The anthropocosmic vector of modern Pedagogy and Linguistics requires development of such tools for future translators that enable as quick as possible processing of huge amounts of information with production of automatically determined frequencies, on the one hand. On the other hand, it demands minimization of the subjective influence of an individual researcher on the received results, giving a chance for detecting and analysing linguistic phenomena unnoticed earlier. Linguistic corpora are a state-of-the-art technology that can solve the outlined problem perfectly, for it opens a broad variety of practical and theoretical research options, and at the same time it is a didactic tool fulfilling purely didactic, cognitive, informative, formative, and testing / checking functions. Therefore, the use of linguistic corpora technology can be considered from two perspectives – learning to use corpora to translate and learning to translate using corpora. Corpora technology employment can enhance both objectivity and reliability of the results researchers obtain when processing language data, too. The application of corpus approach by translators-to-be gives an opportunity to study any language units in different speech genres in different types of discourse, as well as in various contexts in the corpus, without being hindered by the specificity of the studied linguistic unit. Translation students can search for discrete lexical / grammatical units, based on concordances, showing their functioning in different styles and areas of use. Moreover, parallel corpora provide ready solutions for the choice of translation models in certain conditions. The purpose of this article, stipulated by the relevance of the set problem, as well as the lack of ready parallel corpora in Ukraine, covers development of special methodological procedures and exercises for future translators aimed at their mastering of corpus technology as a didactic tool. The paper also describes several technological solutions (Multiconcord, BNC, parallel corpus), which provide the possibilities of such a corpus approach in practice for teaching-learning translators-to-be. In conclusions it is stressed that mastering such linguistic corpora technology at the university is very important for future translators, with a corpus being a useful and convenient didactic tool in their professional area. The prospects for further research can be seen in the development of a set of exercises consolidating future translators’ abilities to successfully process different corpora data.
The paper offers a new complex methodology for analyzing the linguocultural concept HUMAN AGE as a multidimensional archetypal and stereotypical mental structure of human consciousness. To recognize the systemic essence of the Ukrainian, Russian, and English native speakers’ world mapping and their cultural stereotypes, the concept HUMAN AGE is studied by considering its realization through lexical, phraseological, and paremiological units. The study assumes the analysis of such concept structure components as an etymological/historical layer that reflects the essential notional features of the concept, an additional layer, formed as a result of the concept in growth, and an active layer that is regarded relevant for the modern native speakers and represented by axio-notional, axio-figurative, and axio-evaluative stereotypes that help forward mentalizing the concept in the Ukrainian, Russian, and English native speakers’ consciousness. The archetypal basis of the concept is identified by considering the etymology of the concept names and nominations of age stages and persons by age in the three languages. The stages of stereotyping the axio-notional, axio-figurative, and axio-evaluative images of the human age that reveal the similarities (universal features) and differences (nationally specific features) in the mapping of archetypal and stereotypical images of the human age in the consciousness of Ukrainians, Russians, and the English are analyzed. Ultimately, the most complete set of archetypal and symbolic features (universal and nationally specific), sociocultural age stereotypes (neutral, positive, and negative), numerological, coloristic, phytomorphic, and zoomorphic metaphorical nominations of age stages and persons by age in Ukrainian, Russian, and English linguocultures is presented.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.