This Supreme Court Case Could Spell the End of Affirmative Action
- Bias Rating
-10% Center
- Reliability
N/AN/A
- Policy Leaning
10% Center
- Politician Portrayal
68% 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.
Sentiments
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- Liberal
- Conservative
Sentence | Sentiment | Bias |
---|---|---|
"The Supreme Court is hearing a case on affirmative action, causing concerns that the court may put the final nail in the coffin for school integration efforts." | Positive | 8% Conservative |
"Lisa Crooms-Robinson, who spoke to The Root in late June, says she believes the courts will side against affirmative action:The higher ed cases on the docket for the next time, said Crooms-Robinson." | Positive | 0% Conservative |
"But just because affirmative action narrowly survived an attack in 2016 doesn't mean it'll make it through this court." | Negative | -6% Liberal |
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Bias Meter
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Contributing sentiments towards policy:
54% : The Supreme Court is hearing a case on affirmative action, causing concerns that the court may put the final nail in the coffin for school integration efforts.50% : Lisa Crooms-Robinson, who spoke to The Root in late June, says she believes the courts will side against affirmative action:"The higher ed cases on the docket for the next time," said Crooms-Robinson.
47% : But just because affirmative action narrowly survived an attack in 2016 doesn't mean it'll make it through this court.
44% : Based on the court's make-up and earlier willingness to upend decades of precedence by overturning Roe v. Wade, things are likely not looking good for the future of affirmative action.
35% : The Supreme Court may be gearing up to land the final blow in the decades long debate over 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.