Evidence map›Paper›PMID 36196221›Full record

ArticleBioscience2022

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

Emma Steigerwald, Valeria Ramírez-Castañeda, Débora Y C Brandt, András Báldi, Julie Teresa Shapiro, Lynne Bowker, Rebecca D Tarvin

Abstract read
In one paragraph

Article in Bioscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed.

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  15. Strategies for advancing inclusive biodiversity research through equitable practices and collective responsibility.Conservation biology : the journal of the Society for Conservation Biology · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Emma SteigerwaldUniversity of California, Berkeley, Berkeley, California, United States.ORCID https://orcid.org/0000-0003-1027-1421
Valeria Ramírez-CastañedaUniversity of California, Berkeley, Berkeley, California, United States.
Débora Y C BrandtUniversity of California, Berkeley, Berkeley, California, United States.
András BáldiCentre for Ecological Research, Vácrátót, Hungary.
Julie Teresa ShapiroBen-Gurion University of the Negev, Be'er Sheva, Israel.
Lynne BowkerUniversity of Ottawa, Ottawa, Ontario, Canada.
Rebecca D TarvinUniversity of California, Berkeley, Berkeley, California, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

artificial intelligencemultilingualismneural networksplain languagescientific communication

Identifiers

PMID36196221
PMCPMC9525128

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.