Affirmative action's future waits as SCOTUS hears arguments

  • Bias Rating

    2% Center

  • Reliability

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  • Policy Leaning

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Bias Score Analysis

The A.I. bias rating includes policy and politician portrayal leanings based on the author’s tone found in the article using machine learning. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral.

Sentiments

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Bias Meter

Contributing sentiments towards policy:

61% : "The majority of Asian Americans have consistently supported affirmative action, which allows all students to share their whole story that is inclusive of their identities, histories, and lived experiences."
59% :The University of Pennsylvania filed an amicus brief in support of Harvard and the University of North Carolina's use of affirmative action.
58% :Dozens of groups, including the NAACP and the Asian-American Legal Defense Fund, said the court needs to continue to uphold affirmative action.
52% : At least nine states, including Florida, California, and Michigan, have ended affirmative action policies in state universities and colleges.
47% :McClellan and others watching Monday's arguments say that a decision to overturn affirmative action could make an already difficult-to-navigate college admissions process even harder for students of color.
46% : According to the NAACP, overturning affirmative action hurts students of color who face inequity throughout their schooling, missing out on opportunities, and "despite being eminently qualified, are not able to gain that competitive edge to assure their admission."
40% : The court heard two cases surrounding affirmative action -- the policy some colleges and universities use to improve educational opportunities for historically underrepresented groups.
36% : If affirmative action is banned, McCellan says diverse student population numbers are likely to decrease.

*Our bias meter rating uses data science including sentiment analysis, machine learning and our proprietary algorithm for determining biases in news articles. Bias scores are on a scale of -100% to 100% with higher negative scores being more liberal and higher positive scores being more conservative, and 0% being neutral. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.

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