Трансформации современной евразиискои языковой личности российско-казахстанского приграничья
Bibliographic record
Abstract
The article examines the processes of interpenetration of languages in the structure of modern Eurasian linguistic identity, reveals the nature of the interference, leading to the appearance of new features in the regional language of the Russian-Kazakh border areas. We mean the territory of the Russian borderland Tyumen region and the Kazakh border area Northern Kazakhstan. Migration is a multiaspect and complex social-psychological process that begins long before the fact of migration.russian population of the Tyumen region once assimilated representatives Ugric (Khanty, Mansi, Komi), Turkic (Tatars, Kazakhs), Slavic (Ukrainian, Belarusian). Cossacks, merchants, and just farmers and other service people in Siberia almost every man were married to local women, resulting in any sub-ethnic Russian community, a group of Metis population, anthropologically close to the neighbors. This confusion is reflected in the language of the local population on both sides of the border and among Russian and among Kazakhs and Tatars. Facts Kazakh say that the north-east and other dialects of the Kazakh language borrowed many words from Arabic, Persian, Russian and other languages, even before the formation of the literary language. But for all that each of the dialects assimilates new words in their own way. For example, the Russian word «krovat’»/»bed» sounded «keruert» in the West of Kazakhstan, in the South «keruet», and in the North-East «keruert». We can say that the mutual phenomena arise from both language-contactors in areas of intense inter-ethnic cooperation; it helps in certain conditions of the evolution of both the linguistic identity and language systems in general. It is not that we are seeing only West Siberian Kazakhs under the influence of the Russian environment; the Kazakh language also has a significant impact on both the Russian language of Kazakhs and Tatars and Russian dialects of the Russian-Kazakh border region in the Kazakh region. We find this effect at the level of phonetics, vocabulary, and grammar. We have a complex structure of modern Eurasian multi-conceptual linguistic identity, which is multiaspect in modern palette of sound.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.010 |
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 source (direct Gemma or distilled Codex), 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".