The Acquisition of Russian by Multilingual Children in Canada
Bibliographic record
Abstract
This chapter examines a connection between multilingual children’s proficiency in Russian as measured by specific linguistic parameters, such as vocabulary breadth and sentence length, and sociolinguistic parameters, such as children’s language attitudes and language exposure at home and outside. The participants were 30 multilingual five- to seven-year-old children residing in Canada. Nineteen proficiency parameters were extracted from elicited children’s narratives and correlated with 21 sociolinguistic parameters derived from structured interviews with the children. The results indicate that within the given age group, most children favor Russian-English bilingualism, and the strongest variables that correlate positively with several of the measured proficiency parameters are frequency of communication in Russian with siblings, watching Russian movies and playing computer games in Russian, an ability to sing a song in Russian, and frequency of using Russian in interactions with Russian-speaking friends. Additionally, attending community language schools was associated with fewer non-canonical forms and a higher number of nouns in children’s narratives. The chapter discusses these results in relation to the Linguistic Equilibrium Hypothesis and outlines practical suggestions for community schoolteachers and parents of multilingual children. В данной главе рассматриваются связи между параметрами владения русским языком многоязычными детьми и социолингвистическими параметрами (такими как отношение детей к языкам и объем их погружения в русский язык и культуру). Тридцать многоязычных детей в возрасте 5–7 лет, проживающих в Канаде и говорящих на русском как на языке наследия, участвовали в исследовании. Материалами послужили нарративы детей на русском, а также структурированные интервью. Результаты исследования показывают, что данная возрастная группа поддерживает англо-русское двуязычие. Самые сильные ассоциации с языковыми параметрами обнаружены в следующих социальных характеристиках (в убывающем порядке силы ассоциации): как часто дети говорят по-русски с братьями и сестрами; как часто дети смотрят русские фильмы и играют в компьютерные игры на русском; могут ли спеть песню по-русски; и как часто общаются с русскоговорящими друзьями. Посещение диаспорных языковых школ ассоциируется с меньшим количеством ненормативных форм, а также с большим количеством существительных в нарративах. Результаты исследования рассматриваются в их приложении к гипотезе Лингвистического Эквилибриума. Вносятся предложения для учителей диаспорных детских начальных школ, а также для родителей русскоговорящих детей-мультилингвов.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".