NYU study reveals states with highest racial biases against Asian Americans
[Source]
A study conducted by researchers at New York University (NYU) has found that racial biases against Asian Americans vary significantly across U.S. states.
Republican-majority states: In the study recently published in Sage Journals, researchers found that biases are affected by factors like the Asian population size and the political leaning of the state.
Republican-majority and swing states displayed greater stereotyping of Asian-born and Asian Americans. European Americans in these states are also more prone to perceiving Asians as foreigners. This bias is particularly noticeable in states like West Virginia, Iowa, South Carolina, Ohio and Wisconsin.
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States with a large Asian population size: As for states with older median ages and higher percentages of Asians, the data showed less explicit bias against Asians and Asian Americans. These states include Hawaii, the District of Columbia, California, Nevada and Texas.
“Our study shows that experiences of Asians and Asian Americans are likely to significantly differ depending on their state of residence, with residents of some states expressing more biased views that Asian Americans are not as ‘American’ as whites,” Nari Yoo, a PhD candidate who led the research, said in a statement. “These insights should guide future research and interventions to address biases effectively at the state level.”
The study also suggests that growing diversity in some states may increase bias “due to perceptions of threat and competition, which may be amplified by anti-immigrant sentiment.”
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About the study: The research aims to improve understanding and guide interventions to address biases effectively at the state level, particularly in light of increased violence and abuse against Asian Americans during the COVID-19 pandemic.
The coauthors include professor Harvey Nicholson Jr. of the University of Toronto-St. George Campus, professor Doris Chang of NYU Silver and professor Sumi Okazaki of NYU Steinhardt.
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