Die Auswirkungen des Gemeinsamen europäischen Referenzrahmens für Sprachen auf den Deutschunterricht in Japan, untersucht anhand von Lehrbüchern für Deutsch als Fremdsprache
Bibliographic record
Abstract
This article looks at the application of the Common European Framework of Reference for Languages (CEFR) for German language education in Japan. The CEFR was adopted by German publishers and institutions soon after its introduction, and within a few years all textbooks published in Germany, all language tests conducted by German and Austrian institutions, and all language courses in German-speaking countries have been redesigned and labelled with the six reference levels of the CEFR. On the other hand, the implementation of the CEFR in Japan has been much slower. The most widely taken German language test in Japan does not yet reflect the CEFR, and only about 5% of all textbooks published in Japan follow the CEFR. This article looks at the background of these developments with a focus on textbooks, and makes a case for the wider adoption of the CEFR for teaching German as a foreign language in Japan.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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.
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; both teacher heads agree on what is shown here.
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".