Supreme Court Will Hear Admissions Cases, Suggesting Conservatives May Target Affirmative Action
- Bias Rating
-4% Center
- Reliability
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- Policy Leaning
-4% Center
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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.
Sentiments
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- Conservative
Sentence | Sentiment | Bias |
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"The last time the Supreme Court weighed in on affirmative action was in 2016, when the justices unexpectedly ruled 4 to 3 to uphold the University of Texas at Austin's race-conscious admissions policy." | Positive | 14% Conservative |
"The Supreme Court's decision to take that case will make proponents of affirmative action nervous." | Positive | 8% Conservative |
"Students for Fair Admissions' goal has been to get these case before the Supreme Court so that its firm majority of conservative justices will strike down affirmative action altogether." | Positive | 4% Conservative |
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
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Contributing sentiments towards policy:
57% : The last time the Supreme Court weighed in on affirmative action was in 2016, when the justices unexpectedly ruled 4 to 3 to uphold the University of Texas at Austin's race-conscious admissions policy.54% : The Supreme Court's decision to take that case will make proponents of affirmative action nervous.
52% : Students for Fair Admissions' goal has been to get these case before the Supreme Court so that its firm majority of conservative justices will strike down affirmative action altogether.
40% : Additionally, Chief Justice John G. Roberts Jr., who has occasionally sided with the court's liberal bloc on other key votes, has previously made clear his stance against affirmative action.
*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.