Methodological cross-fertilization: empirical methodologies in (computational) linguistics and translation studies

Recent years have seen attempts at improving empirical methodologies in contrastive linguistics and in translation studies through interdisciplinary collaboration with multi-layer corpus architectures in computational linguistics. At the same time, explanatory background for empirical results is increasingly sought in more sophisticated models of language contact in typologically based contrastive linguistics on the one hand, and in language processing in situations of multilinguality, including translation, on the other. Three attempts are discussed to narrow the significant gap between the high level of abstraction of such models, and data provided through shallow analysis and annotation of electronic corpora. The first of these operationalizes the high level terms “explicitness/ explicitation” in terms of lexicogrammatical data available in a contrastive corpus, treating them as dependent variables and attempting to explain their variation in terms of the independent variables controlled for in the corpus architecture. The second attempt starts from the same corpus architecture, yet includes annotations about textual cohesion in its operationalizations and develops increasingly fine-grained hypotheses to limit search space and variation between independent and dependent variables so as to get closer to causal explanations rather than explanations in terms of co-variation . The third attempt intersects corpus data of the type outlined before with data from processing studies, aiming at an integration and mutual explanation of product and process data. Our focus here is on methodological issues involved in integrating data of such different types and granularity in an overall empirical research architecture.