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Record W156356568

Модель интеллектуального развития учащихся-билингвов (на примере адыгейско-русского двуязычия)

2014· article· ru· W156356568 on OpenAlexaboutno aff
Богус Мира Бечмизовна

Bibliographic record

VenueУченые записки университета им. П.Ф. Лесгафта · 2014
Typearticle
Languageru
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsnot available
Fundersnot available
KeywordsGermanBilingual educationNeuroscience of multilingualismForeign languageProcess (computing)Symbol (formal)LinguisticsPsychologyMathematics educationPedagogyComputer science
DOInot available

Abstract

fetched live from OpenAlex

The aim of the present study was revealing the author's model of the intellectual development of the students in the conditions of bilingualism. The article analyzed the domestic and foreign models of the bilingual education. Special attention has been paid to Canadian, American, German, European models of the bilingual education. This analysis has allowed the author to obtain the conclusion that the German model of the bilingual education may serve as an example for the developing models of the bilingual education for the Russian national school. The author has justified the necessity in using the symbol -sign systems of the two languages in the development of bilingual intelligence. The model has been built on the basic idea that for intellectual development of the bilingual personality there is a need in purposeful introduction in educational process of the tasks system in two languages (native and second). The identified model for development of the intellectual abilities of the students based on the bilingual tasks system is applicable at all levels of study.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0190.005

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 head0.014
GPT teacher head0.211
Teacher spread0.197 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueУченые записки университета им. П.Ф. ЛесгафтаSame topicSecond Language Learning and TeachingFrench-language works237,207