English language Morphological Neologisms Reflecting the War in Ukraine
Bibliographic record
Abstract
The aim of this article is to consider English morphological neologisms based on English-language postmodern Ukrainean literary texts. The ways of neologisms formation and their appearance in the language are described. The uses of general theoretical and specific theoretical and empirical research methods system include a description of neologisms, appearing in the English language in the realities of large-scale military aggression in Ukraine, in the context of general issues of linguistic neology. The theoretical significance of the study consists in the analysis of morphological neologisms in terms of postmodern perception. As a result, new speech units of the English language emerge in postmodern literary texts as a result of the war in Ukraine. As the war in Ukraine has acquired global significance for the whole civilized world, the postmodern literary texts ceases to be sectoral and falls into the general discourse. New lexemes are formed, objectifying the modern reality and becoming trendy for society. The paper aim is to analyse the reasons for the formation of war concerned neologisms as well as to investigate their semantically emotive component and pejorative connotations. The methodology included analysis of scientific sources, information search of scientific literature, description, deduction, induction, and continuous sampling method. The results of the study show that during the war in Ukraine, new lexical units emerge and consolidate in the English language. A special characteristic of the sample of neologisms is their emotionality. This can be explained by the proper coverage of the course of the war, where the genocide of the Ukrainian nation takes place and accordingly evokes a spectrum of negative emotions. Morphological neologisms in English have become common due to the catastrophic and global nature of the war in Ukraine. These linguistic neologisms need terminological unification, but the rapid development of events in Ukraine makes it difficult to codify these changes and requires permanent work and research. The study is based on lexicology as a science that studies words, but with special attention to neologisms. Neologisms are more than a code, they are elements of identity that describe a period of conflict and remain a reflection, if not a testimony, of all the atrocities suffered by the population during the war.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".