Key Revelations From Fauci's House COVID Testimony
- Bias Rating
-10% Center
- Reliability
75% ReliableGood
- Policy Leaning
-10% Center
- Politician Portrayal
-29% 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
14% Positive
- Liberal
- Conservative
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:
61% : First, how and why a group of top scientists reversed their initial assessments in a matter of days despite the fact that Communist China was utterly uncooperative in sharing vital information or data, imposing government restrictions on any scientific information coming out of China while suppressing the views of dissident scientists.56% : As the former director of National Institute of Allergy and Infectious Diseases, Fauci had responsibility for overseeing billions of dollars in grants for research activities.
48% : As of this writing, Morens and Moore, who assisted Morens in hiding public information, are still employed by the National Institutes of Health.
34% : Nonetheless, the danger of potentially risky grants (such as viral gain of function funding) to biomedical research organizations operating overseas, especially in unfriendly countries, requires urgent congressional attention.
*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.