Overcoming Language Barriers in Academia: Machine Translation Tools and a Vision for a Multilingual Future

By Emma Steigerwald1, Valeria Ramírez-Castañeda1, Débora Y C Brandt1, András Báldi2, Julie Teresa Shapiro3, Lynne Bowker4, Rebecca D Tarvin1

1. University of California, Berkeley 2. Centre for Ecological Research, Vácrátót, Hungary 3. Ben-Gurion University of the Negev 4. University of Ottawa

Having a central scientific language remains crucial for advancing and globally sharing science. Nevertheless, maintaining one dominant language also creates barriers to accessing scientific careers and knowledge. From an interdisciplinary…

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Having a central scientific language remains crucial for advancing and globally sharing science. Nevertheless, maintaining one dominant language also creates barriers to accessing scientific careers and knowledge. From an interdisciplinary perspective, we describe how, when, and why to make scientific literature more readily available in multiple languages through the practice of translation. We broadly review the advantages and limitations of neural machine translation systems and propose that translation can serve as both a short- and a long-term solution for making science more resilient, accessible, globally representative, and impactful beyond the academy. We outline actions that individuals and institutions can take to support multilingual science and scientists, including structural changes that encourage and value translating scientific literature. In the long term, improvements to machine translation technologies and collective efforts to change academic norms can transform a monolingual scientific hub into a multilingual scientific network. Translations are available in the supplemental material.

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  • Steigerwald, E., Ramírez-Castañeda, V., Brandt, D. Y., Báldi, A., Shapiro, J. T., Bowker, L., Tarvin, R. D., (2022), "Overcoming Language Barriers in Academia: Machine Translation Tools and a Vision for a Multilingual Future", HSSCommons: (DOI: )

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Notes

Published in Open Access in BioScience, Volume 72, Issue 10, October 2022, Pages 988–998, https://doi.org/10.1093/biosci/biac062

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