This article analyzes the preliminary norms (Toury 1995) governing the translation of Arabic works into Spanish produced by members of Spain’s academic community in the twentieth century. In particular, we study the ideological motives and objectives behind the choice of works to be translated. Translation was the ideological tool par excellence of Spanish Arabism. The Catholic Church; Spanish state, regional, and local government bodies; and the European Cultural Foundation were the principal patrons. The works translated served to endorse the pre-eminence of Christendom over Islam and to advance Spanish nation-building. They also contributed to the encouragement of emancipatory and feminist discourses, the commercial success of the Arab winner of the Nobel Prize, Najīb Maḥfūẓ, and the promulgation among the European public of a discourse opposed to the ‘clash of civilizations’. Thus, our analysis illustrates the capacity of translation to generate ideology in a specific socio-political context.
Modern Standard Arabic makes extensive use of coordination particles whereas punctuation marks are scarce and erratic, leading to long clauses. This is generally assumed to hinder Sentence Boundary Detection and to promote sentence splitting when translating from Arabic into English. Previous literature on translation from Arabic to Spanish is practically inexistent. We have tested this hypothesis regarding translation from Arabic to Spanish on a sample of 282,714 graphic words extracted from a bilingual corpus of 8,681,110 graphic words and found that each Arabic sentence yielded an average of 1.5 Spanish sentences. Furthermore, our data shows the potential impact of directionality in that sentence splitting when translating from Arabic into Spanish is 50% more frequent than from English into Arabic. We also determined statistically that five elements (wa [و], ḥaythu [حيث], kamā [كما], wa-qad [وقد], and wa-dhalika [وذلك]) are the most salient potential markers for sentence splitting in the resulting Spanish translations. Our findings should be particularly interesting for Computational Linguistics and translator training.
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