Critical Analysis of English Education Policies in Japan Focusing on Two Discourses: Developing Human Resources and Nurturing Japanese Identity
Bibliographic record
Abstract
A growing body of research reports negative results, such as widening economic disparity, due to English educationreform influenced by neoliberalism. Japan is no exception. Linguistic instrumentalism is intensifying in Tokyo,which is scheduled to host the Olympic and Paralympic Games in 2020. This article critically analyzes policydocuments issued by the largest business lobby in Japan (Keidanren), Japan’s Ministry of Education, Culture, Sports,Science and Technology (MEXT), the Tokyo Metropolitan Government (TMG), and the Tokyo Metropolitan Boardof Education (TMBOE) within Japan’s social and political context. All of the documentary data are official-publicand open-archival. The study reveals that two discourses, developing human resources and nurturing Japaneseidentity, are repeated throughout the policy documents. While MEXT, TMG, and TMBOE stipulate their intention toaccelerate Japan’s internationalization, their policy documents have potential to lead students in an opposingdirection with an emphasis on fierce competition and pluralist multiculturalism, which dichotomizes the self andothers by simplifying differences. In the discussion section I suggest implementing pedagogical practice based oncritical multiculturalism to multiply the effect of these top-down measures. Ultimately, EFL teachers could form abottom-up powerbase by critically analyzing the official policies and by implementing practice that fits to theparticular setting.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".