A Pragmatic Analysis of Nigerianisms in the English Usage in Soyinka's Death and the King's Horseman
Notice bibliographique
Résumé
Introduction The English language is the most widely spoken language in the world. It is a language used in about 673 countries globally, (Graddol, 1997, cited from Akere, 2009). In Nigerian social and cultural contexts, English has become a language employed in different domains of usage such as education, politics, religion, administration, foreign diplomacy, commerce, science and technology. According to Kachru (1985), users of English around the world can be classified into norm-producing inner circle which made up of native speakers of the language; norm developing outer circle, made up of second language users of English; and the norm dependent expanding circle comprising speakers of English as a foreign language. Since English has come in contact with people of different social and cultural backgrounds, new hybrids or variants of the language has 'sprouted'; such as American, British, Canadian and Nigerian Englishes. Different tongues of the language are employed in countries like South-Africa, Ghana, Kenya, Egypt, Lesotho, Nigeria, Cuba, Philippines. Tanzania, Malaysia, Pakistan, Liberia, Sierra-Leone, Gambia etc. Also, the contact of the English language with numerous mother tongues in Nigeria has led to the phonological, syntactic and lexico-semantic variations of the language in the country. As a result, several linguistic studies have been carried out on the lexico-semantic as well as the phonological variations of Nigerian English (NE). Among them are Brosnahan (1958), Banjo (1971, 1995), Bamgbose (1983), Adesanoye (1973), Jubril (1982), Odumuh (1984, 1987), Adegbija (1989, 1998), Udofot (1977, 2003), Kujore (1985), Jowitt (1991), and Bamiro (1994). According to Brosnahan (1958), variation of Nigerian English can be distinguished through the degree of deviation which the variety has from the exoglossic standard norm. Brosnahan's variety 1 of Nigerian English is Nigerian pidgin which is mostly used by non-literate Nigerians. His variety 2 is the English of the primary school leavers. The variety 3 of Nigerian English, according to Brosnahan's (ibid) is the English language employed by the secondary school leavers, while the variety 4 is the English of the university graduate. According to Banjo (1971), there are four varieties of Nigerian English. Banjo's (1971) variety 1 of NE is characterized by the wholesale transfer of [L.sub.1] to [L.sub.2] (English); variety 2 resembles the standard variety (i.e. native speakers'), variety 3 resembles Standard British English (SBE) both in syntax and semantics but different in phonological features; and Banjo's (1971) variety of NE is identical with the British English in syntax, semantics and lexical features, but it is mutually unacceptable among Nigerians. For a variety of Nigerian English to be accepted as a standard variety in the country, Adegbija (1998) states that such a variety must be internationally intelligible, mutually acceptable among Nigerians and devoid of ethnic or social stigmatization. In his own view, Odumuh (1984) states that the following are the varieties of Nigerian English: (i) local colour variety, (ii) incipient bilingual variety, and (iii) near native speaker's variety. Adegbija (1989. 1998), equally examines the characteristics of the lexical and semantic variations of Nigerian English. According to him, lexico-semantics variations of Nigerian English are caused by six factors thus: (i) Socio-cultural differences between the native speakers and second language users of English in Nigeria; (ii) dynamics of the pragmatics of a multilingual context; (iii) the exigencies of the varied discourse constraints and modes in English and in the indigenous languages; (iv) the pervasive influence of the press; (v) the standardization of idiosyncrasies and errors; and (vi) the predominantly formal medium of the acquisition of English. According to Adegbija (1998), Nigerian English is characterized by analogy, language, transfer, acronyms, semantic shifts and neologisms. …
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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,005 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».