What We Know About Trump's COVID-Skeptic Pick to Lead NIH
- Bias Rating
-18% Somewhat Liberal
- Reliability
90% ReliableExcellent
- Policy Leaning
-20% Somewhat Liberal
- Politician Portrayal
1% Positive
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
10% Positive
- 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:
62% : On Tuesday, Trump continued the trend when he tapped Dr. Jay Bhattacharya, a Stanford University-educated physician and economist, to be the next director of the National Institutes of Health.59% : "Together, Jay and RFK, Jr. will restore NIH to a Gold Standard of Medical Research as they examine the underlying causes of, and solutions to, America's biggest Health challenges, including our Crisis of Chronic Illness and Disease," Trump wrote on TruthSocial Tuesday.
51% : President-elect Donald Trump has been rolling out some predictably unorthodox people to lead the nation's health agencies, nominating Robert F. Kennedy Jr. to lead the Health and Human Services Department and celebrity doctor Mehmet Oz to oversee the Centers for Medicare & Medicaid Services.
*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.