According to Michael D. Gordin, science historian and author, “English is the language of science today. No matter which languages you know, if you want your work seen, studied, and cited, you need to publish in English.” Suggesting that a lot of non-English language research papers are overlooked.
There is an abundance of research published in languages other than English that simply does not get translated. For Tatsuya Amano, the English-only phenomenon in the scientific field creates challenges and gaps in the transfer of knowledge between communities.
This is particularly evident in the realm of global biodiversity and conservation. It relates to the fact that evidence around biodiversity conservation is routinely generated by local practitioners, who often prefer publishing their work in their first language; which, for many, is not English. The majority of these works are thus left untranslated.
A study published by PLOS Biology, an open-access, peer-reviewed journal dedicated to biology, found that non-English language studies could provide crucial evidence for informing global biodiversity conversation.
The research looked at 419,679 peer-reviewed papers in 16 languages and identified 1,234 non-English language studies, which provided evidence on the effectiveness of biodiversity conservation interventions. However, because they were not written in English, they may have been overlooked.
Results of the study found that incorporating non-English language research could expand the geographical coverage of scientific evidence on biodiversity by 12–25%, and the number of species covered by 5–32%. There is research on nine amphibian species, 217 bird species and 64 mammal species, which were not covered in English-language studies.
With these figures in mind, synthesizing non-English language studies could be an effective way of overcoming the lack of local, context-dependent evidence, and instead, facilitate evidence-based conservation on a global scale.
What About Machine Translation?
“The quality of machine translation has been improving rapidly, especially in languages such as Spanish, German, Japanese and French, aiding a wider understanding of non-English-language literature,” according to a 2018 study by Sonia Zulfiqar and her team entitled, “Is Machine Translation a Reliable Tool for Reading German Scientific Databases and Research Articles?”
The same study stated, “Even a small number of critical errors [that] can be found in machine translation, can have major consequences in evidence synthesis. There is a need to conduct more robust tests to assess the reliability of machine translation in conducting evidence synthesis.”
However, the team of Zulfiqar et al. prefers to keep its usage of machine translation at a minimum, pointing out, “machine translation should still be used with caution in evidence synthesis, for example, when a native speaker of the language can be asked to double-check the translation output.”