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Record W103278690

Трансформации современной евразиискои языковой личности российско-казахстанского приграничья

2013· article· ru· W103278690 on OpenAlexaboutno aff
Карабулатова Ирина Советовна, Койше Кенесар Куанышевич

Bibliographic record

VenueВестник Кемеровского государственного университета культуры и искусств · 2013
Typearticle
Languageru
FieldSocial Sciences
TopicCultural, Linguistic, Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsKazakhSlavic languagesUkrainianPopulationLatvianTatarEthnic groupGeographyEthnologyHistoryLinguisticsAncient historySociologyAnthropologyClassics
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.502
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0020.005
Science and technology studies0.0070.007
Scholarly communication0.0050.004
Open science0.0070.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0700.074

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.

Opus teacher head0.039
GPT teacher head0.294
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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