A corpus-based study of the ADJ-looking adjectivization in English

This article aims to conduct a corpus-based study of the diachronic and synchronic distributions of a special type of participle adjectivization, the ADJ-looking adjectivization. The study based on the Corpus of Historical American English (COHA) finds that this process of adjectivization consists of two phases: (1) The downward rank-shift from the look ADJ construction to the ADJ looking adjectivization is a process of metaphorization; (2) The transcategorization from the ADJ looking adjectivization to the ADJ-looking adjectivization is a process of lexicalization. The study based on the Corpus of Contemporary American English (COCA) finds that ADJ-looking adjectivizations are mode and register sensitive but not discipline sensitive. The modifier use prefers to occur more in hard science texts to increase the complexity of nominal groups and the predicative use prefers to occur more in soft science texts to increase the grammatical intricacy of sentences. The reason for the non-sensitivity across disciplines is that evaluative adjectives tend to occur in neither soft nor hard science texts.

Functional and stylistic types of special vocabulary in scientific and technical texts (based on English and German aviation vocabulary)

The article is devoted to the consideration of the typology of special vocabulary in the modern language of technology and the study of the proportion of functional and stylistic types of special lexical units (terms, nomens, pragmonyms, terminoids, professionalisms) in scientific and technical texts of various genres. To study the ratio of the types of special vocabulary, popular scientific articles from aviation electronic journals, individual chapters of Ph.D. theses as well as fragments of aviation textbooks in English and German were analyzed. The total volume of the studied texts is 180, 000 characters (30,000 characters for each genre in one language). Based on this material, 2,426 English special lexical units and 2,465 German special lexical units were identified and distributed into separate categories. As a result of the study, it was found that the proportion of types of special vocabulary in scientific and technical texts of the corresponding genres in English and German is approximately the same. In all analyzed popular science, scientific and educational texts, the proportion of terms considerably prevails. The largest number of terms is used in educational texts. In popular science texts, nomens are used more often than in texts of other genres. Terminoids and professionalisms are very rarely used in the studied texts.

TOPIC SEGMENTATION METHODS COMPARISON ON COMPUTER SCIENCE TEXTS

The demand for the creation of information systems that simplifies and accelerates work has greatly increased in the context of the rapidinformatization of society and all its branches. It provokes the emergence of more and more companies involved in the development of softwareproducts and information systems in general. In order to ensure the systematization, processing and use of this knowledge, knowledge managementsystems are used. One of the main tasks of IT companies is continuous training of personnel. This requires export of the content from the company'sknowledge management system to the learning management system. The main goal of the research is to choose an algorithm that allows solving theproblem of marking up the text of articles close to those used in knowledge management systems of IT companies. To achieve this goal, it is necessaryto compare various topic segmentation methods on a dataset with a computer science texts. Inspec is one such dataset used for keyword extraction andin this research it has been adapted to the structure of the datasets used for the topic segmentation problem. The TextTiling and TextSeg methods wereused for comparison on some well-known data science metrics and specific metrics that relate to the topic segmentation problem. A new generalizedmetric was also introduced to compare the results for the topic segmentation problem. All software implementations of the algorithms were written inPython programming language and represent a set of interrelated functions. Results were obtained showing the advantages of the Text Seg method incomparison with TextTiling when compared using classical data science metrics and special metrics developed for the topic segmentation task. Fromall the metrics, including the introduced one it can be concluded that the TextSeg algorithm performs better than the TextTiling algorithm on theadapted Inspec test data set.

Resurrecting Science Education by Re-Inserting Women, Nature, and Complexity

The development of capitalism and then science over the last 500 years or so has produced a very specific way of organising the relations between humans and the rest of nature. Both depend on excluding—and “cheapening”—women, nature, and complexity. This chapter argues that surviving the crisis of the Anthropocene requires us to do the very difficult work of bringing these excluded categories back in to science and science education, at the conceptual level at which they are excluded. The case is made for deconstruction as a framework for envisaging—and resurrecting—science education for the Anthropocene. Drawing on the work of Luce Irigaray, the chapter outlines a pedagogy involving a three-level, deconstructive reading of science texts that is designed to open spaces for thinking “other”-wise. It argues that, in the current context, unlike business-as-usual science education, this approach is genuinely “educative.”

Identification of argumentative sentences in Russian scientific and popular science texts

In this study we analyze the applicability of specific machine learning algorithms to the task of detecting sentences containing argumentation in Russian text. We employ a collection of scientific and popular science texts with manually annotated argumentation to evaluate the quality of identifying argumentative sentences in terms of precision, recall, and F-measure. The experiment involves three algorithms: MNB, SVM, and MLP. The bag of words model is used for representing texts. Lemmas of words in analyzed sentences serve as features for the classification. We perform the automatic selection of informative features in accordance with Variance and χ2 criteria combined with the weight-based filtration of lemmas (via TF*IDF and EMI). The training set includes around 800 sentences, while the test set contains 180. The MNB algorithm demonstrates the highest F-measure and recall scores on almost all feature sets (maximal values reached equal 68.7% and 89% respectively), while the MLP algorithm shows the best precision for about half of feature selection variations (the maximal value is 72.5%).

