
Caroleene Dobson: Harvard's hotbed of antisemitic hate must be ended - Yellowhammer News
- Bias Rating
-10% Center
- Reliability
20% ReliableLimited
- Policy Leaning
-10% Center
- Politician Portrayal
-19% Negative
Continue For Free
Create your free account to see the in-depth bias analytics and more.
Continue
Continue
By creating an account, you agree to our Terms and Privacy Policy, and subscribe to email updates. Already a member: Log inBias 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.
Sentiments
-9% Negative
- Liberal
Sentence | Sentiment | Bias |
---|---|---|
Unlock this feature by upgrading to the Pro plan. |
Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
Bias Meter
Extremely
Liberal
Very
Liberal
Moderately
Liberal
Somewhat Liberal
Center
Somewhat Conservative
Moderately
Conservative
Very
Conservative
Extremely
Conservative
-100%
Liberal
100%
Conservative

Contributing sentiments towards policy:
57% : Among the necessary actions outlined in the letter were reforming Harvard's schools, programs, and groups that have a history of antisemitic bias or politicization; auditing faculty members who discriminated against Jewish or Israeli students or incited students to participate in anti-Jewish rallies; ending hiring practices that are based upon "ideological litmus tests" or require compliance with a specific political philosophy; toughening student discipline policies and prohibiting campus groups that advocate criminal activity, violence, and harassment; and others.53% : I know all of these things because I attended and graduated from Harvard along with a small group of like-minded conservative classmates that included Vivek Ramaswamy, who brainstormed the Department of Government Efficiency with Elon Musk.
*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.