'It doesn't have a clue': Elena Kagan blasts conservative majority over 'frightening' decision on pollution
- Bias Rating
-80% Very Liberal
- Reliability
N/AN/A
- Policy Leaning
24% Somewhat Conservative
- Politician Portrayal
-63% 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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- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
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Contributing sentiments towards policy:
50% : The 6-3 ruling in West Virginia v. Environmental Protection Agency limited the federal government's ability to regulate carbon emissions from power plants, which Kagan lamented in her dissent had weakened "the power to respond to the most pressing environmental challenge of our time.""The subject matter of the regulation here makes the Court's intervention all the more troubling," she wrote.48% : U.S. Supreme Court justice Elena Kagan rebuked the majority who stripped the Environmental Protection Agency of some of its regulatory powers.
45% : While EPA had the power to regulate individual plants, the court ruled, Congress had not given it such expansive powers to set limits for all electricity generating units.
45% : "It is not plausible that Congress gave EPA the authority to adopt on its own such a regulatory scheme," they said.
43% : The ruling was a significant victory for the coal mining and coal power industry, which had been targeted for tough limits in 2015 by the administration of then president Barack Obama in an effort to slash carbon pollution.
38% : It was also a victory for conservatives fighting government regulation of industry, with the court's majority including three right-wing justices named by former president Donald Trump, who had sought to weaken the EPA.
*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.