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Record W7132914774

Ideological orientations towards different forms of bilingualism: an analysis of press release documents about language policies in Japan

2006· dissertation· W7132914774 on OpenAlexaff
Kyoko Motobayashi

Bibliographic record

VenueTSpace · 2006
Typedissertation
Language
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsLibrary and Archives Canada
Fundersnot available
KeywordsIdeologyLanguage policySemioticsCritical discourse analysisOn LanguagePosition (finance)Language ideologyAction (physics)
DOInot available

Abstract

fetched live from OpenAlex

This study examines contemporary Japanese ideological orientations towards different languages and different forms of language education, using a social semiotic discourse analysis approach. Press releases associated with two language-related educational policies, the Action Plan for Japanese with English Ability and the Japanese as a Second Language Curriculum, were analyzed. This thesis first describes the way in which each of these two policies creates various images of languages and bilingualism, as well as various categories and images of the learners. Then, the study points out that a language ideology is shared across these two policies: Japanese language as the only tool for intellectual activities at school and English as the main tool for communication with the international world. It is argued that this language policy discourse reflects the position and strategy of Japan as a nation-state in the transitional era of globalization.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.007
Science and technology studies0.0050.007
Scholarly communication0.0070.003
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.025
GPT teacher head0.382
Teacher spread0.357 · 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 designQualitative
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
Published2006
Admission routes1
Has abstractyes

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