
Will Trump Follow the Law in Punishing Harvard?
- Bias Rating
- Reliability
100% ReliableExcellent
- Policy Leaning
10% Center
- Politician Portrayal
-52% 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
-32% Negative
- Liberal
- Conservative
Sentence | Sentiment | Bias |
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
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Contributing sentiments towards policy:
59% : William A. Stock, managing partner at Klasko Immigration Law Partners, wrote by email that while colleges are subject to an SEVP recertification process every two years, U.S. Immigration and Customs Enforcement has the authority to conduct off-cycle reviews at any time.57% : Remember, Tax Exempt Status is totally contingent on acting in the PUBLIC INTEREST!"
52% : "The IRS would have to do an audit of Harvard and determine that there were one or more reasons why Harvard did not meet the requirements for tax-exempt status," Brunson said.
50% : "My assumption is that the Trump administration is going to argue that Harvard violated a fundamental public policy, either by not reining in pro-Palestinian, anti-Israel protesters enough, or something related to [diversity, equity and inclusion]," Brunson explained.
49% : Trump wrote on Truth Social last week.
48% : While stripping universities of tax-exempt status is rare, it has happened before.
31% : Experts noted that losing SEVP certification would cause a substantial loss of international students and hit research projects hard -- even as such endeavors are already in flux from the Trump administration's freezes on federal funding -- given the high share of Ph.D. students who come from other countries.
*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.