Unsettling race and language: Toward a raciolinguistic perspective

By J. Rosa, N. Flores. 2017

Subfields: Linguistics, Social Sciences & Humanities

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Citations in the corpus

Language (Technology) is Power: A Critical Survey of “Bias” in NLP (2020, background): “This perspective belongs to a broader set of raciolinguistic ideologies (Rosa and Flores, 2017), which also produce allocational harms; speakers of AAE are frequently penalized for not adhering to dominant language practices, including in the education system (Alim, 2004; Terry et al., 2010), when…”
Ethical and social risks of harm from Language Models (2021, background): “For instance, the United States has a longstanding history of disenfranchising and stigmatising speakers of African-American Vernacular English (AAVE) (Rosa and Flores, 2017), which is replicated by the lower performance of language-model-based toxicity detection on AAVE.”
Repairing the Cracked Foundation: A Survey of Obstacles in Evaluation Practices for Generated Text (2022, background): “Beyond performance drops, excluding dialects from datasets can often be seen as akin to de-legitimizing the language and their speakers (Rosa and Flores, 2017).”
Challenges in Automated Debiasing for Toxic Language Detection (2021, background): “For example, viewing AAE as a more toxic or less proper variety of English is a form of linguistic discrimination that upholds racial hierarchies in the United States (Rosa and Flores, 2017).”
Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection (2021, background): “This category has been shown to be considered “worse” English by non-AAE speakers (Hilliard, 1997; Blake and Cutler, 2003; Champion et al., 2012; Beneke and Cheatham, 2015; Rosa and Flores, 2017), and is often mistaken as obscene or toxic by humans and AI models (Spears et al.”
A Survey of Race, Racism, and Anti-Racism in NLP (2021, background): “continue to justify social and economic exclusion (Rosa and Flores, 2017).”
Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selection (2022, background): “Language Ideologies Language ideologies have been widely explored in the sociolinguistics literature (Gal and Irvine, 1995; Rosa and Flores, 2017; Craft et al., 2020, inter alia ).”
Deconstructing NLG Evaluation: Evaluation Practices, Assumptions, and Their Implications (2022, background): “If e.g., grammaticality is understood as adherence to Mainstream U.S. English grammar rules (often the case due to standard language ideologies (Rosa and Flores, 2017)), then it will exclude other language varieties, like Appalachian English (Luhman, 1990) or African American Language (Lanehart,…”