Learners’ practice and theory about Japanese honorifics : an oral interview activity with native speakers
Bibliographic record
Abstract
Japanese honorifics (JH) are challenging for learners of Japanese language to acquire due to their complex grammatical formulas. Textbooks tend to assume that the explanation of grammatical rules and drill exercises focusing on the rules are sufficient for learners to be competent in JH. However, functional issues related to honorifics such as how to use honorifics in socioculturally appropriate ways or how to deal with non-linguistic aspects of honorifics are likely to be ignored. The present study questioned the assumptions entailed in the traditional formoriented approach to teaching language, and examined an oral interview activity carried out by 24 students in a Japanese language course at a Canadian university. In this activity, the students interviewed Japanese professors using JH, and several types of data (i.e., the researcher observations and interviews with the participants and student written reflections on the interviews) were analyzed in order to find out students' practice (i.e., what students did) of and theory (i.e., how students perceived) about JH and oral interviews. The findings of the study present a very complex picture of students' practice and theory; they were engaged not only in the formation of the rules of JH but also in the functional areas such as non-verbal behaviour and conversation management. The data also revealed that students were very much concerned with functional areas during the interviews. From these findings, the study emphasizes the importance offunctions embedded in JH, and suggests that the Japanese teacher help learners acquire the functional competence dealing with JH as well as the linguistic competence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".