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Enregistrement W7010392845

Interpersonality Strategies in International Student Handbooks Written by Native Speakers of English (NSE) and Non-native Speakers of English (NNSE)

2018· dissertation· en· W7010392845 sur OpenAlexaboutno aff

Notice bibliographique

RevueTesis Doctorals en Xarxa (Consorci de Serveis Universitaris de Catalunya) · 2018
Typedissertation
Langueen
DomaineArts and Humanities
ThématiqueDiscourse Analysis in Language Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMetadiscourseInterpretation (philosophy)DerogationSubject (documents)Term (time)TerminologyStress (linguistics)Focus (optics)
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Summary of the doctoral dissertation Interpersonality Strategies in International Student Handbooks Written by Native Speakers of English (NSE) and Non-native Speakers of English (NNSE)\nTesis doctoral presentada por: Stan McDaniel Mann\nValencia, 2014\n\n\tHave you ever read a brochure or handbook written in English by a non-native speaker of English (NNSE), noticed that the grammar and syntax was excellent and the terminology was near-perfect, but you still did not understand the essence of what the author was trying to communicate, or you had the feeling that the information was ambiguous? It was precisely for these two reasons that this research on interpersonality strategies was carried out. Through this analysis it is hoped to contribute to explaining why international student handbooks written by NNSE do not persuade effectively enough and do not establish a proper writer-reader relationship, which are precisely two of the main goals of interpersonality. Interpersonality is also referred to as interactional metadiscourse or interpersonal metadiscourse, and all three terms are used interchangeably throughout this study.\n\tSince the term metadiscourse was coined over 50 years ago, the definitions for it have continuously evolved. Metadiscourse may be broadly described as overtly expressing the writer´s acknowledgement of the reader (Dahl, 2004, p. 1811). There are two classifications of metadiscourse, textual metadiscourse and interactional metadiscourse. For this study, interactional metadiscourse has been chosen due to its focus on establishing a close writer-reader relationship. \n\tHyland and Tse´s (2004) model of analysis proved to be the most reliable for this study due to the fact that it was the first classification of interactional metadiscourse markers with 5 main interactional metadiscourse categories: hedges, boosters, attitude markers, engagement markers, and self-mentions, each category with its corresponding subcategories for a more precise classification and analysis. The main objective was to see the difference of interpersonal metadiscourse usage between NSE and NNSE authors of international student handbooks. The corpus for this study consisted of 50 international student handbooks written by NSE authors, 10 handbooks from 10 different universities from the following NSE countries: USA, Canada, UK, Ireland, and Australia, and 50 handbooks written by NNSE authors, 10 handbooks from 10 different universities from the following NNSE countries: France, Germany, Italy, Turkey, and Japan. A total of 31,989 interpersonal metadiscourse markers from NSE handbooks were classified and analyzed, and a total of 12,948 interpersonal metadiscourse markers from NNSE handbooks were classified and analyzed. \n\tThis study was rather unique in that, unlike the vast majority of the previous research performed on interpersonal metadisdourse which was done on the genre of the research article, it was focused on the business-academic genre of international student handbooks. \n\tFor the statistical analysis, the obtained data was submitted to SPSS, and the ANOVA and T-tests were run. For the percentage analysis, percentages were computed for the main categories and subcategories of interactional metdisdourse. Significant and highly significant differences were discovered and discussed. On a general level, NNSE authors used a total of 10.03% of interactional metadiscourse while NNSE authors used only 5.69%. One of the most surprising results was a very significant difference between interactional metadiscourse usage between to NSE countries. UK authors used a total of 13.37% of interactional metadiscourse while authors from Australia used a mere 6.82%, representing a very unusual variance between 2 NSE countries. \n\tA broad conclusion of this study is that there is definitely a difference in interactional metadiscourse usage between NSE and NNSE authors of international student handbooks which could possibly be due to educational and/or cultural factors. One of the suggestions for possible further research in this field could be the impact of including interpersonality strategies in programs for teaching English as a foreign language.

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,100
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,001
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,013
Tête enseignante GPT0,279
Écart entre enseignants0,265 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2018
Routes d'admission1
Résumé présentoui

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