Why the Supreme Court decision on affirmative action matters
- Bias Rating
-44% Medium Liberal
- Reliability
90% ReliableExcellent
- Policy Leaning
-44% Medium Liberal
- Politician Portrayal
-54% Negative
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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.
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
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Contributing sentiments towards policy:
70% : The ruling in the two cases hands opponents of affirmative action a major victory.61% : In the absence of race in the admissions process, Kelly Slay, an assistant professor at Vanderbilt University who studies affirmative action, expects to see colleges increase targeted recruitment, expand financial aid including free-college programs, and go test-optional, in an effort to maintain their ethnic and racial diversity.
55% :What happens nextThis opinion comes less than a decade since the last time the high court ruled on affirmative action.
37% : The attorney general of Oklahoma filed a brief on behalf of several states in support of the plaintiffs in the two cases: "The University of Oklahoma, for example, remains just as diverse today (if not more so) than it was when Oklahoma banned affirmative action in 2012."
*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.