
Ketanji Brown Jackson Will Recuse Herself from Harvard Race Case
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6% Center
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*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.

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*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.

28% Negative
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Reliability Score Analysis
The Reliability Score of the article is determined on a percentage score basis from 0 to 100%.
- Opposite Sources as Poor for the lower number of sources with different viewpoints.
- Unique Sources as Poor for the lower number of different sources.
- Multiple Sources as Poor for the lower number of total sources.
- Multiple Quotes as Poor for the lower number of quotes used in the article.
- Quote Length as Poor for the lower number of words used in each quote.
Opposite Sources: 0% Poor (Grade F) Unique Sources: 0% Poor (Grade F) Multiple Sources: 0% Poor (Grade F) Multiple Quotes: 0% Poor (Grade F) Quote Length: 0% Poor (Grade F)
Bias Score Analysis
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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Policy Leaning Analysis
This article includes the following sentiments, providing an average bias score of 12% Conservative:
- 1 negative sentiment for Affirmative Action
"Supreme Court nominee Judge Ketanji Brown Jackson said Wednesday that she would recuse herself from an upcoming case alleging racial discrimination against Harvard University over affirmative action if she were to be confirmed by the Senate."
Politician Portrayal Analysis:
This article includes the following Politician Portrayal sentiments, providing an average sentiment of 28% Negative and bias score of -16% Liberal:
1 negative sentiment for Ted Cruz
"Judge Jackson confirmed that she would recuse herself under questioning from Sen. Ted Cruz (R-TX)."
This is a negative sentiment.
"There were also questions about whether Judge Jackson could rule fairly on the case, given that she was specifically selected by President Joe Biden because of her race and her gender."
This is a negative sentiment.
Policies:
Affirmative ActionPoliticians:
Joe BidenTed Cruz
Sentiments
- Conservative
-12% "Supreme Court nominee Judge Ketanji Brown Jackson said Wednesday that she would recuse herself from an upcoming case alleging racial discrimination against Harvard University ..."
-22% Judge Jackson confirmed that she would recuse herself under questioning from Sen. Ted Cruz (R-TX)."
*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. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.
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Contributing sentiments towards policy:
44% : Supreme Court nominee Judge Ketanji Brown Jackson said Wednesday that she would recuse herself from an upcoming case alleging racial discrimination against Harvard University over affirmative action if she were to be confirmed by the Senate.*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.