Pentagon took 3 days to inform White House's NSC of Austin's hospitalization

Jan 06, 2024 View Original Article
  • Bias Rating

    10% Center

  • Reliability

    75% ReliableGood

  • Policy Leaning

    N/A

  • Politician Portrayal

    66% Negative

Bias 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

Overall Sentiment

7% Positive

SentenceSentimentBias
"That strategy has worked well for him, as he's kept President Joe Biden's confidence and is viewed as a key figure in maintaining Western support for delivering weapons to Ukraine."
Positive
22% Conservative
"Still, when Gen. Eric Smith, commandant of the Marine Corps, was hospitalized after a heart attack on Oct. 29, for example, DOD put out a statement within hours."
Negative
-16% Liberal
"There is no standard protocol for when to aounce a defense secretary's hospitalization or temporary inability to do the job, said Brad Carson, formerly under secretary and chief management officer of the Army, though he added it could depend on the severity of Austin's condition."
Negative
-20% Liberal
"Hagel said DOD may have had a good reason to keep Austin's hospitalization quiet for a time, but he still said keeping mum for so long was the wrong call."
Negative
-24% Liberal
"Chuck Hagel, the former senator who served as defense secretary during the Obama administration, said the Pentagon absolutely had to let the NSC know about Austin's condition and whereabouts."
Negative
-40% Liberal
"Chuck Hagel, the former senator who served as defense secretary during the Obama administration, said the Pentagon absolutely had to let the NSC know about Austin's condition and whereabouts."
Negative
-40% Liberal

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-100%
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100%
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*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.

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