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Record W3212357188

한국과 일본의 언어권(言語権)의 관점에서 본 다문화주의 -캐나다의 사례와 비교하여-

2020· article· ko· W3212357188 on OpenAlexaboutno aff
형진의

Bibliographic record

Venue일본문화학보 · 2020
Typearticle
Languageko
FieldComputer Science
TopicEducational Systems and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsLinguistic rightsHeritage languageDeclarationCultural rightsPolitical scienceHuman rightsLanguage policyLinguisticsMinority languageCultural heritageSociologyPedagogyFundamental rightsLawRight to propertyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Linguistic rights mean using and learning languages personally, publicly, and freely. And it means the right to exchange with them. Minority declared the right not to be discriminated based on languages in the Universal Declaration of Human Rights. After this, problems for linguistic minorities were raised in the two declarations. They are legally non-binding, but they are meaningful in that the problems about languages were raised. And they formed the foundation of the Universal Declaration of linguistic rights. Canada implemented pioneering multicultural policies. It evaluated multiculture with social resources and implemented active policies and heritage language education. However, it currently suspended heritage language education because dissent of it was strong in it. It is difficult to keep minorities’ linguistic rights. Discussion on linguistic rights has not begun in Korea. Heritage language education has been implemented focusing on the Korean language. it has been a little bit done in the Japanese language. Korea has little interest in heritage language education of various languages. The Linguistic rights Society was established in Japan in 1998 and discussion on linguistic rights has been actively done. Heritage language education is done focusing on the Japanese language, but in some areas, heritage language education of Chinese, Spanish, Korean, etc. Heritage language education is good to be implemented in the public education system.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.630
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.006

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 head0.044
GPT teacher head0.283
Teacher spread0.239 · 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 teacher head, not a consensus.

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
Published2020
Admission routes1
Has abstractyes

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