Aspects of second language speech: A variationist perspective on second language acquisition.
Notice bibliographique
Résumé
The work reported in this study is based on empirical data collected from three groups of speakers: native speakers of English, native speakers of Persian and Persian speakers of English as a second language. The study addresses, among others, two of the most important aspects of second language speech: (1) it provides an extensive sociolinguistic description of L2 speech by conducting multivariate analyses on features of English spoken by Persians. In this way it throws light on the issue of the systematicity of second language speech by providing evidence for systematic variation in L2, (2) it explores the relationship between native language of the speakers and their L2, on one hand, and the relation between the L2 and the language L2 learners try to acquire, on the other. In other words, it examines the sources of the patterns of variability found in second language speech. The focus of our investigation is the variable contraction (deletion) of auxiliary verbs and variable use of relative and resumptive pronouns by L2 learners. We first use the principles of variation theory to make a detailed assessment of the behavior of the L2 learners with respect to the contraction of auxiliary verbs in their natural L2 speech at both low and high proficiency levels. The comparative method, then, is applied to systematically compare patterns of contraction in low and high proficient L2 speech with: (a) patterns of contracting auxiliaries in our native English data and, (b) patterns found in the samples of Persian speech produced mostly by the same L2 informants. Then, we extend the same procedures to examine variable use of relative and resumptive pronouns in restrictive relative clauses in the three contexts of English, Persian and L2 (high proficiency only). Our results produced conclusive evidence that the variability found in the features of L2 speech studied in this thesis was indeed systematically conditioned by at least one linguistic factor group. There was found to be no difference between high and less proficient learners in this regard. With respect to the sources of variability in L2 speech, we consider at least three possibilities: (1) that the variation can be explained by processes derived from English as the target language, (2) that the variation can be explained by the processes derived from Persian as the native language of the learners, and (3) that the variation and its conditioning system is unique to our learners' L2 speech, different from native or target languages. Parallel analysis and comparison of features of L2 and those of the informants' native and target languages demonstrated that variability in advanced second language speech was mostly conditioned by factor groups and factor weights that constrain native English speech. Informants' native language was found to play a trivial role in this respect. Less proficient learners, however, relied more on their native patterns of variability in cases where they have not acquired the target language patterns of variation yet. It was also demonstrated that patterns of variability change as learners advance in their L2 development. We did not observe any pattern unique to our informants' second language behavior, different from either English or Persian.
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 | 0,003 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,006 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».