Karla Magaña, Devin Judge-Lord
University of Michigan
Racialization is the level to which the public and elite language used to describe an institution and its actions evoke race and thus make relevant and highlight debates around racial inequality or racial resentments.
How has that changed over time?
How does that vary across different contexts?
Perceived liberal-conservative leaning via expert surveys, appointments, donations, and voting patterns
Our study brings race to the forefront in understanding how agencies are perceived
(Clinton and Lewis (2008); Richardson et al. (2019); Richardson et al. (2024); Epstein (1999); Nixon (2004); Chen and Johnson (2014); Maranto (2005); Maranto and Hult (2004); Bertelli and Grose (2011))
Racialized history shapes perceptions of agencies
We introduce a quantitative measure of racialized institutions, building on rich qualitative research in ADP and REP
(King, 1999; Choi and Rainey, 2010; Schickler, 2016; Tate, 2003; White and Laird, 2020; Mansbridge, 1999; Watkins-Hayes, 2009; Minta, 2009; Juenke and Preuhs, 2012; Hayes and Hibbing, 2017)
Racial attitudes & framing affect policy preferences
Our work bridges public opinion research with institutions, elite decision-making, and policy outcomes.
(Gilens, 1999; Kellstedt, 2003; Hutchings & Valentino, 2004; Bartels, 2020; Stephens-Dougan, L., 2020; O’Brian, 2024)
Mandate for Leadership (Project 2025)
New York Times
Rulemaking Documents
Figure 1: New York Times Articles With Racialized Words By Agency, 2005-2025
Figure 2: New York Times Articles With Racialized Words, 2005-2025
Affirmative Action; African American; African Americans; Africans; Alaskan Native; Alien; American Indian; Anti-discrimination; Anti-racism; Anti-racist; Antidiscrimination; Antiracism; Antiracist; Arab American; Arabs; Asian American; Asians; BIPOC; Biracial; Black American; Black Americans; Black children; Black lives; Black Man; Black Men; Black People; Black Person; Black Students; Black Woman; Black Women; Border Crisis; Citizenship; Civil Rights; Color of their skin; Colorism; Communities of Color; Critical Race Theory; Cultural competence; Culturally competent; D.E.I.; DACA; DEI; Diversity and inclusion; Diversity Equity; Diversity lottery; Diversity objectives; Diversity officer; Diversity visa; Diversity, Equity; Diversity, Equity, and Inclusion; Drug Cartel; Enslavement; Equal Opportunity; Equity agenda; Ethnic; Ethnic Diversity; Ethnicity; Gang; HBCU; Hispanic; Historically Black College and University; Illegal Alien; Illegal aliens; Illegal Immigrant; Illegal immigrants; Illegal immigration; Illegal migration; Immigrant; Immigration; Indian Education; Indigenous groups; Indigenous people; Indigenous peoples; Indigenous person; Inequality; Inequitable; Intersectionality; Latina; Latinas; Latino; Latinos; Latinx; Men of Color; Meritocracy; Mexican Cartel; Mexican Drug Cartel; Mexicans; Middle Eastern or North African Ancestry; Migrant; Minority Populations; Minority status; Minority-Serving; Mixed race; Mixed-race; Multicultural; Multiracial; Muslim; Nationality; Native American; Native-Serving; Non-white; Nonminority; Oppression; Oppressors; Pacific Islander; People of Color; People of Minority Status; Person of Color; Predominately white; Prejudice; Puerto Ricans; Racial; Racial Diversity; Racial Identity; Racial Inequality; Racial Inequities; Racial Injustices; Racial Justice; Racially; Racism; Racist; Secure Border; Secure the Border; Securing the Border; Skin color; Slavery; Social Justice; Socioeconomic; Socioeconomically; South Asian American; South Asians; Stereotypes; Structural Racism; Systemic Racism; Tribal; Tribe; Tribes; Unaccompanied Alien Children; Underrepresented Communities; Underrepresented Minorities; Underserved Communities; Underserved Populations; Vulnerable populations; White American; White Americans; White institutions; White People; White Person; White Privilege; White students; White supremacist; White supremacy; Woke; Wokeism; Women of Color; Xenophobia; Xenophobic
Figure 4: Agency Rules with Racialized Language, 2005-2025
For each source, we have two counts: \(r_{i}\) (the count of racialized documents/articles/sentences about agency \(i\)) and \(y_{i}\) (the total document/article/sentence about agency \(i\)).
Percent Racialized \(x_i = \frac{\sqrt{r_{i}}}{\sqrt{y_{i}}}\) (variance stabilized)
Racialization Score \(z_{i} = \frac{x_i - \bar{x}}{sd(x)}\) (standardized, mean 0, standard deviation 1)
Figure 5: Racialized Words in Project 2025 Mandate For Leadership
Figure 6: Racialization in Rulemaking vs. Project 2025
Figure 7: Racialization in Project 2025 vs. New York Times
Figure 8: Racialization in Rulemaking vs. New York Times
Figure 9: Correlation Between Racialization and Perceived Ideology
Figure 10: Correlation Between Racialization and Perceived Ideology
How can we make these measures useful?
Contact: kmagana@umich.edu | judgelor@umich.edu
Figure 11: Distribution of Racialized Words in Mandate For Leadership (Project 2025)
Figure 12: Distribution of Racialized Words in New York Times Articles, 2005-2025
Figure 13: Distribution of Racialized Words in Proposed and Final Rules, 2005-2025
“Racialization and Perceived Institutional Ideology” - Karla Magaña & Devin Judge-Lord