Experts predict Trump will tap his own appellate judges for Supreme Court in the event of a retirement
- Bias Rating
90% Very Conservative
- Reliability
50% ReliableFair
- Policy Leaning
34% Somewhat Conservative
- Politician Portrayal
-23% 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
27% Positive
- Liberal
- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
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Contributing sentiments towards policy:
61% : Trump appointed three justices to the Supreme Court, all three of whom were under the age of 55 at the time of their appointments.59% : "And, so, it's actually quite clever of Trump at that time to release the names and stick to them as people he would appoint to the Supreme Court because it really committed him in the minds of conservatives.
54% : Likewise, Trump appointed more than 50 federal appellate judges during his first term.
50% : "In anticipation of his first administration in 2016, Trump released a list of potential Supreme Court nominees.
46% : "I think Trump, given his practices, would probably favor appointing people that he had appointed already to the circuit courts," Yoo said.
44% : "Going by who Trump picked already, he picked people who seemed committed to originalism, people who had Justice Department backgrounds.
44% : Yoo said he does not expect Trump will repeat himself this time around with an updated list.
43% : "Yoo added that if there was a retirment, Trump would likely look to the appellate judges he appointed during his first term as potential nominees.
41% : "Trump may have the opportunity to further bolster the conservative majority by appointing younger justices if any justices retire.
25% : Trump will continue to fall back on certain judges.
*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.