Supreme Court considers Harvard and University of North Carolina's use of affirmative action. Here's what you need to know | CNN Politics

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Published Oct 30, 2022
Source Analysis Score
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The Source Analysis Score focuses on assessing the quality of sources and quotes used including their number, lengths, uniqueness, and diversity.
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Bias Rating
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The Bias Rating is computed based on a number of factors including bias loaded words, sentiments towards certain political policies, author bias towards politicians, and the amount of tone found in the article.

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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.

Policy Leaning
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The policy leaning score is derived from author biases for or against a certain political policy, as found in articles.

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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.

Politician Portrayal
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The politician leaning score is determined by the author's tone and leaning towards the specific politician mentioned in the article.

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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.

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.


Policy Leaning Analysis

This article includes the following sentiments, providing an average bias score of 10% Conservative:

  • 1 negative sentiment for Affirmative Action
  • 1 negative sentiment for Abortion


Policies:

Abortion
Affirmative Action

Sentiments

  •   Conservative
-16% "Supreme Court precedent allows the consideration of race, but the court’s new composition of conservative justices did not hesitate last term to overturn decades ..."
-24% "The firm is composed of several former clerks of Justice Clarence Thomas who has been a critic of 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. The rating is an independent analysis and is not affiliated nor sponsored by the news source or any other organization.

Extremely
Liberal

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Moderately
Liberal

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Center

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Contributing sentiments towards policy:

42% : Supreme Court precedent allows the consideration of race, but the court’s new composition of conservative justices did not hesitate last term to overturn decades old precedent in a case that curtailed a federal right to abortion.
38% : The firm is composed of several former clerks of Justice Clarence Thomas who has been a critic of 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.

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