Anarcho-transcreation: Anarco-transcriação
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About this ebook
This book addresses the 'why' and the 'how' of the practice of anarcho-transcreation - when fidelity to the original text is incompatible with a literal translation, and where languages and cultures are inescapable from geopolitics. "Flip-over", bilingual, non-fiction style - with an anarchist, de
Mirna Wabi-Sabi
Mirna Wabi-Sabi is an editor, writer, political theorist, teacher and translator. She is the founder of the media initiative and press Plataforma9. For most of her life, she traveled the world, lived in São Paulo, New York, Nijmegen, Amsterdam and Salvador, before returning to her hometown, Niterói, in 2019. After witnessing the post- 9-11 political climate as a young immigrant in the USA and Western Europe, Mirna's work began to orbit radical social change, focused on the destruction of white capitalist patriarchy.
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Anarcho-transcreation - Mirna Wabi-Sabi
Introduction
Translation
(anarcho)Transcreation
Anarchism
Nationalism and de-hierarchization
Imperialism and discourse
Corporatization and remuneration
Authority and autonomy
Conclusion
References
To speak means to be in a position to use a certain syntax, to grasp the morphology of this or that language, but it means above all to assume a culture, to support the weight of a civilization.
(Frantz Fanon)
Introduction
Whoever reads, has read a translation. Even if the text is not a translation, it probably alludes to one. Anyone who does not read, has already been exposed to an idea that has been translated, be it in on T.V.¹, in prayer, or at work. This book, therefore, is not only for people who translate. It is for anyone who has an interest in how ideas and thoughts are shared around the world. The interest in ideas informs our condition as thinking beings that matter in the world. What I want to convey here, above all, is that it is not enough to import ideas, it is necessary to disseminate the idea that people are important. It is not a nation, corporation, or intellectual and governmental authority that matters. We are the ones who matter, and the knowledge is there to enhance our autonomy — especially that of people who are systematically marginalized by the aforementioned entities.
Translation is not just about words. It is about political, social, personal, and historical thoughts and contexts. Words can be handled by algorithms and binary functions. Thoughts, not so much. They are creations of a life, of a being with history and culture, with incomputable idiosyncrasies. Translating, then, demands the ability to bring a thought to an audience that has its own history and culture — without infiltrating authorship. When we think about politics, the translation of a theory that proposes to be universalist, or internationalist, needs to consider not only the peculiarity of the new audience, but also of the authorship. If the theory to be translated is one that aims to imagine the end of borders and nations, addressing the complexity of undeniable cultural boundaries is fascinating. Why and how to execute translation projects taking geopolitics and anarchism into account?
Translation
Translation is much more than a mechanical conversion. Several applications nowadays propose to convert characters and words instantly, which — despite being useful — they end up causing a new set of obstacles to understanding. Some even become a joke, such as: mango juice being translated as ‘sleeve juice’ (Manga can mean either ‘sleeve’ or ‘mango’). Most automatic translators have been able to solve this type of problem over the past 10 years. But the phrase washing your mango
is more complicated, because it requires an analysis of a larger context, since both can be washed, while only one is likely turned into juice. Google Translate, one of the most widely used translation systems in the world, can speed up the work of a translator, but it cannot be the translation itself. Even though this may seem obvious, it is interesting to think about what is behind the inefficacy of automation.
Automated translation systems have for many years been the statistical machine translation
. It starts from the word to the sentence and hierarchizes the relationship between syntax and phrasemes. In addition to being inaccurate and the subject of jokes, it is a Eurocentric method and works — considerably — better among Western European languages. The effectiveness of this system when translating between Western languages is attributed to the grammatical proximity between them, but not only. It is necessary to consider the political, historical and economic relationship of countries in this region.
Historically, European political powers have been more interested in understanding each other than in understanding populations from regions they colonized. In the case of Dutch colonization, of Indonesia and South Africa, the colonists — in fact — invented a new language for local peoples. Afrikaans, a language spoken in South Africa, comes from the word African
in Dutch, a name given to a West Germanic language because settlers did not want the black population to associate with the white elite. In Indonesia, the Dutch did not want the local population learning the language of the elite
either, but they wanted a dominant language for administrative purposes, so they made one based on Malay — Indonesian.
The initiative to mechanize translations with languages outside the European context is recent. Corpus creation is expensive and time-consuming, and many languages are less-resourced
(Sellam, Deffaf, Sadat, & Belguith, 2015). It was only in the 1990s that a corpus, the extensive resource needed in statistical machine translation, emerged for Chinese (Song & Dai, 2015). It makes sense that an automatic translation system has expanded from the Western European context to Chinese-English. If we consider the political and economic interests between these regions and the fact that certain languages access more resources, the financial interest behind this move is undeniable.
In 2016, essentially all major translation platforms changed from statistical
to neural machine translation
. It is inspired by the human brain, which means that instead of starting from the principle of each word, phraseme, and syntactic rules, as in the statistical