If Affirmative Action Ends, College Admissions May Be Changed Forever

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Published Jan 15, 2023
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.
70% ReliableGood
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.

-2% 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.

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 Excellent for a very high number of different sources.
  • Multiple Sources as Excellent for a very high number of total sources.
  • Multiple Quotes as Excellent for a very high number of quotes used in the article.
  • Quote Length as Fair for an average 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 -2% Liberal:

  • 1 negative sentiment for Border Wall
  • 1 positive sentiment and 2 negative sentiments for Affirmative Action.


Policies:

Affirmative Action
Border Wall

Sentiments

  •   Liberal
  •   Conservative
8% "In cases against Harvard and the University of North Carolina, the Supreme Court is widely expected to overturn or roll back affirmative action in ..."
0% "so, those measures will not stave off a decline in underrepresented students if the Supreme Court overturns affirmative action, Dr. McGann said.""
-2% "”Some opponents of affirmative action have argued that preferences should be based on socioeconomic class rather than race, and they have also opposed special ..."
-16% "Title 42: The court said that the pandemic-era policy that restricted migration at the southern border would remain in place for now, delaying the potential ..."
-20% "Citing drops in applications following statewide bans on affirmative action in Michigan and California, he said that some students from underrepresented groups may simply ..."

*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
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Center

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Contributing sentiments towards policy:

54% : In cases against Harvard and the University of North Carolina, the Supreme Court is widely expected to overturn or roll back affirmative action in college admissions.
50% : so, those measures will not stave off a decline in underrepresented students if the Supreme Court overturns affirmative action, Dr. McGann said.
49% : ”Some opponents of affirmative action have argued that preferences should be based on socioeconomic class rather than race, and they have also opposed special considerations that benefit the affluent.
42% : Title 42: The court said that the pandemic-era policy that restricted migration at the southern border would remain in place for now, delaying the potential for a huge increase in unlawful crossings.
40% : Citing drops in applications following statewide bans on affirmative action in Michigan and California, he said that some students from underrepresented groups may simply not apply.

*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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