Narrative microstructure and macrostructure skills in Arabic diglossia: The case of Arab immigrant children in Canada
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
Aims and objectives: The study investigated narrative microstructure skills of Arabic-speaking immigrant children in Canada ( N = 75; age range 7–12 years) with specific focus on diglossia and the lexical distance between Spoken Arabic (SpA) and Standard Arabic (StA). The study also tested the relationship between microstructure and macrostructure and probed into the relative importance of general versus diglossia-specific features of microstructure in predicting macrostructure. Design/methodology/approach: Participants were asked to tell a story from a picture using an Arabic version of the Test of Narrative Language (Gillam & Pearson, 2004). Instructions to participants were given in StA. Data and analysis: General measures of microstructure were coded: number of tokens, number of types, type/token ratio, and mean length of utterance (MLU). In addition to these general measures, we coded the average frequency of five diglossia-specific word types: (a) identical words, which keep the same phonological form in StA and SpA; (b) SpA cognates, namely, cognate words that keep different yet related forms in StA and SpA, used in their SpA form; (c) StA cognates, cognate words used in their StA forms; (d) unique SpA words; and (e) unique StA words. Regression analysis was used to predict macrostructure from general and diglossia-specific features of microstructure. Findings/conclusions: Results showed that the bulk of the lexicon of the narratives produced by immigrant children consisted of words and word forms that are within SpA: identical words, SpA cognates, and unique SpA words; StA word forms appeared less frequently, and English code-switched words were very rare. Results also showed that the microstructure features of narrative length in tokens and type/token ratio significantly predicted macrostructure beyond the children’s age and Arabic language proficiency. However, when diglossia-specific lexical features were added as predictors, the frequency of StA words predicted unique variance in macrostructure beyond age, Arabic language proficiency, and narrative length. Findings advance our understanding of narrative skills in Arabic diglossia among new immigrants and the role of lexical distance in narrative production in this context. Originality: The study is innovative in investigating the manifestation of diglossia in narrative microstructure features and the role of diglossia-specific features in predicting macrostructure, as well as in testing this question among immigrant children. Significance/implications: The study demonstrates the multifaceted lexicon of diglossic Arabic speakers as reflected in the microstructure of their narratives and the prevalence of SpA word forms in their lexicons. The study also demonstrates a significant relationship between microstructure and macrostructure, and the important role of StA lexical features of microstructure in predicting macrostructure. The results of the study have theoretical implications for the importance of lexical distance in understanding narrative production in children at both the microstructure and macrostructure levels. The study also has practical implications for assessment and intervention with Arabic-speaking children in diglossic Arabic.
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.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 découle