Language Inclusion in Ecological Systematic Reviews and Maps: Barriers and Perspectives

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1002/jrsm.1699. This is version 1 of this Preprint.

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Authors

Kelsey Hannah , Neal R Haddaway, Richard Fuller, Tatsuya Amano

Abstract

Systematic reviews and systematic maps are considered the most reliable form of research evidence in science, but they often neglect non-English-language literature. Non-English-language literature can provide important evidence, especially in ecological studies, which may also influence findings and alter conclusions. To understand the barriers that might limit authors’ ability or intent to find and include non-English-language literature, we assessed factors that may predict the inclusion of non-English language literature in ecological systematic reviews and maps, as well as the review authors' perspectives.
We assessed all systematic reviews and maps published in the journal Environmental Evidence (n=72) prior to January 2022, extracting data related to the study's level of language inclusiveness and its potential predictors. We also surveyed the corresponding author from each paper (n=32 responses), gathering information on the barriers to the inclusion of non-English language literature.
Thirty-two (44%) of the 72 assessed reviews did not search or include any non-English language literature. The most common justifications for this were resource and time constraints. Regression analysis showed that systematic reviews and maps involving more authors, authors from a greater number of countries, especially those where English is not the primary language, and author teams that spoke more languages searched in a significantly greater number of non-English languages. Our survey identified that the most common barriers to use of non-English language methods in reviews were the lack of relevant language skills within the review team and limited funding.
Our study suggests that greater language diversity in the review team could help increase language inclusion and thus create more comprehensive and less biased systematic reviews and maps. Machine translation combined with the use of the review team’s language skills may help to reduce the financial and resource burdens of translation. The cost of translation could also be included in funding applications to alleviate the financial burden.

DOI

https://doi.org/10.32942/X28K5V

Subjects

Other Ecology and Evolutionary Biology

Keywords

evidence synthesis, language bias, biodiversity conservation, language barriers, Non-English language literature

Dates

Published: 2023-06-09 19:21

License

CC BY Attribution 4.0 International

Additional Metadata

Language:
English

Conflict of interest statement:
None

Data and Code Availability Statement:
https://github.com/KHannah12/UseofNEL/