BORROWINGS FROM THE POLISH LANGUAGE IN THE BELARUSIAN SCIENTIFIC LANGUAGE AT THE BEGINNING OF THE XX CENTURY

This article examines interaction specifics of the Belarusian and Polish languages in scientific texts at the beginning of the 20th century. On the basis of scientific and educational, popular science texts and lexicographic materials, the characteristics of polonisms, their subject and thematic affiliation, as well as the peculiarities of their formal adaptation on the Belarusian linguistic basis are carried out. The work uses descriptive, contrastive and comparative historical methods, which were useful during the examination of polonisms in Belarusian language. The author establishes the dependence of the interacting nature of contacting languages on various intralingual and external factors, which predetermined the nature of the interlanguage relations of the Belarusian and Polish languages at the beginning of the 20th century. For all the lexical inequality of scientific texts, their linguistic unity was formed due to a common goal – the transmission of scientific information. In general, the analysis showed that when borrowings from the Polish language are used in the texts of Belarusian science, there is no consistency. Accordingly, it can be stated that the influence of the Polish language on the Belarusian scientific language is not characterized by depth, and the language of Belarusian science at the beginning of the 20th century was not oversaturated with polonisms. This was probably facilitated by the tendencies of the Belarusian linguistic and cultural revival, the dominant of which was primarily the orientation towards national identity and, accordingly, the limitation of foreign linguistic influences.

Linguistic and Cultural Poetics of German Popular Science Texts (based on U. Stumpf’s “Kräuter: Gefährten am Wegesrand”) and Resultant Translation Challenges

The article examines several aspects of linguistic and cultural poetics of German popular science texts, which in many ways shape national and cultural specifics of such texts and thus influence the process of translating them into Russian. As a distinct hybrid, popular science texts are characterized by high information density, intertextuality, and a wide range of vocabulary and style. Popular science texts create a special information space in which national and cultural specifics play a significant role. The article presents the results of the linguistic, stylistic, and cultural analysis of the German popular science work on botany by W. Stumpf “Kräuter: Gefährten am Wegesrand,” The strongly marked linguistic and cultural poetics of this text is largely determined by the peculiarity of botany as a field of knowledge: namely the knowledge of herbs, based on discoveries of ancient botanists, on folk knowledge, and on the personal experience of the author. At the lexical level, the linguo-cultural specifics are most clearly manifested in the nominations of plants: etymologically interesting phytonyms, their synonymic chains, and lexical gaps identified in the translation process. As a cross between scientific, journalistic, and literary texts, popular science texts display features of all these styles, which also determines the density of their linguistic and cultural poetics. The article provides a translation of several passages into Russian in order to demonstrate some of the challenges in translating popular science texts while taking into account their national and cultural specifics. The results of the study can be used both in teaching German as a foreign language and in translation courses at all levels of general and professional education as well as in developing textbooks, thematic dictionaries, and botanical glossaries.

Models of representing an astronomer’s voice in a journalist’s popular judgment

Within the framework of this article, the starting point of the research is the theoretical position, according to which reports on discoveries and achievements in the field of astronomy appear as a frequency phenomenon, covered in specialized popular scientific texts. As a result, a pragmatic analysis of the source of information and ensuring access to the voices of astronomer researchers in a journalistic report is an urgent problem. The personality of the journalist acts as an intermediary between scientists and non-professional readers, whose knowledge of astronomy is limited, and the created popular science texts are a kind of communication platform for voicing the judgments that are put forward by representatives of the astronomical communities. In this regard, journalists not only supplement the reader’s knowledge in an accessible form, but also open access to the voices of representatives of the scientific and astronomical community, relying on such means as direct and indirect speech, which reveal different degrees of frequency in the first paragraph of the text and in the subsequent presentation. To systematize the actual data indicating the explicit labeling of the source of information in a popular science message, the most frequent language signals that are used by journalists in order to introduce a «foreign» voice into the text (predicates that introduce direct or indirect speech) are analyzed. As a result, models and indicators of their frequency were identified, this, in turn, provided an opportunity to trace the trends in voicing the expert astronomers’ opinions in a popular scientific text. It is established that the distribution of direct and indirect speech with explicit marking of the source of information in the first paragraph of the popular science text is not homogeneous. In this text segment, indirect speech is the most frequent, which allows the journalist to focus the reader’s attention on an unbiased vision of a scientific and astronomical event.