
   Google Scholar
• Liddy, E. D. (1991). The discourse-level structure of empirical abstracts: An exploratory study. Information Processing and Management, 27(1), 55–81. doi: 10.1016/0306-4573(91)90031-G
   Web of Science ®Google Scholar
• Litman, D. J. (1996). Cue phrase classification using machine learning. Journal of Artificial Intelligence Research, 5, 53–94.
   Web of Science ®Google Scholar
• Malcolm, L. (1987). What rules govern tense usage in scientific articles? English for Specific Purposes, 6, 31–43. doi: 10.1016/0889-4906(87)90073-1
   Google Scholar
• Moens, M.-F., Boiy, E., Palau, R. M., & Reed, C. (2007, 4–8 June). Automatic detection of arguments in legal texts. The Eleventh International Conference on AI and Law, Stanford, CA, USA, 4–8 June, 2007.
   Google Scholar
• Myers, G. (1992). ‘In this paper we report … ’: Speech acts and scientific facts. Journal of Pragmatics, 17(4), 295–313. doi: 10.1016/0378-2166(92)90013-2
   Web of Science ®Google Scholar
• Paice, C. D. (1990). Constructing literature abstracts by computer: Techniques and prospects. Information Processing and Management, 26, 171–186. doi: 10.1016/0306-4573(90)90014-S
   Web of Science ®Google Scholar
• Palau, R. M., & Moens, M. (2009). Argumentation mining: The detection, classification and structure of arguments in text. In C. D. Hafner (Ed.), Proceedings of the 12th International Conference on Artificial Intelligence and Law, Barcelona, Spain (pp. 98–107). New York: ACM Press.
   Google Scholar
• Reed, C. (2010). Walton's theory of argument and its impact on computational models. In C. Reed and C. W. Tindale (Eds.), Dialectics, dialogue and argumentation (pp. 73–84). London: College Publications.
   Google Scholar
• Saint-Dizier, P. (2012). Processing natural language arguments with the <TextCoop> platform. Argument and Computation, 3(1), 49–82. doi: 10.1080/19462166.2012.663539
   Google Scholar
• Salager-Meyer, F. (1994). Hedges and textual communicative function in medical English written discourse. English for Specific Purposes, 13(2), 149–170. doi: 10.1016/0889-4906(94)90013-2
   Google Scholar
• Spinoza, B. (2007). Ethics demonstrated in geometrical order (J. F. Bennett, Trans.). Retrieved from http://www.earlymoderntexts.com/sp.html (Original work published in 1677.)
   Google Scholar
• Stannard, J. (1965). The presocratic origin of explanatory method. The Philosophical Quarterly, 15(60), 193–206. doi: 10.2307/2217596
   Google Scholar
• Stirling, L., Fletcher, J., Mushin, I., & Wales, R. (2001). Representational issues in annotation: Using the Australian map task corpus to relate prosody and discourse structure. Speech Communication, 33, 113–134. doi: 10.1016/S0167-6393(00)00072-8
   Web of Science ®Google Scholar
• Strong, P. M. (1988). Minor courtesies and macro structures. In P. Drew & A. Wootton (Eds.), Erving Goffman: Exploring the interaction order (pp. 228–249). Oxford: Northeastern University Press.
   Google Scholar
• Swales, J. (1990). Genre analysis: English in academic and research settings. Cambridge: Cambridge University.
   Google Scholar
• Swales, J. (2004). Research genres: Exploration and applications. Cambridge: Cambridge University.
   Google Scholar
• Taboada, M. (2009). Implicit and explicit coherence relations. In J. Renkema (Ed.), Discourse, of course: An overview of research in discourse studies (pp. 127–140). Amsterdam: John Benjamins.
   Google Scholar
• Teufel, S. (1999). Argumentative zoning: Information extraction from scientific articles (Unpublished dissertation). University of Edinburgh. Retrieved January 20, 2007, from http://www.cl.cam.ac.uk/~sht25/thesis/t.pdf
   Google Scholar
• Teufel, S. (2010). The Structure of scientific articles: Applications to citation indexing and summarization. Stanford, CA: CSLI Publications.
   Google Scholar
• Teufel, S. (2014). Scientific argumentation detection as limited-domain intention recognition. In E. Cabrio, S. Villata, & A. Wyner (Eds.), ArgNLP 2014: Frontiers and connections between argumentation theory and natural language processing. Proceedings of the Workshop on Frontiers and Connections between Argumentation Theory and Natural Language Processing. CEUR-WS.
   Google Scholar
• Thompson, D. K. (1993). Arguing for experimental ‘facts’ in science: A study of research article results sections in biochemistry. Written Communication, 10(1), 106–128. doi: 10.1177/0741088393010001004
   Web of Science ®Google Scholar
• Thompson, S. E. (2003). Text-structuring metadiscourse, intonation and the signalling of organisation in academic lectures. Journal of English for Academic Purposes, 2(1), 5–20. doi: 10.1016/S1475-1585(02)00036-X
   Google Scholar
• Trawiński, B. (1989). A methodology for writing problem-structured abstracts. Information Processing and Management, 25(6), 693–702. doi: 10.1016/0306-4573(89)90102-7
   Web of Science ®Google Scholar
• Van Dijk, T. A. (1980). Macrostructures: An interdisciplinary study of global structures in discourse, interaction and cognition. Hillsdale, NJ: Lawrence Erlbaum.
   Google Scholar
• Walton, D. (2009). Enthymemes and argumentation schemes in health product ads. CMNA IX, Computational Models of Natural Argument Workshop, Pasadena, 13 July 2009
   Google Scholar
• Wilbur, W. J., Rzhetsky, A., & Shatkay, H. (2006). New directions in biomedical text annotation: Definitions, guidelines and corpus construction. BMC Bioinformatics, 7, 356–365. doi: 10.1186/1471-2105-7-356
   PubMed Web of Science ®Google Scholar
• Willard, C. (1989). A theory of argumentation. Tuscaloosa: University of Alabama Press.
   Google Scholar
• Wyner, A., Mochales-Palau, R., Moens, M., & Milward, D. (2010). Approaches to text mining arguments from legal cases. In E. Francesconi, S. Montemagni, W. Peters, & D. Tiscornia (Eds.), Semantic processing of legal texts (pp. 60–79). No. 6036 in Lecture notes in Computer Science. Berlin: Springer.
   Google Scholar