Language and Racialization

By Anne H. Charity Hudley. 2017

Subfields: Linguistics, Social Sciences & Humanities

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Linguistics

1. Hal Daumé Iii
2. Dan Jurafsky
3. J. Rickford
4. Su Lin Blodgett

In Social Sciences & Humanities

1. Hanna M. Wallach
2. Sharad Goel
3. Hal Daumé Iii
4. Dan Jurafsky
5. J. Rickford
6. Solon Barocas
7. Su Lin Blodgett
8. Adrian Weller

Citations in the corpus

• Language (Technology) is Power: A Critical Survey of “Bias” in NLP (2020, background): “As a starting point for reorienting work analyzing “bias” in NLP systems around this question, we 3Language ideologies encompass much more than this; see, e.g., Lippi-Green (2012), Alim et al. (2016), Rosa and Flores (2017), Rosa and Burdick (2017), and Charity Hudley (2017). provide the following c”
• Racial disparities in automated speech recognition (2020, methodology): “DDMs do not capture a speaker’s entire linguistic system (36, 37), but, in our setting, the measure we use provides insight into drivers of the ASR performance gaps we see.”