Lexical competition in Kazakh–Russian bilingual media: A corpus-based quantitative study
In recent years, corpus linguistics has provided new opportunities for studying language contact using quantitative and data-driven techniques. For the Kazakh language, situated in a multilingual setting involving Kazakh, Russian, and English, lexical interference represents an important sociolinguistic issue. This study investigates lexical competition from quantitative and functional standpoints, with particular attention to frequency, distribution, and variation in Kazakh-language mass media under Kazakh-Russian language contact. Using corpus methods, the study shows that large collections of texts make it possible to identify borrowed lexemes and competing equivalent forms. Borrowed items may coexist with native equivalents, producing measurable differences in frequency and stylistic preference. In some instances, foreign lexemes are more frequent than standardised national alternatives in the analysed corpus, although established Kazakh norms may continue to coexist with such borrowings. To address this issue, the study introduces the Lexical Competition Coefficient (LCC), a descriptive numerical indicator that measures the relative frequency of competing lexical equivalents in corpus data. When the Kazakh item predominates, the LCC exceeds one (k > 1), indicating that the Kazakh variant is more frequent in the corpus. By contrast, a coefficient below one (k < 1) indicates that the borrowed variant is more frequent. The findings indicate that lexical competition in Kazakh-language media is uneven across lexical pairs, with some borrowed forms substantially outnumbering Kazakh equivalents while other Kazakh variants remain dominant in corpus usage. The study combines scholarship on language contact and quantitative corpus analysis and proposes a systematic procedure for assessing lexical competition in corpus data.