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Language policy and multilinguality

2024· article· ru· W4403063658 on OpenAlexaboutno aff
Л.В. Резникова, А.Л. Погребисская

Bibliographic record

VenueSovremennyj učënyj. · 2024
Typearticle
Languageru
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsLinguisticsLanguage policyPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

настоящая статья посвящена исследованию языковой политики и многоязычия, с особым вниманием к их историческому развитию, современным моделям и влиянию процессов глобализации. В условиях глобализации и интенсификации миграционных потоков вопросы управления языковым разнообразием приобретают особую значимость, оказывая влияние на социальную интеграцию, национальную идентичность и образовательные системы. Исследование основано на анализе исторических документов, нормативных актов, научной литературы, а также на полевых данных, включая интервью и опросы. В рамках исследования проведен сравнительный анализ языковых политик различных стран, таких как Швейцария, Канада, Испания и Финляндия, что позволило выявить общие тенденции и уникальные особенности в подходах к поддержке языкового многообразия. Результаты исследования показывают, что успешные модели языковой политики включают официальное признание многоязычия, поддержку языков меньшинств и интеграцию многоязычного образования. В то же время, глобализация и технологические изменения оказывают двойственное влияние на языковую политику: с одной стороны, они способствуют распространению доминирующих языков, с другой - предоставляют новые возможности для сохранения и изучения редких языков. Особое внимание уделено образовательным стратегиям, направленным на поддержку многоязычия, и правовым аспектам регулирования языкового использования. Исследование подчеркивает необходимость комплексного подхода к разработке и реализации языковой политики, учитывающего исторический контекст, социальные и политические особенности, а также вызовы и возможности цифровой эпохи. Полученные результаты и предложенные рекомендации могут быть полезны для разработчиков языковой политики, исследователей и практиков в области образования, а также для широкого круга читателей, интересующихся вопросами языкового разнообразия и культурного наследия. this article explores language policy and multilingualism, with a particular focus on their historical development, contemporary models, and the impact of globalization processes. In the context of globalization and increased migration flows, managing linguistic diversity has become crucial, influencing social integration, national identity, and educational systems. The research is based on the analysis of historical documents, legal acts, scientific literature, and field data, including interviews and surveys. A comparative analysis of language policies in various countries, such as Switzerland, Canada, Spain, and Finland, was conducted, revealing common trends and unique features in approaches to supporting linguistic diversity. The results of the study show that successful language policy models include the official recognition of multilingualism, support for minority languages, and the integration of multilingual education. At the same time, globalization and technological changes have a dual impact on language policy: they promote the spread of dominant languages while providing new opportunities for the preservation and learning of rare languages. Special attention is given to educational strategies aimed at supporting multilingualism and the legal aspects of language use regulation. The study emphasizes the need for a comprehensive approach to developing and implementing language policy, considering historical context, social and political characteristics, as well as the challenges and opportunities of the digital age. The findings and proposed recommendations can be useful for policymakers, researchers, and practitioners in the field of education, as well as for a wide audience interested in issues of linguistic diversity and cultural heritage.

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0040.008
Scholarly communication0.0110.008
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0180.002

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 head0.071
GPT teacher head0.511
Teacher spread0.440 · 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 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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