Biden pardon leaves Fauci with 'legal peril' * WorldNetDaily * by Paul D. Thacker, Real Clear Wire
- Bias Rating
-10% Center
- Reliability
90% ReliableExcellent
- Policy Leaning
16% Somewhat Conservative
- Politician Portrayal
-41% 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
-9% Negative
- Liberal
- Conservative
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Reliability Score Analysis
Policy Leaning Analysis
Politician Portrayal Analysis
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Contributing sentiments towards policy:
58% : A month prior to Fauci's hearing with Paul, Columbia University professor Jeffrey Sachs confirmed that U.S.-funded research at the WIV consisted of gain-of-function virus research that could have started the pandemic.52% : Another area of potential inquiry is Fauci's congressional testimony last summer denying his use of private email to conduct official business, "Let me state for the record that to the best of my knowledge I have never conducted official business via my personal email," Fauci wrote in his sworn statement to Congress.
49% : "In the days before Biden offered the pardon to Fauci, along with other critics of Donald Trump, some experts who have followed Fauci's career and handling of the pandemic, as well as members of the Trump transition team, reiterated their assertion that Fauci perjured himself on several occasions during the pandemic - especially regarding his agency's links to the lab in Wuhan, China, that might have created the virus that causes COVID-19.
49% : The NIH did not respond to comment about Fauci's use of private email to conduct government business with reporters.
24% : Despite reporting that Trump is bent on revenge, the appetite among MAGA appointees for holding Fauci accountable hasn't been particularly vocal.
*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.