Evaluation in experimental research articles

This thesis examines evaluation in experimental research articles in terms of the meanings made and their contribution to the organisation of the articles. After an introduction to the phenomenon of evaluation in Chapter 1, Chapter 2 surveys recent work concerning the process of scientific discovery and the writing of research articles. Chapter 3 returns to evaluation and its place in various theories of discourse, mainly those of Sinclair and of Halliday. The model of evaluation proposed in this thesis is set out in the next three chapters, dealing in turn with the Status, Value and Relevance functions of evaluation. Status is the function of evaluation which bestows entity, assessing along a certain-uncertain parameter. Value bestows quality and assesses along a good-bad parameter. Evaluation of Relevance is meta-discoursal and marks significance. Relevance Markers are identified, which progressively chunk and organise the text. Comparisons between texts analysed for Status, Value and Relevance demonstrate a movement towards the theoretical and an increase in complexity of argument as the sub-discipline under discussion progresses. Chapter 7 investigates the contribution of evaluation towards text structure and notes a number of ways in which discourse units in experimental research articles may be organised. The concluding chapter, Chapter 8, discusses some of the practical and theoretical implications of the work described in the thesis. The Appendix contains the research articles which comprise the corpus

A linguistic ethnography of theatre production

Voices and Practices in Applied Linguistics comprises a selection of original applied linguistics-based research on the theme of the diversity of Applied Linguistics and in Applied Linguistics. It is a unique collection of reflections and cutting-edge research relating to academic, policy and professional fields of Applied Linguistics, featuring chapters written by founders of the field, established researchers, and rising stars. This accessible, eclectic and forward-looking volume is significant both for research and practice. It highlights current globalised perspectives on diversity in language use and communication, across a variety of contexts, and with a rich mix of frameworks, methodologies and participants. Compiled and edited by a team of academic experts in the field, this edited collection will be of interest to established and emerging researchers in Applied Linguistics globally. It will also be relevant to language professionals, practitioners, and policy makers. The volume draws together papers from the 2017 British Association for Applied Linguistics (BAAL) conference, marking the 50th anniversary of its inaugural meeting. Founded in the mid-1960s, this UK-based professional association provides a forum for Applied Linguistics and its annual meeting brings together researchers and language professionals from across this field

Introduction. Converging ways of applying corpus linguistics

Corpus analysis is an area of research that has broadened the scope of a number of different fields of language analysis. One aspect of this research is quantitative. For more than sixty years, linguists have demonstrated that language features can be counted and frequencies calculated, and that these data are useful for the interpretation and understanding of language. For this reason, corpus analysis has been used in several fields of knowledge to support or challenge hypotheses and theories. In this volume our intention is to show that corpus analysis not only deals with a large amount of numbers and quantities, it also comprises studies that consider both quantitative and qualitative analysis.Carrió Pastor, ML.; Hunston, S. (2012). Introduction. Converging ways of applying corpus linguistics. Revista Española de Lingüística Aplicada. 25(1):11-14. http://hdl.handle.net/10251/78184S111425

Multi-dimensional analysis, text constellations, and interdisciplinary discourse

Multi-Dimensional Analysis (MDA) has been widely used to explore register variation. This paper reports on a project using MDA to explore the features of an interdisciplinary academic domain. Six dimensions of variation are identified in a corpus of 11,000 journal articles in environmental studies. We then focus on articles in one interdisciplinary journal, Global Environmental Change (GEC). It is expected that they will diverge sufficiently to produce differences that are analogous to register differences. Instead of identifying these “registers” on external criteria, we use the dimensional profiles of individual texts to identify ‘constellations’ of texts sharing combinations of features. Six such constellations are derived, consisting of texts with commonalities in their approaches to research: the development of predictive models; quantitative research; discussions of theory and policy; and human-environment studies focusing on individual voices. The identification of these constellations could not have been achieved through an a priori categorisation of texts

'What is this corpus about?': Using topic modelling to explore a specialised corpus

This paper introduces topic modelling, a machine learning technique that automatically identifies 'topics' in a given corpus. The paper illustrates its use in the exploration of a corpus of academic English. It first offers the intuitive explanation of the underlying mechanism of topic modelling and describes the procedure for building a model, including the decisions involved in the model-building process. The paper then explores the model. A topic in topic models is characterised by a set of co-occurring words, and we will demonstrate that such topics bring us rich insights into the nature of a corpus. As exemplary tasks, this paper identifies the prominent topics in different parts of papers, investigates the chronological change of a journal, and reveals different types of papers in the journal. The paper further compares topic modelling to two more traditional techniques in corpus linguistics, semantic annotation and keywords analysis, and highlights the strengths of topic modelling.We believe that topic modelling is particularly useful in the initial exploration of a corpus