Empirical research is carried out in a cyclic way: approaching a research area bottom-up, data lead to interpretations and ideally to the abstraction of laws, on the basis of which a theory can be derived. Deductive research is based on a theory, on the basis of which hypotheses can be formulated and tested against the background of empirical data. Looking at the state-of-the-art in translation studies, either theories as well as models are designed or empirical data are collected and interpreted. However, the final step is still lacking: so far, empirical data has not lead to the formulation of theories or models, whereas existing theories and models have not yet been comprehensively tested with empirical methods. This publication addresses these issues from several perspectives: multi-method product- as well as process-based research may gain insights into translation as well as interpreting phenomena. These phenomena may include cognitive and organizational processes, procedures and strategies, competence and performance, translation properties and universals, etc. Empirical findings about the deeper structures of translation and interpreting will reduce the gap between translation and interpreting practice and model and theory building. Furthermore, the availability of more large-scale empirical testing triggers the development of models and theories concerning translation and interpreting phenomena and behavior based on quantifiable, replicable and transparent data.
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Silvia Hansen-Schirra, Dipl.-\xDCbers., Dr. phil., PD, is a full professor of English linguistics and translation studies at Johannes Gutenberg University Mainz in Germersheim, Germany. Her main research interests include specialized communication, text comprehensibility, post-editing, translation process and competence research. As fellow of the Gutenberg Research College she is the director of the Translation & Cognition (TRACO) Center in Germersheim and co-editor of the online book series "Translation and Multilingual Natural Language Processing.
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