Japanese interactional particles yo, ne and yone : their functions and acquisition by Japanese language learners
Notice bibliographique
Résumé
The Japanese language possesses a class of particles called "interactional particles" which appear in and facilitate interactions among people. This thesis analyzes the functions and Japanese language learners' acquisition of the interactional particles yo, ne and yone, which frequently occur in Japanese conversations. Employing speech data obtained from spontaneous conversations and written data from questionnaires and fill-in-the blank tests, the present study analyzed yo, ne and yone as used by Native Japanese Speakers (NJSs) and Japanese Language Learners (JLLs). It is generally understood that yo marks new information and ne elicits and demonstrates agreement. Based on the analyses of yo, ne and yone in previous works, I propose that the fundamental function of yo is "pointing to the speaker's private world" and that that of ne is "pointing to the common ground of the speaker and addressee." Yone, the combination of yo and ne, also points to the interlocutors' common ground. Due to the existence of yo, yone further reveals the speaker's personality: uncertainty about information and empathy toward the addressee. The NJS data revealed two notable practices which contrast with general understanding concerning the use of these particles. First, the NJSs presented new information in conjunction with ne, often accompanied by the nominalization form n(o) (da/desu). Secondly, they often requested agreement by employing yone. I claim that the NJSs' inclination for using ne and yone, the particles of "common ground," exemplifies a politeness strategy and Japanese communicative styles (e.g., expressions of enryo 'reservedness', omoiyari 'empathy' and wakimae 'discernment'), both of which are oriented to the unification of understandings between the speaker and addressee. The JLLs underused yone and overused ne. The JLLs' use of yone was approximately 10% lower than that of the NJSs. In contrast, the JLLs' use of ne was 20% higher than that of the NJSs. Furthermore, the JLLs misused yone and ne due to inadequate instruction on their use both in textbooks and classrooms. In particular, the JLLs showed difficulty when presenting new information by properly combining ne and yone with the nominalization form. This indicates the importance of the ability to handle the nominalization form along with yo, ne and yone. The present study revealed the JLLs' inadequate acquisition of the use of yo, ne and yone, which conform to politeness strategies and Japanese communicative styles. In conclusion, I suggest that Japanese textbooks and classrooms should pay more attention to the effects of these particles on human relationships. I also propose the introduction of yone, which is not often dealt with, into Japanese language teaching because of its significant contribution to Japanese interaction and discourse: an essential device for demonstrating agreement and exemplifying Japanese politeness and communicative styles.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».