Tapping into non-English-language science in tackling global challenges

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This project aims to transform the conventional practice of English-biased evidence use to multilingual evidence synthesis to enable us to better tackle global challenges. The project expects to lay the foundations and provide platforms for multilingual, unbiased evidence-based solutions to global issues including biodiversity loss, climate adaptation and animal-origin diseases. Expected outcomes include a database of non-English-language evidence on the three global issues of focus, machine learning tools, and machine translation platforms that make non-English-language evidence accessible. This should benefit national/international policies and practices by making a neglected source of evidence available for science-led decision-making.