Looking like a Language, Sounding like a Race

By J. Rosa. 2018

Looking like a Language, Sounding like a Race examines the emergence of linguistic and ethnoracial categories in the context of contemporary US constructions of Latinidad. The book draws from more than 24 months of ethnographic and sociolinguistic fieldwork to analyze the racialization of language as a central form of modern governance. It focuses specifically on youth socialization to US Latinidad as a contemporary site of political anxiety, “raciolinguistic” transformation, and urban inequity. Rosa’s account studies the fashioning of Latinidad in a highly segregated Chicago high school whose student body is more than 90% Mexican and Puerto Rican. Rosa shows how anxieties surrounding language, race, and identity produce an administrative project that seeks to transform “at risk” Mexican and Puerto Rican students into “Young Latino Professionals.” This institutional effort, which requires students to learn to be—and sound like—themselves in highly studied ways, reflects administrators’ attempts to navigate a precarious urban terrain in the city grappling with some of the nation’s highest youth homicide, drop-out, and teen pregnancy rates. Rosa explores the ingenuity of his researchers participants’ creative responses to these forms of marginalization through the contestation of political, ethnoracial, and linguistic borders. The detailed engagement with the relationship between linguistic and ethnoracial category-making that develops throughout the book points to the raciolinguistic, historical, political, and economic dynamics through which people come to look like a language and sound like a race across cultural contexts.

Subfields: Linguistics

How researchers see this paper

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

In Linguistics

Citations in the corpus

Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus (2021, background): “, 2020) and exacerbates existing (language-based) racial inequality (Rosa, 2019) as well as stigmatization of LGBTQ+ identities (Pinsof and Haselton, 2017).”
Challenges in Automated Debiasing for Toxic Language Detection (2021, methodology): “, 2019), thereby exacerbating racial inequality (Rosa, 2019).”
Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection (2021, background): “Our findings suggest that annotators perceive that AAE posts are associated with the Black racial identity (Rosa, 2019), which could cause those who score highly on the RACISTBELIEFS scale to annotate them as racist, potentially as a form of colorblind racism (e.”
Looking closely and listening carefully: A sociocultural approach to understanding the complexity of Latina/o/x students’ everyday language (2020, background): “This tendency to presume a gap is grounded in longer histories and broader contexts related to the racialization of Latina/o/x populations (Flores & Rosa, 2015; Rosa, 2009).”
Unsettling race and language: Toward a raciolinguistic perspective (2017, background): “Rosa (2018) analyzes one such process of raciolinguistic enregisterment through which people come to look like a language and sound like a race.”
Handling Bias in Toxic Speech Detection: A Survey (2022, unknown): “, to not promote minority exclusion [71, 101].”