Scientific research must take gender into account
By Londa Schiebinger. 2014
85 citations recorded by the source corpus.
Subfields: Public Health, Environmental and Occupational Health, Reproductive Medicine
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In Public Health, Environmental and Occupational Health
In Reproductive Medicine
Citations in the corpus
- Assessing gender bias in machine translation: a case study with Google Translate (2018, background): “On a 2014 article, Londa Schiebinger suggested that scientific research fails to take gender issues into account, arguing that the phenomenon of male defaults on new technologies such as Google Translate provides a window into this asymmetry [35].”
- Gender Bias in Machine Translation (2021, background): “While these studies focused on contrastive phenomena, Schiebinger (2014)9 went beyond linguistic insights, calling for a deeper understanding of gender bias.”
- How to Measure Gender Bias in Machine Translation: Optimal Translators, Multiple Reference Points (2020, background): “Google Translate uses hundreds of millions of texts collected from the Internet in order to determine its translations (Kuczmarski, 2018), but researches show that online texts contain more male-related words than female-related ones (Bolukbasi et al., 2016; Schiebinger, 2014).”