A Semantic and Grammatical Comparison between the Chinese “YE” and Japanese “MO” and an Analysis of the Difficulties of “YE”’s Acquisition by Japanese Students
Bibliographic record
Abstract
Through a comparative study between “YE” in modern Chinese and its counter part “MO” in Japanese, the paper puts forward the difficulties and easiness of Japanese students’ acquisition of “YE”. It offers help to both teaching and studying. Key words: grammatical distribution, acquisition Resume: Cet article nous indique les difficultes et les facilites pour les etudiants japonais en apprentissage du mot “也“ ne faisant des comparaisons entre ce mot et son equivalent “も“en japonais. Il est d’une importance significative pour les enseigants et les etudiants. Mots-cles: repartition grammaticale, enseignement 摘要：本文通過對現代漢語“也” 日本語中“也”的的相應用法“も”的比較，切實地指出了日本留學生習得漢語“也”的難點和易點。對老師教學和學生學習都很有意義。 關鍵詞：語法分佈；習得
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| 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".