Race at the Top: white and Asian Americans and the push for equity in education
- Bias Rating
-8% Center
- Reliability
N/AN/A
- Policy Leaning
8% Center
- Politician Portrayal
-60% 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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-100%
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100%
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Contributing sentiments towards policy:
63% : Expanding on my interest in increasing educational opportunities, I have just completed a book on affirmative action which will be released in October.52% : Some even moved their children to private schools to provide them environments with less academic competition.
47% : Conservatives, such as those behind the SFFA v Harvard lawsuit claiming affirmative action in admissions amounts to racial discrimination toward Asian Americans, are using Asian American academic achievement to further their anti-racial justice agenda.
43% : Liberals often respond to this logic by rejecting the possibility that Asian Americans ever experience racial discrimination, as if we have to deny the possibility of anti-Asian racism in education in order to defend affirmative action.
41% : That book will use social science research to analyze arguments that have been made for and against affirmative action in college admissions.
*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.